SERIES
Maintaining the Momentum while
Addressing Service Quality and Equity
A Diagnostic of Water Supply, Sanitation,
Hygiene, and Poverty in Ethiopia
ETHIOPIA
This work was financed by the World Bank Water and Sanitation
Program and the Swedish International Development Cooperation
Agency and was a multi-Global Practice initiative led by Water and
Poverty with significant support from Governance and Health,
Nutrition, and Population.
Maintaining the Momentum
while Addressing Service
Quality and Equity
A Diagnostic of Water Supply, Sanitation, Hygiene, and
Poverty in Ethiopia
© 2018 International Bank for Reconstruction and Development / The World Bank
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Please cite the work as follows: World Bank. 2018. Maintaining the Momentum while Addressing
Service Quality and Equity: A Diagnostic of Water Supply, Sanitation, Hygiene, and Poverty in Ethiopia. WASH
Poverty Diagnostic. World Bank, Washington, DC.
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Contents
Acknowledgments xi
Executive Summary xiii
Abbreviations xxi
Chapter 1 Introduction 1
References 4
Chapter 2 Demographic and Poverty Overview 7
References 15
Chapter 3 Framework for WASH Service Provision in Ethiopia 19
References 24
Chapter 4 Rural WASH Sector Analysis 27
Rural Water Supply Subsector Analysis 27
National Status and Trends 27
Evolution of Funding and Capacity for Delivering Rural Water Supply 27
The Expansion of Rural Water Supply Infrastructure and its Sustainability 29
Access Disparities by Wealth and Consumption 33
Access Disparities by Geography 33
Access Disparities by Service Qualities along the Service Delivery and
Results Chain 40
Implications of Service Quality on the SDG Baseline 46
Implications of a Shift Toward Piped Water Supply on Affordability 47
Rural Sanitation Subsector Analysis 53
National Status and Trends 53
Access Disparities by Geography and Livelihoods 54
Access Disparities by Wealth and Consumption 62
Access Disparities by Geography and Poverty 64
Overlapping Deprivation and Rural Sanitation Access 66
Barriers to Rural Sanitation Access 68
Implication of Achieving the SDG Targets 70
Capacity Constraints across Rural WASH 71
Notes 72
References 73
Chapter 5 Urban WASH Sector Analysis 77
Urban Growth and Institutions 77
Urban Water Subsector Analysis 81
National Status and Trends 81
Evolution of Funding for Urban Water Supply 81
Access Disparities by Wealth and Consumption 85
Separating Service Affordability from Other Barriers to Hooking Up 93
Access Disparities by Service Quality Along Service Delivery and
Results Chain 95
Implications of Service Quality on the SDG Baseline 96
Urban Sanitation Subsector Analysis 99
National Status and Trends 99
Access Disparities by Geography and City Population 102
Maintaining the Momentum while Addressing Service Quality and Equity iii
Access Disparities by Poverty 104
Access Disparities by Tenants Compared to Home Owners 105
Sanitation Solutions across the Service Chain 106
Role for the Private Sector 110
Implication of Achieving the SDGs Targets 114
Notes 115
References 115
Chapter 6 WASH, Nutrition, and Health 117
Notes 122
References 122
Chapter 7 Conclusions and Recommendations 125
Appendix A Poverty Calculations 135
Appendix B Linear Regression Model of Improved Water Supply in
Rural Areas of Ethiopia 137
Appendix C Hydrogeological Index 143
Appendix D Water Quality 147
Appendix E Logit Regression Model for Improved Water on Premises
in Urban Areas of Ethiopia 155
Appendix F Logit Regression Model for Shared Sanitation in Urban
Areas of Ethiopia 159
Appendix G Supply- and Demand-Side Barriers Households Face in
Hooking Up to Utilities 161
Appendix H One WASH National Program: Institutional and
Implementation Arrangements 163
Appendix I Woreda-Level Financing 165
Appendix J WASH and Health: Defining Exposure Risk Factors and
Model for Analysis 169
Appendix K WASH and Health: Distribution of Exposure and Susceptibility 179
Boxes
Box 1.1: Data Used in This Report 2
Box 2.1: Ethiopia’s Absolute Poverty Line 8
Box 2.2: Ethiopia’s Rural Productive Safety Nets Program 15
Box 3.1: De Jure Assignment of Functions in Ethiopia’s Rural Water Subsector 21
Box 3.2: Integrating Public Finance with Development Assistance 22
Box 4.1: Maintenance of Water Points in Lodi Etosa Woreda, Arsi Zone, and
Oromia Region 31
Box 4.2: Lessons from the El Niño Drought 43
Box 4.3: Poor Households Receiving Safety-Net Funding from PSNP Excluded
from Access to Improved Piped Water 49
Box 4.4: Health Extension Workers Support Improvement in Sanitation 54
Box 4.5: Challenge of Sustaining Sanitation Improvements in SNNPR 59
iv Maintaining the Momentum while Addressing Service Quality and Equity
Box 5.1: Case Study of Applying for Connection by Poor People in Harar City 88
Box 5.2: Accountability for Urban Sanitation Service Delivery in Addis Ababa 107
Box 5.3: Example Case of a Household in a Densely Populated and
Inaccesible Area’s Attempt to Empty Latrine Facilities 111
Box 7.1: Rural Water Supply Recommendations 126
Box 7.2: Rural Sanitation Recommendations 128
Box 7.3: Urban Water Supply Recommendations 129
Box 7.4: Urban Sanitation Recommendations 131
Box 7.5: Targeting WASH Investment for Health Benefits 132
Box G.1: Coverage, Access, and Hook-Up Rates: Relationships and Definitions 162
Figures
E S.1:
Figure Shifts in Service Delivery over the Past 20 Years in
Ethiopia, 2017 xiv
ES.2: Key Challenges in Service Quality in Four WASH Subsectors
Figure
in Ethiopia, 2016 xv
ES.3: Inequalities in Service Delivery across the Four WASH Subsectors
Figure
in Ethiopia, 2017 xvi
Figure 1.1: JMP Estimates of Water Supply and Sanitation Coverage in
Ethiopia, 1990–2015 2
Figure 2.1: Livelihood Types by Region in Ethiopia, 2010 7
Figure 2.2: Share of Population by Population Size of Towns and Cities in
Ethiopia, 2007 and 2015 9
Figure 2.3: National Poverty Trends in Ethiopia, 2000–11 10
Figure 2.4: Poverty Headcount by Region in Ethiopia, 1996–2011 10
Figure 2.5: Absolute Numbers of Poor and Nonpoor Households, by Region
and Residence in Ethiopia, 2012 11
Figure 2.6: Mean Consumption, by Urban, Rural, and National Quintiles in
Ethiopia, 2011 12
Figure 2.7: Household Size and Poverty 12
Figure 2.8: Poverty by Livelihood Type in Ethiopia, 2007 13
Figure 2.9: Poverty by Livelihood Type and Region in Ethiopia, 2007 14
Figure 2.10: Poverty Rates by Livelihood Type and Safety Net Coverage in
Ethiopa, 2011 14
Figure B3.2.1: Financial Channels in Ethiopia 22
Figure B3.2.2: Sectoral Financial Flows in Ethiopia 23
Figure 4.1: Rural Drinking Water Trends in Ethiopia, 1990–2015 27
Figure 4.2: Budgets and Expenditure for Main Rural Water Supply Financing
Modalities in Ethiopia, 2006–08 28
Figure 4.3: Regional Variation in Water Point Functionality in Ethiopia, 2012 30
Figure 4.4: People per Water Point by Region in Ethiopia 2012 30
Figure 4.5: Rural Drinking Water Coverage by Wealth Quintile in
Ethiopia, 1995–2011 34
Figure 4.6: Rural Drinking Water Coverage by Consumption Quintile in
Ethiopia, 1995–2011 34
Figure 4.7: Access to Rural Piped Water from Public Stand Posts by
Consumption Quintile in Ethiopia, 2011 35
Figure 4.8: Access to Rural Piped Water from Public Stand Posts by
Wealth Quintile in Ethiopia, 2011 35
Figure 4.9: Access to Improved Sources of Water in Rural Areas by Region in
Ethiopia, 2000–16 37
Figure 4.10: Improved Water Coverage by Dominant Livelihood Type in
Ethiopia, 2007 and 2010 38
Figure 4.11: Improved Water Coverage with Regions, by Livelihood Type 39
Maintaining the Momentum while Addressing Service Quality and Equity v
Figure 4.12: Improved Water Coverage by Woreda’s Dominant Livelihood Type
and whether the Woreda is a Recipient of the PSNP Safety Net 39
Figure 4.13: Service Quality along Results Chain between T60 and B40
Households in Ethiopia, 2016 41
Figure 4.14: Households Able to Fetch Water within 30 Minutes in
Ethiopia, 2000–16 42
Figure 4.15: E. Coli Risk Levels at Point of Collection by Rural Water Supply
Type in Ethiopia, 2016 45
Figure 4.16: Main Source of Household Drinking Water by Type in Ethiopia, 2016 45
Figure 4.17: Estimates of Safely Managed Rural Drinking Water in
Rural Ethiopia, 2016—SDG Methodology 47
Figure 4.18: Average Total Consumption per Person per Year in Ethiopia, 2011 48
Figure 4.19: Trends in Access to Rural Sanitation 49
Figure 4.20: Rural Sanitation Coverage by Region in Ethiopia, 2016 55
Figure 4.21: Rural Sanitation Coverage Trends in Large Regions, Emerging
Regions, and Chartered Cities in Ethiopia, 2000 and 2016 55
Figure 4.22: Rural Sanitation Coverage Trends by Regions in Ethiopia, 2000–16 56
Figure 4.23: Open Defecation Rates in Ethiopia, by Livelihood Type and
Production System, 2007 58
Figure 4.24: Open Defecation Rates by Livelihood Type and Region in
Ethiopia, 2007 59
Figure B4.5.1: Rural Populations in Ethiopia with Unimproved Latrines and
Practicing Open Defecation, by Region, 2016 62
Figure 4.25: Sanitation Coverage by Rural Consumption Quintile in
Ethiopia, 2000–11 63
Figure 4.26: Sanitation Coverage by Rural Wealth Quintile in Ethiopia, 2000–11 63
Figure 4.27: Exposure Variables by Economic Level for Rural Populations
of Children under 5 in Ethiopia, 2011 64
Figure 4.28: Rural Sanitation Coverage–Gender Analysis 64
Figure 4.29: Open Defecation Rates by Woreda Population Density in
Ethiopia, 2007 66
Figure 4.30: Open Defecation Rates by Livelihood Type and Population
Density in Ethiopia, 2007 66
Figure 4.31: Overlapping Deprivation Trends in Rural Areas in Ethiopia, 2001–11 67
Figure 4.32: Access to Sanitation by Education Level of Head of the
Household in Ethiopia, 2011 67
Figure 4.33: Sanitation Coverage Compared to Access to Credit in Rural and
Urban Regions in Ethiopia, 2011 69
Figure 4.34: Sanitation Coverage Compared with Access to Credit in Poverty
Quintiles in Ethiopia, 2011 70
Figure 4.35: Rural Sanitation Coverage in Ethiopia, 2016—SDG Methodology 71
Figure 5.1: Population Growth by Population Size of Towns and Cities in
Ethiopia, 2007–15 78
Figure 5.2: Share of Population by Population Size of Towns and Cities in
Ethiopia, 2007 and 2015 78
Figure 5.3: Urban Drinking Water Trends in Ethiopia, 1990–2015 82
Figure 5.4: Towns Transitioning from Rural to Urban Local Governance,
Ranked by Access to Improved Source of Drinking Water, 2007 83
Figure 5.5: Donor Aid to Urban Water Supply and Sanitation in
Ethiopia, 2006–15 83
Figure 5.6: Urban Drinking Water Coverage by Wealth Quintile in
Ethiopia, 1995–2011 86
Figure 5.7: Urban Drinking Water Coverage by Consumption Quintile
in Ethiopia, 2000–11 86
Figure 5.8: City Size and Poverty in Ethiopia, 2015 87
vi Maintaining the Momentum while Addressing Service Quality and Equity
Figure 5.9: Improved Access by Addis Ababa, City States, and Other
Urban Areas in Ethiopia, 2011 87
Figure 5.10: Proportion of PSUs in Ethiopia with Supply- or Demand-Side
Barrier to Hooking Up Households, 2011 91
Figure 5.11: Coping Strategies in Areas of Small Towns in Ethiopia with
No Piped Water, 2011 91
Figure 5.12: Share of Urban B40 and T60 Households Hooked Up to
Available Urban Water Supply in Ethiopia, 2011 92
Figure 5.13: Total Expenditure per Year by Urban Households on Water, by
Wealth Quintile and Source in Ethiopia, 2011 93
Figure 5.14: Annual Water Bill for Households Consuming 6 m3 of Water per
Month in Ethiopia 94
Figure 5.15: Annual Average per Capita Expenditure, by Water Source in
Urban Areas in Ethiopia, 2011 94
Figure 5.16: Disparities Driven by Relative Wealth along Service Delivery
and Results Chain in Ethiopia, 2016 95
Figure 5.17: Water Quality in Addis Ababa, Secondary Towns, and Small
Towns in Ethiopia, 2016 96
Figure 5.18: Main Source of Household Drinking Water in Urban Areas in
Ethiopia, 2016 96
Figure 5.19: E. Coli Risk Levels at Point of Collection by Urban Water
Supply Type in Ethiopia, 2016 97
Figure 5.20: Estimates of Safely Managed Drinking Water in Urban Areas in
Ethiopia, 2016—SDG Methodology 97
Figure 5.21: Urban Sanitation Coverage in Ethiopia, 2000–16 99
Figure 5.22: Sanitation Service Chain in Ethiopia 100
Figure 5.23: Share of Improved and Unimproved Private and Shared
Latrines in Ethiopia, 2011 100
Figure 5.24: Urban Sanitation Coverage with Shared Latrines in
Ethiopia, 2000–11 101
Figure 5.25: Trends in Access to Urban Sanitation across Regional Groups in
Ethiopia, 2000 and 2016 102
Figure 5.26: Share of Total Urban Population, People with Unimproved
Latrines, and Practicing Open Defecation in Ethiopia, 2016 103
Figure 5.27: Access to Sanitation in Urban Areas by City Population in
Ethiopia, 2007 103
Figure 5.28: Urban Sanitation Coverage by Poverty Quintile in Ethiopia,
2005 and 2016 104
Figure 5.29: Share of Private Latrines by Wealth Quintile in Ethiopia, 2011 104
Figure 5.30: Sanitation Coverage among Urban Households Owning or
Renting Properties in Ethiopia, 2011 105
Figure 5.31: Sanitation Service Chain 106
Figure 5.32: Opportunities for Private Sector Engagement across the
Service Chain in Ethiopia 110
Figure 5.33: Urban Sanitation Coverage in Ethiopia, 2016—SDG Methodology 114
Figure 6.1: Trends in Nutritional Status of Children under Age Five in
Ethiopia, 2000–16 118
Figure 6.2: Exposure, Susceptibility, and Risk Indexes for Children under
Five in Ethiopia, 2011 120
Figure 6.3: Relationship between Community-Level Access to Water
or Sanitation Services and Stunting in Ethiopia, 2011 121
Figure A.1: Access to Water by Wealth Quintile Analysis in Ethiopia,
2000 and 2011 135
Figure A.2: Access to Water by Consumption Quintile Analysis in Ethiopia,
2000 and 2011 136
Maintaining the Momentum while Addressing Service Quality and Equity vii
Figure B.1: Mean Improved Water Coverage Levels by Livelihood Type in
Rural Areas in Ethiopia, 2007 138
Figure B.2: Ordinary List Squared Regression Results for Possible
Determinants of Improved Water in Rural Areas of Ethiopia 139
Figure B.3: Mean Improved Water Coverage Levels in Agropastoralist and
Pastoralist Areas with and without PSNP in Ethiopia, 2007 141
Figure B.4: Mean Improved Water Coverage Levels in Agrarian Cropping
Areas with and without PSNP in Ethiopia, 2007 142
Figure D.1: E. Coli Risk Levels at Collection Point and Household Level
in Ethiopia, 2017 151
Figure E.1: Odds Ratio Results for Improved Water on Premises in
Ethiopia, 2017 156
Figure F.1: Odds Ratio Results for Sharing of Toilet Facilities in Ethiopia 160
Figure H.1: Schematic of the OWNP Institutional and Implementation
Arrangement 164
Figure J.1: WASH Poverty Risk Model Conceptual Framework 169
Figure K.1: Distribution of Susceptibility Factors by Economic Level for
Children under Five in Ethiopia, 2011 181
Figure K.2: WASH-Related DALY Enteric Burden for Children under Five
in Ethiopia, 2011 182
Maps
Map 2.1: Net Sellers and Buyers of Food Crops in Ethiopia, 2010 8
Map 2.2: Productive Safety Nets Program in Woredas and Responsible
Agency in Ethiopia, 2010 13
Map 4.1: Coverage of Improved Water Supply across Woredas in
Ethiopia, 2007 36
Map 4.2: Hydrogeology Index in Ethiopia, 2016 36
Map 4.3: Productive Safety Nets Program in Woredas and Responsible
Agency in Ethiopia, 2010 38
Map 4.4: Open Defecation Rates in Ethiopia, 2007 57
Map 4.5: Improved Sanitation Coverage in Ethiopia, 2007 57
Map 4.6: Poverty Relationship to Open Defecation in Ethiopia, 2007 65
Map 4.7: Poverty Relationship to Improved Latrines in Ethiopia, 2007 65
Map 6.1: Share of Children Stunted in Ethiopia, 2017 119
Map 6.2: Share of Children Underweight in Ethiopia, 2017 119
Map 6.3: Risk Index Values in Ethiopia for Populations of Children
under Five, 2011 121
Map 7.1: Effect of Water Supply and Sanitation Access Improvement on
WASH Risk Reduction in Ethiopia, 2011 132
Map K.1: Exposure Index Values in Ethiopia for Populations of Children
under Five, 2011 179
Map K.2: Susceptibility Index Values in Ethiopia for Populations of
Children under Five, 2011 180
Tables
Table B3.1.1: Responsibilities of WASH sectors institutions 21
Table 4.1: Average Tariff by Scheme Type and Payment Method 48
Table 4.2: Involuntary Turnover by Sector and Professional Level in
Ethiopia, Fiscal Year 2013 72
Table 5.1: Main Urban Water Supply and Sanitation Donors by
Commitments in Ethiopia, 2006–15 84
Table 5.2: Operational Costs and Revenues for AAWSA in Ethiopia, 2011–16 85
viii Maintaining the Momentum while Addressing Service Quality and Equity
Table C.1: Relationship between HI Index and Recommended
Development Approach 143
Table D.1: E. Coli Risk Levels at Point of Collection by Water Supply
Type, Location, and Region in Ethiopia, 2017 150
Table D.2: Availability and Sufficiency of Water, by Technology and
Location, 2016 152
Table D.3: Safely Managed Drinking Water Services in Ethiopia, 2016 153
Table I.1: Average Per Capita Expenditure by Region in Ethiopia and
Change in Access to Improved Water Supply 165
Table I.2: Ethiopian Woredas with Reported Capital Expenditure, 2010–12 166
Table J.1: Exposure Risk Model Parameters 171
Table J.2: Exposure Scenarios and Assigned Relative Risk from
Literature Estimates 172
Table J.3: Definitions of Other Exposure Risk Factors 172
Table J.4: Model Parameters for the Susceptibility Index 173
Table J.5: Summary of Susceptibility Index Calculation 175
Maintaining the Momentum while Addressing Service Quality and Equity ix
Acknowledgments
The WASH Poverty Diagnostic in Ethiopia was led by Dominick de Waal (Senior Economist,
P).
Water GP) and Oliver Jones (Senior Water Supply and Sanitation Specialist, Water G
Over the duration of the task, team members included Wendwosen Feleke (Operations Officer,
Water GP), Eyob Defere (Consultant), Libbet Loughnan (Consultant), Tewodros Tebekew
(Consultant), and Yemarshet Yemane (Consultant).
The team greatly appreciates the constructive inputs of the Ministry of Water, Irrigation and
Electricity, Ministry of Health, and Ministry of Education during the conceptualization and
development of this report. The team also recognizes the collaboration of the Central Statistics
Agency to expand the water module of the Ethiopia Socioeconomic Survey (ESS) and Living
Standards Measurement Study (LSMS) to provide important additional and current WASH-
report.
related data to assist the analysis of
Contributions are also acknowledged from Roger Calow and Florence Pichon (both Overseas
Development Institute [ODI]) and Prof. Seifu Kebede (Addis Ababa University) on governance
and hydrology analysis; and contributions from Oliver Cumming (London School of Hygiene and
Tropical Medicine [LSHTM]) and Richard Rheingan (Appalachian State University), John
Anderson, Karoun Bagamian, and Said Ryan (latter three, University of Florida) on health and
nutrition analysis.
The peer reviewers for this work were: Helene Grandvoinnet (Lead Social Development
Specialist,), Ruth Hill (Senior Economist), Anne Bakilana (Senior Economist – Health) and
Shomikho Raha (Public Sector Specialist).
The team is also grateful for feedback and discussion with Luis Andres (Lead Economist),
Tesfaye Bekalu (Senior Water Supply and Sanitation Specialist), Gulilat Birhane (Senior Water
Supply and Sanitation Specialist), Tom Bundervoet (Senior Economist), Craig Kullmann (Senior
Water Supply and Sanitation Specialist), and Vivek Srivastava (Lead Public Sector Development
Specialist). The team also thanks Jyoti Shukla (Senior Manager) and Wambui Gichuri (Program
support.
Manager) for their
Maintaining the Momentum while Addressing Service Quality and Equity xi
Executive Summary
The WASH Poverty Diagnostic (WPD) in Ethiopia is part of a global initiative to understand the
linkages between service delivery of water supply, sanitation, and hygiene (WASH) and
poverty. The WPD provides a detailed analysis of the history, status, strengths, and
eliminating
weaknesses of WASH service delivery in Ethiopia to inform policy, planning, and programming
for universal access to safely managed water supply and sanitation and attainment of the new
Sustainable Development Goals (SDGs).
Poverty in Ethiopia
Between 2000 and 2011 the proportion of households living below the national poverty line
ercent. Over this same period there was also
fell from just under 45 percent to just under 30 p
Ethiopia.
convergence in the rate of poverty, to around one person in three, across all regions of
Though poverty rates were slightly lower in urban (26 percent) than in rural areas (30 percent),
reas. Ethiopia’s population
the great majority of Ethiopia’s poor households still live in rural a
lives predominantly in rural areas (83 percent) though there are strong signs that urbanization
is accelerating with some estimates forecasting urban growth at 5.4 percent a year (World
Bank 2015c).
In support of its predominantly rural population and its livelihoods, the Government of Ethiopia’s
(GoE’s) poverty reduction efforts have, since 2000, focused on rural and agricultural
development. There has been a very deliberate effort to promote agricultural development,
provide basic rural services equitably, and develop safety nets for households especially in the
eastern half of the country, which has less food security and lower rainfall than other r egions.
These basic services have been delivered at industrial scale through a two-tier decentralization,
first to regional states and subsequently to over 800 districts (woredas). Funding for these
basic services has grown consistently from the early 2000s, supported by both GoE and donor
sources.
Poverty reduction efforts in urban areas have been less focused and deliberate with a sizable
and growing divide emerging among households living in urban areas. Recognizing this growing
urban inequality, and alongside investments in urban infrastructure promoting growth, GoE
began to address poverty in urban areas through large-scale investments in housing in the
mid-2000s. This investment has aimed to replace traditional social housing nationalized in the
Derg era and managed by urban local governments (kebeles) with “condominium housing”
units, which are large blocks of flats being built in the peri-urban areas of particularly larger
cities. Yet Ethiopia’s urban growth is not just in its large cities but includes a very broad base
of even faster growing small towns for which a separate strategy is needed to finance their
infrastructure needs.
WASH Services in Ethiopia
upply. This significant
In 2015 Ethiopia met its Millennium Development Goal (MDG) for water s
achievement was largely driven by the very rapid increase in rural areas where 35 million
people got access to piped and protected water sources between 1994 and 2015. In urban
areas, an additional 10 million people benefited from gaining access to piped water on
savings.
premises, including the benefits of convenience and time
The MDG for sanitation was not met but good progress was made in reducing open defecation
areas. Over 40 million people built basic latrines in rural areas and in urban areas good
in rural
progress was made with 8 million people moving up the sanitation ladder from basic to
Maintaining the Momentum while Addressing Service Quality and Equity xiii
ES.1: Shifts in Service Delivery over the Past 20 Years in Ethiopia, 2017
Figure
Rural water Rural sanitation Urban water Urban sanitation
From surface to From open defecation From public taps to From basic latrines to
improved sources to basic sanitation taps in the compound improved facilities
35 million 40 million 10 million 8 million
people people people people
have gained have built have joined those have gained
access to water from basic latrines and with access to access to
piped systems, no longer more convenient improved
protected hand defecate piped water in their toilet
pumps and springs in the open home or compound facilities
Source: DHS.
acilities. However, gains in urban sanitation coverage have been offset by
improved toilet f
increases in urban population and a lack of improvement on the entire sanitation service
chain.
The progress in improving access to WASH services has been driven by a combination of
decentralization and sector reforms. The backbone for all basic service delivery in Ethiopia is
political, fiscal, and administrative decentralization. Decentralization has provided the basic
financing, staffing, and administrative systems in regions and woredas for service delivery,
including for water supply and s anitation. In tandem, sector reforms to guide the specifics of
water supply and sanitation service delivery have put in place the policies, plans, and basic
technical guidance needed by sector professionals to deliver s ervices. This includes establishing
clear expenditure assignments for rural water supply and sanitation at both regional and
woreda levels and policies establishing progress toward cost recovery in urban areas—albeit
thus far only for operations and some maintenance.
Financing of WASH service delivery has been through a combination of general and special
purpose grants, as well as development assistance. The largest flows to WASH—over 60
percent—have been through the regional and woreda block grants, the food security program,
Fund. Donor finance that is not
the productive safety nets program, and more recently the MDG
specific to WASH service delivery supports many of these general and special purpose grants
especially through the Protection of Basic Services program and the Productive Safety Nets
Program (PSNP). In addition, there has been donor funding specifically for WASH services
through a wide range of projects, and more recently consolidated as programmatic funding
through the One WASH National Program.
Although WASH sector investments from donors have not been the main financing sources,
donor investment has been instrumental in building capacity at regional and woreda l evels.
From the mid-1990s, donors have supported policy and institutional development, underpinning
the formation of the Federal Ministry of Water Resources. Since service delivery was
decentralized, donor projects shaped the formation and capacity building of regional water
bureaus and woreda water desks, town water boards, and utilities. Administrative and technical
capacity building benefitted from a learning-by-doing approach through the rigorous design,
procurement, contract management, and reporting required, especially by African Development
Bank (AfDB) and the World B ank. In turn, support from the United Nations Children’s Fund
(UNICEF) and the World Bank Water Supply and Sanitation Program (WSP) have had a big
influence on approaches and capacity to deliver rural sanitation and behavioral changes,
integrating these into the nationwide, GoE-led Health Extension P rogram.
xiv Maintaining the Momentum while Addressing Service Quality and Equity
Rural water supply and sanitation infrastructure has been delivered at scale and equitably
uality. This means that the putative economic benefits expected as a result of
but is of poor q
investment in WASH services delivery have not been fully r ealized. Albeit from a low base, the
rollout of rural water supply infrastructure has been rapid since 2000 with increases in
coverage being some of the fastest in the world. However, this improved infrastructure used
by an additional 35 million people has not translated into the expected time savings for
fetching water. Even by 2016 less than half this number of people (<17 million) were brought
into the fetching water within 30 minutes c ategory. Between 2000 and 2011 the proportion
of people able to fetch water within 30 minutes fell (from 65 percent to 57 percent) as many
people walked further to improved water sources than previously to unimproved sources.
Only by 2016 did the proportion of people able to fetch water within half an hour return to the
2000 level.
There is little difference in water quality between improved and unimproved sources in rural
reas. E. coli contamination of both protected and unprotected springs and wells was reported
a
at over 90 percent in the 2016 Ethiopia Socioeconomic Survey (ESS). Even in more expensive
interventions contamination rates were extremely high: tube wells (>85 percent) and piped
water systems (>75 percent).1
The functionality of systems remains a challenge, especially as the stock of infrastructure
grows. The National WASH Inventory, last conducted in 2011, reported that 25 percent of
schemes were nonfunctional. Discontinuity of supply and unpredictable breakdowns interrupt
access, jeopardizing the health benefits associated with continuous access. The recent drought
raised concerns about the resilience of systems, with in particular very high rates of hand-dug
wells running dry, and raising the question of whether progress in extending access to basic
services has masked a problem with their underlying vulnerability.
Increases in rural sanitation coverage have resulted in increased convenience and improved
safety and dignity, especially for women, but the poor quality of infrastructure has resulted in
limited health benefits. Very few latrines reliably separate people from fecal matter. Though
survey data lack the ability to reliably define this quality, very few latrines have a washable slab
with effective covers, prerequisites to avoid fecal-oral transmission.
Though the rollout of both rural water supply and sanitation has been equitable across wealth
groups, access to these services has lagged behind in pastoralist and agropastoralist areas.
In Ethiopia, people in rural areas pursue broadly three livelihood types: agrarian, agropastoralist,
and pastoralist. Together pastoralists and agropastoralists are a significant minority group in
ES.2: Key Challenges in Service Quality in Four WASH Subsectors in
Figure
Ethiopia, 2016
Rural water Rural sanitation Urban water Urban sanitation
Over Less than Average
85 percent 10 percent revenue 55 percent
of improved of all latrines per cubic meter of households
rural water constructed in rural sold was just with a latrine
sources were areas qualify as US$0.32 share
contaminated an improved against costs of with two or more
with E. coli latrine US$0.29 households
Source: DHS.
Maintaining the Momentum while Addressing Service Quality and Equity xv
Ethiopia making up around 10 percent of the p opulation. While progress on water supply and
sanitation coverage has been made in the predominantly pastoralist and agropastoralist
regions of Afar and Somali, it lags behind that of other regions. Furthermore, coverage in the
pockets of pastoralist and agropastoralist areas of other large predominantly agrarian regions
(including Oromia and Southern Nations, Nationalities, and People Region [SNNPR]) has also
lagged behind, pointing to systemic problems in the ability of the decentralized service delivery
machinery to reach pastoralists and agropastoralists. The problems are driven by a combination
of complex hydrogeology, remoteness, financing modalities, and the interface between the
bureaucracy and these more mobile forms of livelihood.
In contrast to rural WASH services, urban WASH services have delivered real benefits but not
ustainably. With over 10 million people joining those who are able to access water
equitably or s
from a piped source on premises, significant time savings have been realized in urban a reas.
However, these time savings have been disproportionally captured by wealthier households
(top 60 percent [T60] of the wealth index), which are nearly four times more likely to have
access to piped water on premises than poorer households (those in the bottom 40 percent
[B40] of the wealth i wofold. For around one-
ndex). The reasons for this inequitable uptake is t
third of unconnected households, mainly in smaller towns, there is a basic lack of infrastructure
to hook up to. For the other two-thirds of unconnected households, mainly in large urban
centers, there is infrastructure to hook up to but there are barriers in the form of connection
charges and utility inertia.
In the case of urban sanitation, while driven by individual investment rather than through
capture of a public service, households in the wealthiest quintile are six times more likely to
uintile. Over half of urban households
have improved their latrines than those in the poorest q
share latrines with two or more other households, and this proportion is significantly higher
among households that rent (77 percent) rather than own (29 percent) their h ouses. The
expanding private rental market requires increased dialogue with the private sector and greater
standards.
regulation to maintain
Though delivering real benefits WASH services are far from sustainable. In the case of water
supply, cost recovery is barely covering operational costs, is only partially covering maintenance
costs, and is not covering the replacement of i nfrastructure. Much routine maintenance is
being deferred because costs are only marginally below revenues. Moreover, the new sources
of water that will need to be developed to meet rapidly increasing urban demands will incur
higher marginal costs as existing urban and peri-urban sources are depleted. In the case of
urban sanitation services, though both the numbers and the proportion of improved latrines
ES.3: Inequalities in Service Delivery across the Four WASH Subsectors in
Figure
Ethiopia, 2017
Rural water Rural sanitation Urban water Urban sanitation
Access to improved Latrine coverage in Wealthier Households in the
water sources in
Emerging households are nearly wealthiest
pastoralist four times
regions more likely to have quintile are six times
areas is access to piped more likely to have
twothirds is half that of water on premises an improved latrine
of that in coverage in the than poorer than those in the
agrarian areas Large regions households poorest quintile
Source: DHS.
xvi Maintaining the Momentum while Addressing Service Quality and Equity
have risen over the past 20 years, fecal sludge management chains are nascent at b est. In
many towns these chains are nonexistent, resulting in fecal sludge being dumped untreated
environment.
into the
The potential health benefits of providing access to water supply and sanitation services are
not being fully realized due to communities not reaching high enough coverage levels to break
the transmission of disease. This is further compounded by poor quality of services—
unimproved latrines and poor water quality—upon which most households rely. The health
burden of inadequate access to WASH services is disproportionately borne by poorer children
and those in vulnerable geographic a reas. Children in poor households are up to 2 .7 times
nderweight. Overlapping
more likely to be underweight and five times more likely to be severely u
vulnerabilities substantially modify the impact of WASH investments. Children in poor
households have higher exposure and susceptibility than children in rich households, with the
B40 having approximately 50 percent of the cumulative share of the susceptibility and r isk.
Conclusions and Recommendations
The GoE has been successful at linking the decentralized generic service delivery machinery
it has put in place with the sector policy direction, plans, and capacity to rollout basic
WASH services at an industrial scale. This has been done with strong country leadership
that directs both domestic public and overseas aid resources well with basic, public access
WASH services (nonrivalrous, nonexclusive goods). However, when WASH services have
added value and a private dimension (rivalrous and exclusive goods), progress on
implementing the policy direction, particularly on cost recovery, has been limited and the
sector outcomes regressive, with wealthier households disproportionately capturing the
expenditure.
benefits of public
The rollout of basic WASH services has been equitable across wealth groups though albeit less
equitable across livelihood types. Basic water supply services in rural areas include public
boreholes). In the case of sanitation and hygiene
water points (protected wells, springs, and
this has been through knowledge disseminated from health extension workers across the
country.
The challenge for basic WASH services will be to improve quality and functionality while
achieving universality. Without making these shifts, the contribution of WASH services to
improving key health indicators, such a reducing diarrhea and stunting, will not be realized. In
the case of rural water supply there are two p riorities. First, to ensure that rural water services
deliver their potential health benefits, water quality needs to be improved. Second, rural water
supply needs to deliver on the economic promise of freeing people’s time by bringing services
closer to peoples’ homes, and do so reliably by addressing mechanical functionality. This, in
turn, will increase demand for water quantity, which requires more systematic approaches to
water resource assessment and monitoring both to respond to the increase in demand and to
reduce vulnerability to extreme climate events.
For sanitation, the main aim is to improve the quality of latrines to ensure they separate people
from fecal m aterial. Moving the millions of rural households using unimproved latrines up the
sanitation ladder is going to require a combination of demand- and supply-side a pproaches.
Health extension workers will need additional skills and updated communication tools to more
effectively combine demand creation with supply-side interventions. This would include market
development for businesses selling sanitation products as well as nonhardware subsidies for
bringing supply and demand together.2
This study shows that the availability of microfinance in Ethiopia is positively correlated with
coverage. Expanding financing options for producers and consumers of
improved sanitation
sanitation products should be promoted, and targeted subsidies, possibility through PSNP ,
should be explored to ensure that the very poorest households are not left b ehind.
Maintaining the Momentum while Addressing Service Quality and Equity xvii
Remaining inequalities in basic services are principally in pastoralist and agropastoralist
areas. GoE is well aware of this service gap and in 2009 set up the Ministry of Federal Affairs
principally to close the service and capacity gaps between large and low-income regions.
Addressing this gap requires building greater technical expertise in areas with difficult
hydrogeology and finding ways for the decentralized service delivery machinery to interface with
pastoralist and agropastoralist communities. As part of the rollout of the Millennium
Development Goal (MDG) special purpose grant, the regions of Afar and Somali drew on
gencies. While this may be part of the solution, the
capacity in larger regions to set up drilling a
same larger regions are having difficulty delivering services to pastoralists and agropastoralists
regions. This suggests that both the existing technologies and the service delivery
in their own
interface in pastoralist and agropastoralist areas needs revisiting for both water supply and
sanitation services.
There has also been progress in the rollout of WASH services with added value and a private
dimension. These value added services—though often not yet safely managed—are piped
water on premises and sustainably managed sanitation. To date, the rollout and uptake of
these services have mainly been in urban areas and have been regressive, with wealthier
households disproportionately capturing piped water on premises and finding it easier to invest
facilities. Yet even these value added WASH services
in building or upgrading their own toilet
have flaws in both quality and sustainability.
The challenge for value added WASH services will be addressing equity while improving quality
and sustainability. For piped water supply the greatest barrier to equity needs to be tackled at
the level of service providers. With two-thirds of unconnected urban dwellers in areas where
they could hook up to utilities, there needs to be much stronger incentives for utilities to
connect them.
The qualitative work for this report brings to light both that connection charges are a barrier
and that the interface between service providers and customers makes requesting connections
an unnecessarily long and complicated process. There is also room to gradually increase
tariffs and improve the efficiency with which bill payments are collected to overcome a second
problem raised by utilities: collecting revenues from poorer households connected to utilities
cost more than the amount c ollected. This would also start to address the broader underlying
need to work toward full cost recovery.
Investment is needed in water treatment and water quality monitoring. This is especially the
case for towns that have transitioned from being classified as rural to being classified as urban
local governments ( ULGs). As towns make this transition, they lose access to woreda block
grants but have yet to increase their own source revenue capacity for investment. A transitional
infrastructure financing arrangement is needed to plug this g ap. The MDG special purpose
grant for capital investment that was introduced in 2011 may be part of the solution, but it is
too early to tell. The MDG grant’s highly discretionary nature, being both multisector and for
rural or urban, does not favor targeting this transitional d emographic. In parallel, improving the
performance and reach of the Water Resources Development Fund, a public sector lending
facility for utilities set up in 2002, could also help small towns with their water supply investment
needs.
Value added sanitation solutions, particularly in urban areas, require a citywide approach
to tackle the full service chain, and to ensure fecal sludge is safely captured, transported,
and treated. This needs increased public investment in the management and treatment of
fecal sludge, and, where appropriate, investment in sewers to enable transportation.
However, the current low sewerage access levels, high cost, and challenge of retrofitting
sewers in fast expanding, unplanned cities mean most transportation will be through
vacuum trucks (which is one opportunity to engage the private sector). A second opportunity
to involve the private sector at scale is through the private urban housing sector, which can
bring innovation and efficiency to fecal sludge management, e.g., management of
decentralized treatment plants.
xviii Maintaining the Momentum while Addressing Service Quality and Equity
To improve sanitation services for the poorest households, better access to fecal sludge
transportation services is needed in unplanned urban areas. While the private sector can play
a role in driving down the cost of latrines and developing innovative solutions for challenging
areas, government subsidies might also be considered. Subsidies could be focused at lowering
borrowing costs for improving household sanitation infrastructure, facilitating connection to
sewers, and encouraging the use of fecal sludge transportation s ervices. These subsidies
could be channeled through the new urban safety net initiative.
Incentives for landlords, including for kebele-managed housing,3 is needed to facilitate
investment to reduce sharing rates and to improve the quality of latrines. This could be
egulations. The qualitative work for this report
facilitated for new housing through building r
highlights the need for greater responsiveness by kebele administrations to encourage rather
than discourage home improvements that tenants are prepared to m ake.
Geographic targeting of WASH investments to areas with higher concentrations of children who
face poor nutrition status and health access offers a simple compass for reaching the most
vulnerable. The regional distributions of exposure, susceptibility, and risk index values in the
B40 population indicate that every region has highly vulnerable c hildren. This emphasizes the
importance of combining geographic and poverty targeting of WASH and health investments.
The implementation of pro-poor targeting in the WASH sector would be further enhanced
through coordination with social protection programs that focus on households with young
children who are vulnerable.
On top of the challenges of delivering services under the MDG framework, GoE and its
development partners now need to consider the additional rigor required in delivering on the
SDGs. Improving and expanding both basic and safely managed WASH services call for
continuing GoE’s twin track development of both its core country systems for decentralized
service delivery and its sector institutions that together have driven progress at scale over the
past decade and more.
The transition to the SDGs needs to be done with two supporting factors in mind: (a) a massive
upgrading of skills in the public and private sector to provide the right mix of skills and services
needed to tackle the SDG, and (b) a full integration of WASH service delivery into the broader
water governance agenda to ensure that water services are able to compete with other fast
growing demands for water.
With the estimated SDG financing gap running into billions of dollars a year, much more than
needed. The reward for making this transition
incremental improvements to past progress are
from MDGs to SDGs is the real prospect of delivering on the health and economic gains that
have been elusive under the MDG framework.
Notes
1. Previous smaller water quality surveys reported lower levels of contamination but lacked
the scale and representativeness of the 2016 Ethiopia Socioeconomic Survey Water
module.
Quality Test
2. Subsidies that facilitate market functioning,
e.g., training sanitation entrepreneurs, include
lowering interest rates for borrowing for sanitation-related improvements rather than
subsidies for sanitation hardware slabs).
(e.g.,
3. A kebele, similar to a ward, is the smallest administrative unit in Ethiopia; it translates to
“neighborhood.”
Reference
World Bank 2015c. Ethiopia Urbanization Review: Urban Institutions for a Middle-Income
Ethiopia. Washington, DC: World Bank.
Maintaining the Momentum while Addressing Service Quality and Equity xix
Abbreviations
AAWSA Addis Ababa Water and Sewerage Authority
AfDB African Development Bank
B20 bottom 20 percent of the wealth index
B40 bottom 40 percent of the wealth index
BGS British Geological Survey
BoFED Bureau of Finance and Economic Development (regional)
CDF Community Development Foundation
CLTHS community-led total sanitation and hygiene
CSA Central Statistical Agency
CWA consolidated WASH Account
DALY disability-adjusted life year
DHS Demographic Health Survey
DP development program
EED environmental enteric dysfunction
ESRDF Ethiopia Social Rehabilitation and Development Fund
ESS Ethiopia Socioeconomic Survey
ESS-WQT Ethiopia Socioeconomic Survey-Water Quality Testing Component
EWSSP Ethiopian Water Supply and Sanitation Project
GBD global burden of disease
GoE Government of Ethiopia
GPG General Purpose Grant
GPW Gridded Population of the World
GTP Growth and Transformation Plan
HEP health extension program
HEW health extension worker
HI Hydrological Index
Maintaining the Momentum while Addressing Service Quality and Equity xxi
HICES Household Income Consumption and Expenditure Survey
IBEX Integrated Budget and Expenditure Management System
IHDP Integrated Housing Development Program
ISA Integrated Surveys on Agriculture
IUSHS Integrated Urban Sanitation and Hygiene Strategy
JMP Joint Monitoring Programme for Water Supply and Sanitation (WHO/UNICEF)
LIU Livelihoods Integration Unit
LSHTM London School of Hygiene and Tropical Medicine
LSMS Living Standards Measurement Study
MDG Millennium Development Goal
MoE Ministry of Education
MoFEC Ministry of Finance and Economic Cooperation
MoFED Ministry of Finance and Economic Development
MoH Ministry of Health
MoU memorandum of understanding
MoWIE Ministry of Water, Irrigation and Electricity
MoWUDC Ministry of Works, Urban Development and Housing Construction
NHSS National Hygiene and Sanitation Strategy
NGO nongovernmental organization
NRW nonrevenue water
NSDS National Strategy for the Development of Statistics
NWCO National WASH Coordination Office
NWI National WASH Inventory
NWSC National WASH Steering Committee
NWTT National WASH Technical Team
ODI Overseas Development Institute
ORT oral rehydration treatment
OLS ordinary least squares
OWNP ONE WASH National Program
xxii Maintaining the Momentum while Addressing Service Quality and Equity
PASDEP A Plan for Accelerated and Sustained Development to End Poverty
PMU project management unit
PSNP Productive Safety Nets Program
PSU primary sampling units
RADWQ Rapid Assessment of Drinking-Water Quality
RCT randomized controlled trials
RR relative risk
RWCO Regional WASH Coordination Office
SD standard deviation
SDG Sustainable Development Goal
SDPRP Sustainable Development and Poverty Reduction
SNNPR Southern Nations, Nationalities and People Region
SPG specific purpose grant
T20 top 20 percent of the wealth index
T60 top 60 percent of the wealth index
ToFED Town Administration Office of Finance and Economic Development
TVET Technical and Vocational Education and Training Agency
UAP Universal Access Plan
ULG urban local government
UNICEF United Nations Children’s Fund
VIP ventilated improved pit (latrine)
WASH water supply, sanitation, and hygiene
WASHCO water supply, sanitation, and hygiene committee
WASH PRM WASH Poverty Risk Model
WDI World Development Indicators
WFA weight-for-age
WIF WASH Implementation Framework
WMS Welfare Monitoring Survey
WoFED Woreda Office of Finance and Economic Development
Maintaining the Momentum while Addressing Service Quality and Equity xxiii
WPD WASH Poverty Diagnostic
WQT water quality testing
WRDF Water Resource Development Fund
WSG woreda support groups
WSP Water Supply and Sanitation Program
WWTP wastewater treatment plant
WQ wealth quintile
YLL years of life lost
ZoFED Zonal Administration Office of Finance and Economic Development
xxiv Maintaining the Momentum while Addressing Service Quality and Equity
© Chris Terry/World Bank
Chapter 1
Introduction
The WASH Poverty Diagnostic (WPD) in Ethiopia is part of a global initiative with the objective
of improving the evidence on the linkages between water supply, sanitation, and hygiene
(WASH) and poverty, as well as identifying opportunities and bottlenecks in the sector. Following
the structure of all WPDs, this diagnostic uses existing and newly collected data to answer four
core questions:
•• Who and where are the poor populations and bottom 40 percent (B40) of the national
distribution (consumption)?
•• What is the level of access and quality of WASH services experienced by poor households
and the B40 as compared to the nonpoor and to the top 60 percent (T60)?
•• What are the linkages and synergies between WASH and other sectors?
•• What are the WASH service delivery constraints and potential solutions to improving
services to the poor households and B40?
By answering these core questions, the WPD aims to provide a comprehensive analysis of the
current state of access to water supply and sanitation services, including understanding the
drivers behind the significant progress in coverage in Ethiopia over the last 20 years. Ethiopia
achieved the drinking water Millennium Development Goals (MDG) target of 57 percent,
successfully halving the number of households without access to improved drinking water
since 1990. In doing so over 52 million people in Ethiopia now have access to an improved
drinking water source (within 1.5 kilometers) as compared to only 6 million people in 1990
(see figure 1.1).
This achievement is primarily the consequence of significant improvements in access to
drinking water supplies in rural areas. The Sustainable Development Goals (SDGs) aim for
universal access to safe water supply and sanitation, raise the bar for the WASH sector.
Water quality has been added to the definition of the SDGs water indicator for safely managed
water coverage. Ethiopia has a significant challenge to increase the quality of coverage to
address this.
While Ethiopia did not achieve the MDG for sanitation, the practice of open defecation was
decreased by 63 percent, which was the largest decrease in the proportion of the population
practicing open defecation of any country globally. As a result, 67 million people gained access
to a latrine over the MDG period at an average of 2.6 million people per year. This progress was
achieved through the integration of sanitation and hygiene promotion into the wider health
deliver mechanism, and a strong focus on behavior change. However, despite this progress just
10 percent of all latrines constructed in rural areas qualify as an improved latrine.
Urbanization has increased the pressure on existing services, specifically sanitation, and
historic funding levels have struggled to keep up with demand. Just as water needs to be safely
managed under SDG goals, the SDG definition for sanitation targets requires sanitation to be
safely managed. Ethiopia currently has limited infrastructure and service delivery systems to
ensure fecal waste can be safely managed across the service chain. The combination of
increased demand and expectation of higher standards in urban areas require new approaches
to be adapted, as well as significant increases in financing and greater institutional capacity to
Maintaining the Momentum while Addressing Service Quality and Equity 1
address these more complex challenges. The WPD examines the challenges that need to be
addressed around three main areas:
•• Increasing the quality of services, both for greater impact and to meet the higher bar set
by the SDGs
•• Effective targeting and delivery mechanisms to reach and provide sustainable services
to underserved sections of the population, specifically pastoralist communities
•• Solutions to the growing urban water supply and sanitation service delivery gap, both in
large urban centers and smaller emerging towns.
Figure 1.1: JMP Estimates of Water Supply and Sanitation Coverage in Ethiopia,
1990–2015
a. Water supply b. Sanitation
100 100
13
29
80 80
48 30
60 60
Coverage (%)
Coverage (%) 92 29
40 40
39 45
14
20 20 28
1
12 12 4
1 3
0 0
1990 2015 1990 2015
Surface water Open defecation
Other unimproved source Other unimproved latrine
Other improved source Shared latrine
Piped water supply Improved latrine
Source: UNICEF/WHO 2015.
Note: JMP = Joint Monitoring Programme.
Box 1.1: Data Used in This Report
This report draws on a wide range of household surveys; administrative data from the water,
urban, and agriculture sectors; financial BOOST data for Ethiopia; and Ethiopia’s national
integrated budget and expenditure management system (IBEX).
box continues next page
2 Maintaining the Momentum while Addressing Service Quality and Equity
Box 1.1: Continued
National representative household surveys. The main nationally representative surveys used
are the Demographic Health Survey (DHS), the Welfare Monitoring Survey (WMS) and the
Housing and Population Census. The Mini-DHS 2014 was not used. Though nationally
representative and representative at regional level, the sample frame was not suitable for
urban versus rural analysis at the regional level particularly in smaller regions.
Each of these types of survey has its strengths and weaknesses. The DHS series (2000,
2005, 2011, 2014, 2016) has water supply and sanitation definitions, which are best aligned
to MDG and SDG monitoring. The WMS series (2000, 2010/11) are linked to the Household
Incomes, Consumption, and Expenditure surveys, which enable econometric analysis. The
2007 Housing and Population Census, which has a long form of the questionnaire administered
to one in five households across the country, yields by far the highest resolution and enables
analysis at the woreda level (district units of around 100,000 population). Though dated, the
sector outcomes in the 2007 Census are in line with the trajectories of later surveys meaning
that the analysis of differences in coverage among categories is insightful.
The WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation (JMP) reports
on global, regional, and country progress on access to WASH. The JMP data served as the
basis for monitoring the MDGs and building indicators for WASH within the Sustainable
Development Goals (SDGs). The JMP relies on a number of government data points and
applies some assumptions to reach their coverage figures. Apart from instances in which the
report directly references JMP data, the analysis in this report has used the original government
survey data and not applied any assumptions. It was felt, specifically in relation to sanitation
coverage, that the original government survey data provides a more accurate picture than data
generated using the JMP assumptions.
Atlas of Ethiopian Livelihoods. In 2010 the Livelihoods Integration Unit at the Ministry of
Agriculture and Rural Development released a national database and atlas of livelihoods for
Ethiopia. The data are based both on household surveys and broader field work on rural
livelihoods. Building on work done by the Ethiopia Poverty Assessment (World Bank 2015a),
the livelihoods database underpinning the atlas was fully integrated with the 2007 Census
data, and the 2010/11 poverty data from HICES, as well as with hydrogeological data from
the University of Addis Ababa.
National WASH Inventory. In 2010/11 the Ministry of Water, Irrigation and Electricity (MoWIE)
compiled a national inventory of improved water points (piped and protected sources). Though
this data have not been made public in full, summary data have been used to analyze aspects
of service delivery such as water point functionality not possible to estimate from national
surveys.
Learning journeys. In addition to examining the quantitative data, the team has identified and
followed the personal journeys of people in different parts of Ethiopia who faced basic
problems in accessing WASH or in fixing systems that have broken down. These personal
learning journeys are used to illustrate specific issues including: affordability, age, gender, and
governance.
Maintaining the Momentum while Addressing Service Quality and Equity 3
References
UNICEF and WHO (World Health Organization). 2015. Progress on Sanitation and Drinking
Water: 2015 Update and MDG Assessment. New York: UNICEF.
World Bank. 2015a. Ethiopia Poverty Assessment 2014. Washington, DC: World Bank.
4 Maintaining the Momentum while Addressing Service Quality and Equity
Bosena Abeetew, widow and mother of 7, Aboakokit Kebele, Fogera Woreda, Amhara Region
© Chris Terry/World Bank
Chapter 2
Demographic and
Poverty Overview
In 2015 Ethiopia’s population approached 100 million people. Over 80 million people live in
rural areas. Rural livelihoods are shaped by Ethiopia’s extremely diverse geography. Rainfall,
altitude, topology, soils, culture, and population density interact to form a complex mosaic of
livelihood zones. Understanding and responding to the needs of different livelihood types have
been key to reducing poverty and promoting growth in rural areas.
Three broad livelihood types that emerge from this mosaic are: pastoralist, agropastoralist,
and agrarian cropping. Pastoralist and agropastoralist livelihoods are dominant in the
sparsely populated eastern and southern dry lowland areas; agrarian copping is dominant in
the mid- to higher altitude areas, which also have higher population densities. Within agrarian
cropping areas the lower rainfall eastern half of the country is less food secure than the west
of the country leading to a consistent pattern of net buyers and net sellers of food crops
(map 2.1).
Figure 2.1: Livelihood Types by Region in Ethiopia, 2010
National
Tigray
Amhara
Benishangul
SNNPR
Oromia
Gambella
Somali
Afar
0 20 40 60 80 100
Percent
Cropping Agropastoral Pastoral
Source: GoE 2010.
Note: SNNPR = Southern Nations, Nationalities, and People Region.
Maintaining the Momentum while Addressing Service Quality and Equity 7
Map 2.1: Net Sellers and Buyers of Food Crops in Ethiopia, 2010
Legend
Northeastern and central
Net sellers highland croppers
Net buyers 48%
No data
Net buyers Net sellers
52%
Agropastoralists
Pastoralists
Source: GoE 2010.
Box 2.1: Ethiopia’s Absolute Poverty Line
In Ethiopia, absolute poverty is measured by comparing a household’s consumption per adult
equivalent to the national poverty line, defined as Br 3,781 per year in 2011. The poverty line
indicates the minimum money required to afford the food covering the minimum required
caloric intake (estimated at Br 1,985) and additional essential nonfood items (Br 1,796),
totaling Br 3,781. This was based on the 2010/11 Household Income Consumption and
Expenditure Survey (HICES).
Following years of ad hoc food aid to many eastern areas of the country, including some
pastoral and agropastoral areas, the Government of Ethiopia (GoE) and its development
partners launched the Productive Safety Nets Program (PSNP) in 2005, which covers around
300 woredas (box 2.1). PSNP has become a structural feature of both defining and alleviating
rural poverty.
Of the people living in urban areas, just under one-third live in Addis Ababa, just under one-third
in 16 secondary cities with over 100,000 people, and, the remainder in over 200 small towns
8 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 2.2: Share of Population by Population Size of Towns and Cities in Ethiopia,
2007 and 2015
2015
2007
Addis Ababa 50,000–100,000
100,000–350,000 < 50,000
Source: National Survey 2007.
spread throughout the country. The share of the urban population outside of Addis Ababa is
growing, as urbanization in secondary cities and small towns outpaces that in the capital
(figure 2.2).
While Ethiopia has been slow to urbanize compared to other countries in Africa, urbanization is
accelerating, with recent estimates putting urban growth at above 5 percent. The “Ethiopia
Urbanization Review” (Ozlu et al. 2015) points to the need to proactively manage urbanization
if it is to provide jobs, infrastructure, services, and housing that will drive poverty reduction and
growth in future. With much of this growth happing outside of Addis Ababa in both secondary
cities and hundreds of small towns, strategic decisions on systems to support this distributed
urban development today will have far reaching implications for Ethiopia’s cities of tomorrow
(Ozlu et al. 2015).
Between 2000 and 2011 the proportion of households living below the national poverty line
fell from just under 45 percent to just under 30 percent (figure 2.3). Over this same period
there was also convergence in the rate of poverty, to around one person in three, across all
regions of Ethiopia (figure 2.4).
Though poverty headcount rates were not dissimilar in urban (26 percent) and rural areas
(30 percent), 85 percent of Ethiopia’s poor households live in rural areas (figure 2.5). With
Ethiopia’s regional states being of uneven size over half of poor people in 2011 lived in rural
Oromia and Amhara.
In addition to being predominantly rural households, the household heads of poor households
are older, less educated, and more often married than nonpoor household heads, and they
have a greater number of dependents than wealthier households. Households in the bottom
10 percent of the consumption distribution have even lower levels of education, are in
households of larger size, have more dependents, and are headed by more elderly heads than
other poor households.
Maintaining the Momentum while Addressing Service Quality and Equity 9
Figure 2.3: National Poverty Trends in Ethiopia, 2000–11
50
45
40
35
30
Percent 25
20
15
10
5
0
2000 2005 2011
Poverty rate (headcount index)
Death of poverty (poverty gap index)
Poverty severity (squared poverty gap index)
Source: World Bank 2015a.
Figure 2.4: Poverty Headcount by Region in Ethiopia, 1996–2011
70
60
50
Poverty headcount (%)
40
30
20
10
0
1996 2000 2005 2011
Tigray Afar Amhara Oromia
Somali Benishangul SNNPR Gambela
Source: World Bank 2015a.
Note: SNNPR = Southern Nations, Nationalities, and People Region.
10 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 2.5: Absolute Numbers of Poor and Nonpoor Households, by Region and Residence in Ethiopia, 2012
a. Urban poor households by region b. Rural poor households by region
Harari
Dire Dawa
Gambela
B.G.
Afar
Tigray
Somali
SNNPR
Amhara
Oromia
Addis
25 20 15 10 5 0 0 5 10 15 20 25
Number of urban poor by region (millions) Number of rural poor by region (millions)
Poor Nonpoor
Sources: World Bank calculations based on GoE 2012 and 2007 Census data.
Note: B.G. = Benishangul-Gumuz; SNNPR = Southern Nations, Nationalities, and People Region.
Across urban areas, poverty rates in small urban centers—rural towns—are higher than larger
urban centers (see figure 2.6). The exception to this is Addis Ababa, which has a higher poverty
headcount ratio and greater inequality than most other cities, independent of size.
Households with elderly members, widows, and with elderly or female heads are much more
likely to be poor if they are in urban areas compared to rural areas (see figure 2.7). In urban areas
households with an elderly member or an elderly head are 12 and 13 percentage points more
likely to be poor than other households. This contrasts with elderly household members or elderly
heads in rural areas, who are less likely to be poor than other rural households. A similar pattern
is observed for female-headed households who are less likely to be poor in rural areas and more
likely to be poor in urban areas. A number of factors influence these different characteristics of
the poor households across rural and urban areas including (a) that urban households are
smaller on average; (b) that there are more single adult urban households; and (c) that there are
a higher proportion of female-headed households in urban than rural areas.
Another contributing factor to the difference in poverty across rural and urban households is
that, whereas the PSNP provides support to the poor and vulnerable households in rural areas,
there is no equivalent in urban areas. Urban households do benefit more than rural households
from indirect subsidies in fuel and food, but this benefit is not large enough to compensate for
the lack of direct transfers among the bottom percentiles (Ozlu et al. 2015.).
In rural areas, poverty rates are higher among households with pastoralist and agropastoralist
livelihoods than among those areas where agrarian cropping is dominant. This is particularly
the case in the regional states of SNNPR and Oromia where pastoralists and agropastoralist
are minorities among households pursuing agrarian livelihoods.
Maintaining the Momentum while Addressing Service Quality and Equity 11
Figure 2.6: Mean Consumption, by Urban, Rural, and National Quintiles in
Ethiopia, 2011
20,000
18,000
Mean per capita consumption
16,000
(Annual Br, nominal)
14,000
12,000
10,000
8,000
6,000
4,000
2,000
0
a. Urban b. Rural c. National
Poorest 3,125 1,796 1,891
Poorer 4,883 2,806 2,970
Middle 6,516 3,588 3,857
Richer 8,934 4,545 5,062
Richest 18,493 7,374 9,837
Source: HICES 2011.
Figure 2.7: Household Size and Poverty
a. Household size by urban and rural and b. Difference in the headcount
above and below the Poverty Line, 2011 poverty rate in urban and rural
8 20
15
6
Headcount
Headcount
10
4 5
0
2
–5
0 –10
Rural Urban Elderly head Female head
Poor Nonpoor Rural Urban
Source: HICES 2011.
12 Maintaining the Momentum while Addressing Service Quality and Equity
Map 2.2: Productive Safety Nets Program in Woredas and Responsible Agency in
Ethiopia, 2010
Erob
Mereb Lekhe
Tahtay Adiabo Gulomekeda
Laelay Adiabo Ahferom
NW. Tigray Laelay Maichew Dalol
Tahtay Maichew
Adwa Saesi Ts ae d’aemba
Tahtay Koraro
Tigray Medebay Zana
Asgede Tsembila
Werie Lekhe Hawzien
E. Tigray
W. Tigray Naeder Adet Atsebi Wenberta
Koneba Berahle
Kilte Awlaelo
Kola Temben
Tselemti Degua Temben
Zone2
C. Tigray
Adiarkay Tselemt Tanqua Abergele Enderta Afdiera
Abala
Saharti Samre
Debark Beyed Erebti
Abergele Hintalo Wajirat
Dabat Janamora Elidar
W. Hamra Alaje
Megale
Sahila S. Tigray
Wogera Egdamohoni
Ziquola
N. Gonder Sokota Raya Azebo Teru
Misrak Belesa Ofla Yalo Dufti
Mirab Belesa Dehana
gazgibla Alamata
Afar Zone4 Elidar
Ebinat Bugna N. Wello Gulina
Mirab Belesa Awra
Kobo
Lasta
Gidan Zone1
Lay Gayiot Ewa
Meket Gubalafto Dufti
S. Gonder
Simada Delanta Wadla Habru Chefra
Amhara Bahir Dar Tach Gayint
Dawunt Ambassel
Asayta
Worebabo
Simada Tenta Tehuledere Mille
Kuta ber Adaare
Mek dela
Bati Afambo
S. Wello Argeta
W. Gojam Sayint Ajibar Telalak
Metekel Gonca Siso Enessie Mahal sayint
Dessie Zuriya
Agew Awi Argoba
E/Sar Mider Legambo
Albugo Oromiya Dewe
Debra Sina Woreilu Dewa Chefa Dewa Harawa
Ben Gunniz Wogdi
Legehida
Ketta/Kelala Githe Rabel Artuma/dalifagie
E. Gojam Aruma Fursi Zone5 Gewane
Jama
Asosa Shinile
Legend
Shebel Berierifa Menz Gera Mider Fursi Bure mudayetu
Gile Timuga Afdem Erer Shinelle
Menz Keya Gebriel
Menz Mama Mider
Menz Lalo Mider
Zone3
Regions
Semurobi gelallo
N. Shewa (R4) N. Shewa (R3)
Kamashi Kuyu
Zones
Horo Gudru Abiohu Gnea Dulecha
Wuchale Amibara Dire Dawa Jars
Argoba spacial
Tongo SW W. Wellega Argolela Tera
Gro gutu Meta Kersa
Rombolcha
Kimbibit Assagert
E. Wellega
PSNP woredas
Haramaya Gurs
G um
Dobba
Meiso Tullo
Deder HUNDENIE Jijiga
Kurfachele Harshin
West Shewa Awash fentale Babile
AA Zone4 Chiro Bedeno
Fedis
Mesela Girawa
AA Zone3 Fantalle Guba Qoricha Gemachis Melka Belo
Kelem AA Zone6
Anchare Habroo E. Harerge Midhega
Babile
Boosat Kuni
S.W. Shewa W. Haraerge
E. Shewa Merti Aseko
Gole Oda
Illubabor Boke
D\Habour
Dedota Dodota Golecha(ARSI)
Zone 1 Dodota Darelebu
Meyu Mukke Degehabur
Zone 3 Gurage Meskan
Arsi
Mareko
Selti Z Dugda
Jimma Lega Hida
Yem SW Hadiya
Gambella Gibe Misna
A/T/J/Kombolcha
DalochaLanfaro Seru Fik
Unlmmu Seru
Gpmboro Selti
Zone 2
Sheka Oromiya Lemmu
Soro Shahego
Alaba
Arsi Negelle
Gololcha(Bale)
Shala Sewane
Godere Duna Demboya Alaba
Warder
Kacha Bira KT
Tembaro Kore
Kefa Gena Bosa Shaahemene
Siraro Ginir
B oloso- Bombe Boloso Awasa zuna
Duguaria fan West Arsi Goro
Dawro Kingoo Koysha
Sodo zuria
Boricha Shebedino
Rayitu
Somali
Loma Offa Dale Sidama Dawe Kechen
Barbare
Kinso Diday Humbo Leka Abaya Aleta wondo Bale Korahe
Chuko Bona zurila
Kucha Boreda
SNNPR Demba goffa
Geze goffa
Dilla zuria
Dara Hulla Bensa
Harene Bulki
Bench Maji Dita
Mirab abaya Wonago Arerosa Gura Damole
Basketo SW Oyda Zala Dalo Mena
Dardamole Chencha Yingacheffe Gode
Nbadebrest Gamo Gofa Galanaa Kocherle Gedeo
Kemba A/minchizuria
Bonke
Amaro
Meda Walabu
Amaro SW Melka Sodda
Derashe
Guji
Dirashe SW Burji Mustahil
South Omo Konso Burji SW Dugda Dawa
Charati
Hargelle Barie
Konso SW Liben Afder
Yangatom Filtu
Yabello
Hamer
Taltelle Liben
Daesenech Borena Hudet
Arero
Dolobay
Doloodo
Dilo
Dahahas
Dire
Miyoo
Moyale
0 75 150 300 450 600
kilometers
Source: World Bank calculations based on the merged 2011 HICES and the 2010 LIU livelihoods database.
Note: PSNP = Productive Safety Nets Program.
Figure 2.8: Poverty by Livelihood Type in Ethiopia, 2007
45
40
Average of poverty headcount (%)
35
30
25
20
15
10
5
0
Cropping Agropastoralist Pastoralist
Livelihood type
Maintaining the Momentum while Addressing Service Quality and Equity 13
Figure 2.9: Poverty by Livelihood Type and Region in Ethiopia, 2007
70
Average of poverty headcount (%)
60
50
40
30
20
10
0
ng
t
ng
t
t
t
t
ng
t
t
is
is
is
is
is
is
is
al
al
al
al
al
al
al
pi
pi
pi
or
or
or
or
or
or
or
p
p
p
ro
ro
ro
st
st
st
st
st
st
st
pa
pa
Pa
pa
Pa
pa
Pa
C
C
C
ro
ro
ro
ro
Ag
Ag
Ag
Ag
SNNPR Oromiya Afar Somali
Livelihood type by region
Note: SNNPR = Southern Nations, Nationalities, and People Region.
Figure 2.10: Poverty Rates by Livelihood Type and Safety Net Coverage in Ethiopa, 2011
60
Average of poverty headcount (%)
50
40
30
20
10
0
No safety net Safety net No safety net Safety net No safety net Safety net
Cropping Agropastoralist Pastoralist
Livelihood type
Source: FAO 2010.
Note: PSNP = Productive Safety Net Program.
14 Maintaining the Momentum while Addressing Service Quality and Equity
Box 2.2: Ethiopia’s Rural Productive Safety Nets Program
In 2005 the GoE launched the PSNP to help address the needs of chronically food insecure
households. The PSNP is a flagship program both in its scope, covering around 10 million
people, and in its partnership approach. The PSNP provides up to 10 million people with
(a) predictable food and cash transfers to targeted beneficiary households so as to avoid
asset depletion in times of need; and (b) the creation of productive and sustainable community
assets through a public works program that contributes to the rehabilitation of severely
degraded areas and increases household productivity.
PSNP has contributed significantly to improved food security in Ethiopia over the past decade.
In the highland regions, PSNP clients have seen their average months of food security rise
from 8.4 per year in 2006 to 10.1 in 2012. The public works program addresses root causes
of vulnerability and food insecurity by supporting the development of a productive watershed
and linking rural communities to small towns where they can access inputs, markets, and
services. Further, PSNP public works have led to important improvements in rural infrastructure
and have contributed to improved access to education and health services, enhanced water
retention, and reduced soil and water run-off. The public works have also protected land in
area enclosures, which increases soil fertility and carbon sequestration.
In 2014 the annual budget of the PSNP program was over US$500 million a year. PSNP has provided
important disaster response through contingency budgets at woreda and regional levels and a
federal risk financing mechanism. Since its launch, PSNP has grown the number of rural woredas
that it covers: 260 in 2005, 290 in 2009, 320 in 2014, and a planned 411 in 2018. This expansion
has been driven both by the splitting of woredas and the expansion of the program into Afar and
Somali regions. The analysis in this report examines data for PSNP woredas from 2005–09.
Source: World Bank 2014b.
By contrast to the marked differences in poverty rates between agrarian and pastoralist
livelihoods, there was little difference in the poverty rates across the different categories of
crop–market interaction types within the agrarian livelihoods category. Poverty rates for
households pursuing agrarian cropping livelihoods were also very similar to those covered
and those not covered by the PSNP safety net. This may be the result of the positive effects
of the PSNP . However, poverty rates in pastoralist and agropastoralist were much higher in
woredas covered by PSNP , pointing to the possibility that the program has had less of an
equalizing effect in these areas. These variations in the poverty characteristics of rural and
urban areas are foundational to the analysis of service delivery explored in this report.
References
FAO (Food and Agriculture Association) and WFP (World Food Program). 2010. Special Report:
Crop and Food Security Assessment Mission to Ethiopia. New York: FAO. http://www.fao
.org/docrep/012/ak346e/ak346e00.pdf.
GoE (Government of Ethiopia). 2010. An Atlas of Ethiopian Livelihoods—The Livelihoods
Integration Unit. Addis Ababa: GoE.
Maintaining the Momentum while Addressing Service Quality and Equity 15
———. 2012. “Ethiopia’s Progress Towards Eradicating Poverty: An Interim Report on Poverty
Analysis Study (2010/11).” Development Planning and Research Directorate, Ministry of
Finance and Economic Development, Addis Ababa.
Ozlu, M. O., A. Alemayehu, M. Mukim, S. V. Lall, O. T. Kerr, O. Kaganova, C. O. Viola, R. Hill,
E. Hamilton, A. T. Bidgood, B. L. Ayane, A. I. Aguilera De Llano, T. Gebre Egziabher, and
S. Z. Gebretsadik. 2015. “Ethiopia Urbanization Review: Urban Institutions for a Middle-
Income Ethiopia.” Working Paper 100238. World Bank, Washington, DC. http://documents.
worldbank.org/curated/en/543201468000586809/Ethiopia-Urbanization-review-urban
-institutions-for-a-middle-income-Ethiopia.
World Bank. 2014. Ethiopia—Productive Safety Nets Project Four. Washington, DC: World Bank.
———. 2015. Ethiopia Poverty Assessment 2014. Washington, DC: World Bank.
16 Maintaining the Momentum while Addressing Service Quality and Equity
Natural spring water supply, Ayjaseta Kebele in Fegeta Lakoma Woreda, Amhara Region, Ethiopia.
© Chris Terry/World Bank
Chapter 3
Framework for WASH Service
Provision in Ethiopia
Ethiopia has taken a progressive approach to instilling rights to basic services—including the
right to clean, safe, and adequate water supply and sanitation—in its Constitution and through
the ratification of international conventions. Article 90 of the 1994 Constitution states that “…
to the extent the country’s resources permit, policies shall aim to provide all Ethiopians access
to public health and education, clean water, housing, food and social security.” Although
universal coverage to basic service has not yet been achieved, Ethiopia has made significant
steps to create the necessary enabling environment: sector policies and plans; institutions at
federal, regional, and woreda (district) level; and financing modalities to support progress. Key
to creating this enabling environment is that both the core systems for rolling out service
delivery in general (for all basic services) and sector-specific systems for shaping that service
delivery have evolved in tandem with one reinforcing the other enabling at-scale service delivery.
The establishment of a decentralized system of service delivery has taken place gradually but
deliberately over the last 20 years. The 1995 Constitution established a federal system with
nine ethnically based regional states and two chartered cities with the right to self-determination.
Each state has a parliamentary assembly, which elects representatives to the upper chamber
of the federal parliament, the House of the Federation. Regions are split into two distinct
groups, which also act a useful reference point of analysis in this report: large regions (Amhara;
Oromia; Southern Nations, Nationalities, and People Region [SNNPR]; and Tigray) and emerging
regions (Afar, Benishangul-Gumuz, Gambella, Harari, and Somali). The chartered cities of Addis
Ababa and Dire Dawa have different structures but are considered equivalent to regions. The
region of Harari has different characteristics than the other regions since it is largely urban.
The first phase of decentralization took place in 1995 with some of the central government
powers devolved to regional states. In 2003, the GoE mandated a second wave of decentralization
to woredas. Woredas, of which there are now over 800, are Ethiopia’s key unit of local
government. They have service delivery departments, including for water, health, education,
and agriculture extension. Kebeles sit under woredas in the hierarchy and have an average
population of about 5,000. In the most populous regions, zones were introduced as an
intermediary administrative area above woredas, though their oversight over woredas varies
among regions. The decentralization process stimulated a series of legal, fiscal, and
administrative reforms, which began with four of the largest regions. The reforms have resulted
in significant responsibilities for the provision of basic services being placed on woredas.
In parallel with fiscal decentralization, regions and woredas have significant service delivery
roles. Regional and woreda governments have their own means of raising finance through local
taxes. However, the percentage of regional budgets derived from internal revenue is still
relatively small (the highest share was 20 percent in 2009/10), and the rate of growth in the
share of budget derived from internal revenue has been low (Assefa 2015). The revenue
generating capacity of the woreda level is even more constrained due both to the woreda’s
limited tax assignments and to their limited institutional capacity (Snyder et al. 2014).
To compensate for the imbalance in revenue and expenditure assignments, regions rely on a
system of intergovernmental transfers between federal, regional, and woreda levels. There are
two main types of intergovernmental transfer instruments in Ethiopia: the unconditional, or
General Purpose Grant (GPG); and conditional, or Specific Purpose Grant (SPG). The block
Maintaining the Momentum while Addressing Service Quality and Equity 19
grant transfer scheme is based on equity in service delivery for all Ethiopians, and respective
allocations are determined by a set of criteria that include population, expenditure needs, and
revenue-raising capacities of each region. This approach seeks to smooth out the disparities
in revenue-raising capacity across different levels of government (vertical imbalance) and
equity between different jurisdictions (horizontal imbalance) (Assefa 2015).
Regions determine formulas to distribute block grant resources to woredas as long as
resources are allocated in a rule-based manner following a predetermined and objective criteria
(Garcia and Rajkumar 2008). Some regions, such as Amhara and Tigray, follow the same
budget allocation criteria to distribute resources downward to woredas, whereas others, such
as SNNPR, use uniform distribution to all woredas irrespective of any weighting criteria.
Together, the two tiers of regional and woreda government and the intergovernmental transfer
mechanisms form the backbone for all serivce delivery in Ethiopia, including for water supply
and sanitation.
The evolution of Ethiopia’s formal water sector began in 1995 with the establishment of the
Ministry of Water Resources, which happened in parallel with political, fiscal, and administrative
decentralization, and which created the core systems for service delivery. The first water
resource management policy was passed in 1999 to promote equitable and efficient use of
water resources for water supply, sanitation, irrigation, and hydropower. The policy was shortly
followed by a Water Sector Strategy (2001) and Water Sector Development Programme (2002)
to set out a more comprehensive institutional and financial framework to achieve the water
policy objectives.
The 2005 Universal Access Plan (UAP) for water supply and sanitation consolidated the link
between Ethiopia’s decentralized institutions with the policy direction for expanding services.
The UAP became the nationwide delivery mechanism; it set out explicit national targets
for water supply and sanitation with the aim of reaching 98 percent, 100 percent, and
98.5 percent for rural, urban, and combined rural and urban settings, respectively, with access
by 2012 (later revised to 2015). In rural areas access was to 15 liters per capita per day within
1.5 kilometers, and in urban areas, 20 liters per capita per day within 0.5 kilometers. The plan
endorsed low-cost technologies and empowered woredas to deliver basic services and
individual households to build self-supply sources. The UAP was key in galvanizing political and
financial support for water supply and sanitation as a means of alleviating poverty.
The integration of sanitation and hygiene promotion with water supply has been an important
step taken by the GoE. The National Hygiene and Sanitation Strategy (NHSS) was developed
by the Ministry of Health (MoH) and published in 2005; it complements the existing Health
Policy and Water Sector Strategy.
The government’s strong commitment to decentralization and a clear sector policy framework
have provided a solid basis to guide service delivery. For the most part, the GoE has clearly set
out functions, coordination mechanisms, and guidance for implementation within the water
supply, sanitation, and hygiene (WASH) sector. However, the strength of the sector policy
framework and clarity of strategy varies among the four WASH subsectors. The rural subsectors
are more mature than the urban subsectors, and water subsectors are more developed than
sanitation (see box 3.1 on the roles and responsibilities for rural water supply). In urban areas,
autonomous utilities were established and over the last 10 years the MoWIE has introduced
further legislation to strengthen these, including a moving toward full cost recovery for urban
water schemes. There is also a wide range in the capacity to implement these policies and
across regions and woredas.
Since the late 1990s Ethiopia has been a country at the forefront of managing the interface
between public finance and development assistance. Though programmatic approaches were
adopted earlier in other sectors such as health and education, development assistance to
water supply and sanitation has steadily shifted from project to programmatic approaches over
the past decade. The ambitious targets set out in the UAP and the Growth and Transformation
20 Maintaining the Momentum while Addressing Service Quality and Equity
Box 3.1: De Jure Assignment of Functions in Ethiopia’s Rural Water Subsector
Ethiopia’s institutional arrangement for WASH is clearly articulated on paper, with roles distributed across federal and
, the government has introduced
regional levels, woredas, and communities (table B3.1.1). Since the inception of the OWNP
WASH coordination, management, and guidance bodies at the federal and regional tiers of government to manage
Consolidated WASH Account (CWA) investments. These institutions are less developed, and recent research suggests
that understanding of their role is limited at regional and woreda levels.
Table B3.1.1: Responsibilities of WASH sectors institutions
Level Body Responsibilities
Federal Ministry of Water, Irrigation •• Planning, development, and management of resources
and Energy (MoWIE) •• Development of guidelines, strategies, policies, programs
•• Development and implementation of sectoral laws and
regulations
•• Chairing the national WASH committee
Regional Zonal Water Resources •• Supporting water bureaus in giving technical support to
Development Office woreda water offices and town water supply offices
•• Coordinate activities, plans, and reports, and liaise
between water bureaus and woreda water offices
Bureau of Water Resources •• Implementing federal policies and adapting them to
Department conditions of the region
•• Chairing the regional WASH steering committee
Regional WASH team •• P
roviding support to woreda-level authorities
•• May directly support WASHCOs when breakdowns exceed
local capacity
Woreda Woreda Water Resources •• Responsible for investigation, design, and implementation
Development Office of small-scale water supply schemes
•• Provide technical support to town water supply offices in
towns without municipalities
Woreda WASH Team •• Cross-sectoral team responsible for all aspects of water
supply and sanitation development
•• Provide support to kebeles and WASHCOs directly for
monitoring and technical support
Woreda / WASHCO •• Community-level WASH committee established to manage
kebele a specific WASH facility (there may be multiple WASHCOs
in a kebele, depending on the number of facilities)
•• WASHCOs are accountable to woreda water team
Maintaining the Momentum while Addressing Service Quality and Equity 21
Box 3.2: Integrating Public Finance with Development Assistance
There are three channels established for WASH sector funding, but these are complex and
overlapping (see figures B3.2.1 and B3.2.2):
• Channel 1 is on-budget and is managed by the MoFEC, regional Bureaus of Finance and
Economic Development (BoFEDs), and woreda finance offices. “On-budget” means
included in the national annual budget description. Channel 1 is further divided into the
following:
• Channel 1a: funds are transferred through the MoFEC to regional BoFEDs, and then
to WASH sector bureaus and offices.
• Channel 1b: funds are transferred through the MoFEC, but funds go directly to WASH
sector bureaus and offices.
• Channel 2 funds are made available directly to the WASH sector ministries (MoWIE, the
Ministry of Health [MoH], MoE) and then to their respective bureaus and offices at lower
levels. Bilateral assistance and most United Nations agency investments flow through
channel 2, and are also on-budget.
• Channel 3 funds are directly transferred by donors and aid agencies to service providers,
and the donor retains financial control. Channel 3 funds are off-budget, meaning they
are outside the control of government and are not included in the national annual
budget.
Figure B3.2.1: Financial Channels in Ethiopia
oth and
)
ers
Os
(NG
Cha
nne Channel 1a
l3
(GoE)
Channel 1
(mainstream
nel 2 GoE system)
(OPs g
ch n tly to
dir c rs)
Chan
nellin
secto
Channel 1b
e
(CWA)
a
Note: CWA = Consolidated WASH Account; DP = development program; GoE = Government of Ethiopia;
NGO = nongovernmental organization.
box continues next page
22 Maintaining the Momentum while Addressing Service Quality and Equity
Box 3.2: Continued
Figure B3.2.2: Sectoral Financial Flows in Ethiopia
Donor 1 MoFED WASH sector
Foreign ministries
Donor 2 special CWA
accounts Br
Donor 3 WRDF
WASH sector bureaus BoFEDs
Town water
boards
Zone sector
ZoFEDs ToFEDs WoFEDs
offices
WASHCOs
Note: BoFED = Bureau of Finance and Economic Development; CWA = Consolidated WASH Account; DP = development
program; MoFED = Ministry of Finance and Economic Development (MoFED); ToFED = Town Administration Office of
Finance and Economic Development; WASH = water supply, sanitation, and hygiene; WASHCOs = water supply, sanitation, and
hygiene committees; WoFED = Woreda Office of Finance and Economic Development; ZoFED = Zonal Administration Office of
Finance and Economic Development.
Plan (GTP) were a major driver for the GoE and development partners to reorganize and
streamline investment in water supply, sanitation, and hygiene (WASH). (See box 3.2.)
The resulting ONE WASH National Programme (OWNP) is, since 2011, the GoE’s main vehicle for
achieving its ambitious WASH goals. The institutional arrangements for the first national WASH
Program were set out in the 2011 Memorandum of Understanding and WASH Implementation
Framework (WIF), signed by the Ministry of Finance and Economic Cooperation (MoFEC),
the Ministry of Water, Irrigation and Electricity (then Water Resource and Energy) (MoWIE), the
Ministry of Health (MoH), and the Ministry of Education (MoE). The objective of the OWNP is to
extend and sustain access to water supply and sanitation services in rural and urban areas,
while moving away from discrete WASH projects and toward a programmatic, sectorwide approach
based on four key principles:
•• Integration of water, health, education and finance sectors
•• Alignment of partner activities (donors, nongovernmental organizations [NGOs], private
sector agents) with those of the GoE
•• Harmonization of partner approaches and activities
•• Strengthened partnerships between WASH stakeholders at all levels, from federal to
woreda
However, though good progress has been made in interfacing public and donor resources,
there will be a large annual financing gap as Ethiopia adopts the Sustainable Development
Maintaining the Momentum while Addressing Service Quality and Equity 23
Goals (SDGs). According to a World Bank study (World Bank 2016) on the costs of meeting the
SDGs for WASH, it is estimated that Ethiopia would need to invest US$2.5 billion a year to
extend basic services and over US$5 billion a year extend safely managed services (Hutton
and Varughese 2016). The funding gap of US$2 billion a year for basic or US$4.5 billion a year
for safely managed services will not be met by public and donor resources alone. Ethiopia and
its development partners will need to leverage far greater levels household and private finance.
GTP II places emphasis on building the capacity of the domestic private sector. To meet the
high demands of the OWNP , the private sector is a potential source of additional capacity for
the WASH sector. There is a clear need for private contractors, consultants, and suppliers’
engagement to support the designing, building, and rehabilitating of water supply and sanitation
schemes. MoWIE carried out an assessment of supply chains in 2010, and the study shows
that supply chains for hand pumps and spare parts, largely driven by market forces, were still
in their infancy in Ethiopia. The World Bank’s own assessment of the sanitation supply chain
further confirmed it is fragmented and weak. However, both studies confirm that there is a
significant market for WASH products and services, such as well drilling, household water
treatment, on-site sanitation products, and fecal sludge management.
To maximize the private sector contribution, there is a need for more supportive sector policies
and strategies to create a conducive enabling environment to facilitate their engagement.
Basic challenges such as lack of clear regulatory frameworks, unskilled labor, high transport
costs, limited availability of financial services, and land tenure insecurity are barriers to more
meaningful engagement of the private sector in the WASH sector. In addition, questions still
remain over whether economic conditions are such that financially sustainable private sector
involvement in the construction, operation, and management of WASH infrastructure are
possible in the near term without carefully planned programs of support.
References
Assefa, D. 2015. “Fiscal Decentralization in Ethiopia: Achievements and Challenges.” Public
Policy and Administration Research 5 (8): 27–39.
Garcia, M., and A. S. Rajkumar. 2008. “Achieving Better Service Delivery through Decentralization
in Ethiopia.” African Human Development Series Working Paper 131, World Bank,
Washington, DC.
Hutton, G., and M. Varughese. 2016. The Costs of Meeting the 2030 Sustainable Development
Goal Targets on Drinking Water, Sanitation, and Hygiene. Washington, DC: World Bank.
Snyder, K. A., E. Ludi, B. Cullen, J. Tucker, A. Zeleke, and A. Duncan. 2014. “Participation and
Performance: Decentralised Planning and Implementation in Ethiopia.” Public Administration
and Development 34: 83–95. doi:0.1002/pad.1680.
World Bank. 2016. Institutions and Service Provision of Urban Sanitation in Addis Ababa.
Washington, DC: World Bank.
24 Maintaining the Momentum while Addressing Service Quality and Equity
Collecting water from a community water point in Mareko Word, SNNPR.
© Chris Terry/World Bank.
Chapter 4
Rural WASH Sector Analysis
Rural Water Supply Subsector Analysis
National Status and Trends
In 2015 Ethiopia met its Millennium Development Goal (MDG) for water supply. This significant
achievement was largely driven by the very rapid increase to improved access to rural water: one
of the top five fastest rates of change in the world. Nearly half of all rural Ethiopians had access
to an improved water source in 2015 (see figure 4.1), up from just 15 percent in 1994 (UNICEF/
WHO 2015).1 Over the period around 35 million people made the shift from using unprotected
wells, springs, and surface sources to an improved water source. Two-thirds of this access is
provided from protected wells and springs and one-third from communal piped systems.
Evolution of Funding and Capacity for Delivering Rural
Water Supply
In the 1990s donor-funded programs were central to progress. Initially the Ministry of Water,
Irrigation and Electricity (MOWIE) worked with programs such as the World Bank–funded
Figure 4.1: Rural Drinking Water Trends in Ethiopia, 1990–2015
100
16
80
54
35
Coverage (%)
60
40
43
20 48
3
0 0 1
1990 2015
Surface water
Other unimproved sources
Other improved sourcel
Piped onto premises
Source: WHO/UNICEF 2015.
Maintaining the Momentum while Addressing Service Quality and Equity 27
Ethiopia Social Rehabilitation and Development Fund (ESRDF) to deliver services nationwide.
By the late 1990s programs such as the ESRDF were also being used to build up capacity in
regional offices. Through the ESRDF alone, 3 million people in rural areas gained access to
improved water at a cost of just under US$30 million, or US$3 million a year from 1995–2005.
Other bilateral donors and nongovernmental organizations (NGOs) delivered services through
area-based projects.
During the early 2000s, as decentralization took root, the rollout of rural water schemes
through government systems grew rapidly. By 2006–08 around US$40 million a year was being
spent on rural water supply, 65 percent of which was funded through Government of Ethiopia
(GoE) block and special purpose grants, and 35 percent from, mainly, multilateral development
partners. Though most of the sector finance (60 percent to 70 percent) was being managed
by regional bureaus, after the second wave of decentralization, woredas were managing
10 percent of capital expenditure.
By the mid-2000s rates of execution through government channels were higher than through
development partner channels (see figure 4.2). From 2006–08 only 60 percent of what was
budgeted for annually (US$65 million) was actually being spent. In response to these low rates
of execution, both the World Bank and the African Development Bank (AfDB) changed their
funding modalities by integrating them into the more streamlined channel. Over the 2008–12
period this shift to funding modalities, aligned with country systems, translated into better
overall budget execution rates (80 percent) though still lower in some regions and lower than
this average for capital expenditure at the woreda level. With additional commitments over this
2009–12 period annual expenditures on rural water supply rose above US$50 million a year,
peaking at US$60 million in 2009/10. This was managed mainly by regions (43 percent) but
with a sizable share managed by woredas (37 percent) and a minority share managed at the
federal level (20 percent) (World Bank 2015b).
Expenditure by NGOs also increased. From 2006–08 NGO expenditure on WASH was estimated
at US$5 million a year, while from 2009–12 period the NGO Supply and Sanitation Forum
reports annual expenditures of US$18 million a year.
Figure 4.2: Budgets and Expenditure for Main Rural Water Supply Financing Modalities in Ethiopia, 2006–08
400
350
300
Br (millions)
250
200
150
100
50
0
Regional block Food security Productive AfDB World Bank UNICEF Finland (CDF) NGOs
grants program safety nets (EWSSP)
program
On treasury On-budget multisector On-budget water supply and sanitation Off-budget
Annual budget Annual expenditure
Source: IBEX.
Note: Amounts are three-year average for 2006, 2007, and 2008. AfDB = African Development Bank; CDF = Community Development Foundation; EWSSP = Ethiopian
Water Supply and Sanitation Project; NGO = nongovernmental organization.
28 Maintaining the Momentum while Addressing Service Quality and Equity
While investments from donors have not been the main financing source, donor projects have,
and will continue to be, instrumental in building capacity at regional and woreda levels. From
the mid-1990s donors supported policy and institutional development, including the formation
of the Federal Ministry of Water Resources. As service delivery was decentralized, donor
projects shaped the formation and capacity building of regional water bureaus and woreda
water desks. Administrative and technical capacity building benefitted from a learning-by-doing
approach through the rigorous design, procurement, contract management, and reporting
required by donors. Good practices included (a) the use of woreda support groups (WSGs) to
help woredas develop strategic plans and identify and design projects; (b) the development of
project implementation manuals; and (c) annual work planning.
By 2008 capacity for planning and supervising development of rural water supplies at the
regional level was well established across most regions. This included skills in sector planning,
scheme design, procurement, contract supervision, scheme management training, and
postconstruction support. The allocation to salaries at regional level increased threefold in
nominal terms from 2005–08, and operational costs increased fivefold, enabling regional level
staff to manage projects. This regional capacity was greater in the large regions than in the
emerging regions, which is reflected in the progress made across regions. The larger regions
were able to implement capacity through state-owned drilling and dam construction companies
and had better access to private sector contractors than emerging regions.
Unlike capacity at the regional level, capacity and funding at the woreda level has been less
well developed. The 2009 PER (World Bank 2009) reports that as result of increasing the
number of woredas and the number of staff deployed on the water desks in the second wave
of decentralization, the allocation to salaries at woreda level increased tenfold in nominal
terms between 2005–08. During the same period, operational costs increased sixfold in
nominal terms, but dropped as a percentage of water desk spending (33 percent to 22 percent
of the recurrent budget). The average number of woreda water desk staff in 2008 was 7.5, with
an operational budget averaging Br 2,000 (US$200) per staff member per year. The 2015 PER
(World Bank 2015b) similarly notes that the low level of recurrent budget remains a constraint
to the quality and adequacy of supervision and support to the water sector. The amount of
recurrent budget allocated at the woreda level in 2009–12 rose from Br. 141.5 million to Br
622.5 million. However, when divided among the large number of woredas in the country, the
operational budget left after paying salaries averaged only Br 5,287 per woreda per year
(around US$300 in 2015).
Operational budgets at these levels do not enable staff members to carry out their basic
duties of data collection and backstopping support to rural schemes. During interviews held
at the woreda level for the 2009 PER (World Bank 2009), it was evident that coupled with the
absence of vehicles, equipment, and office space, this environment was leading to low morale
and ultimately high staff turnover. The result has been that woredas are understaffed and staff
members lack key skills. Even in Amhara region, a favored region in which to work, only
30 percent of posts were filled (World Bank 2014).
The Expansion of Rural Water Supply Infrastructure
and its Sustainability
From 2006 to 2012 the construction of water points and schemes has been at an industrial
scale across Ethiopia. The backbone of generic service delivery machinery that GoE has put in
place through the two-tier decentralization process, coupled with strong sector policy direction
and consistent sector funding (from government and donors), have enabled between 6,000
and 10,000 water points a year to be constructed from 2006 to 2012.
However, only around 75 percent of the 85,000 rural water schemes captured by the 2011
National WASH Inventory were reported as functional (NWI 2011). 2 Though this is a higher
Maintaining the Momentum while Addressing Service Quality and Equity 29
level of functionality than in many other countries in the Africa region (70 percent or lower is
common [Carter and Ross 2016]), the role and capacity of woredas to sustain access remain
questions among policy makers, particularly as the stock of infrastructure grows Tincani
et al. 2015).
More detailed studies of water point operation reveal deeper problems of nonfunctionality
(see figures 4.3 and 4.4). A 2016 detailed survey of 171 community shallow (tube wells
equipped with hand pumps), chosen to be representative of woredas in the Ethiopian Highlands,
finds that 82 percent were working at the time of the survey, which is similar to data from the
National Well Inventory survey. However, extending the definition of functionality to exclude low
yielding (less than 10 liters per minute) and unreliable boreholes (down time of more than one
month per year), functionality dropped to 45 percent (Kebede et al. 2017).
Figure 4.3: Regional Variation in Water Point Functionality in Ethiopia, 2012
35
22
30
Water points (thousands)
25 25
20
27
15
33
10
5
34 33
32
25
0
Gambela BG Afar Somali Tigray SNNPR Oromia Amhara
Functional water points Nonfunctional water points (%)
Source: National WASH Inventory, 2012.
Note: SNNPR = Southern Nations, Nationalities and People Region; BG = Benishangul Gumuz.
Figure 4.4: People per Water Point by Region in Ethiopia 2012
35
People per water point (hundreds)
30
25
20
15
10
5
0
Tigray Amhara BG Gambela Afar National SNNPR Oromia Somali
Population per water point Poor persons per water point
Source: National WASH Inventory, 2012.
Note: SNNPR = Southern Nations, Nationalities and People Region.
30 Maintaining the Momentum while Addressing Service Quality and Equity
A key finding from the Overseas Development Institute (ODI) RiPPLE program in Ethiopia is that
woreda and regional government staff are often unaware of the problems village water
committees have with repair and maintenance. Research conducted by the RiPPLE program in
SNNPR, for example, indicates that 43 percent to 65 percent of water points or schemes were
nonfunctional. Moreover, problems are not restricted to more complex schemes with deep
boreholes and motorized pumps. In Mirab Abaya woreda, for example, nearly 50 percent of off-
plot, communal water points equipped with hand pumps were not working at the time of survey
(Calow et al. 2013).
Improving on this level of functionality depends in part on whether woreda water desks will
backstop community-level water management committees. Backstopping involves periodically
checking whether cost recovery mechanisms are working and facilitating the sourcing and
fitting of spare parts when water committees need help in keeping systems running. These
activities require recurrent operational costs (see box 4.1).
However, poor siting, design, and construction expose weaknesses at regional and woreda
levels. Postconstruction sustainability audits of water point infrastructure examine siting,
design, and construction standards. Recent studies conducted for the World Bank (Calow et al.
2013) and the CMP (Calow et al. 2016) point to upstream implementation issues, for example,
water point type and design were not well matched with hydrological or hydrogeological
conditions, which is a regional planning function. A poorly sited and constructed dug well
(woreda responsibility) or shallow well (regionally commissioned, but subcontracted to a drilling
company) are more likely to have a low or intermittent water supplies, more likely to be
contaminated by pathogens, and more likely to suffer flood damage. These upstream
weaknesses greatly constrain what village water committees are able to do to keep water
points functioning.
Box 4.1: Maintenance of Water Points in Lodi Etosa Woreda, Arsi Zone, and
Oromia Region
In 2011 the Woreda Water Office built a spring protection with government funding for Tuma
Wolkitei and Meda Gefersa villages in Lodi Etosa Woreda. A WASH committee was formed to
oversee the scheme, but the committee received no training. Except for the poorest of the
poor households, households pay Br 30 a year to collect water from the spring.
Since the spring was located in a streambed, a hand pump was used to lift water into a spring
box. In 2015 the hand pump broke. In this case the provision of the spare part was assumed
to be the Woreda Water Office’s responsibility both by the Woreda Water Office and user
community. The Woreda Water Office was informed of the broken pump by the WASH
committee, but neither the woreda nor the committee had funds to purchase the spare part,
since the WASH committee had not collected funds for the repair. Households went back to
fetching water from traditional surface and unprotected sources. After 10 months the Woreda
Water Office fixed the hand pump by replacing the broken part with a part taken from another
new pump within their store. Yet, the pump was vandalized shortly afterward with essential
screws stolen from the pump. Villagers and leaders recognized the need to strengthen the
WASH committee; fence the scheme; and collect the nominal fee to cover maintenance cost;
however, none of this happened.
box continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 31
Box 4.1: Continued
Broken water point in Arsi Woreda Oromia.
© Chris Terry/World Bank
Like most government-financed schemes in the woreda, the focus during the implementation
period was on the hardware provision alone with no consideration of sustainability. No budget
was allocated for training the WASH committee for follow-up after the construction of the
spring protection. Though at the zonal and woreda level, technical staff are employed to
provide technical support to sustain the schemes yet they have no budget. Staff at Lodi Etosa
Woreda found this lack of budget demotivating, pointing out that paying their salaries without
an operations budget was a waste of money.
box continues next page
32 Maintaining the Momentum while Addressing Service Quality and Equity
Box 4.1: Continued
Discussions at the woreda and zonal levels revealed that the same trend is being adopted in
the implementation of government-financed schemes at present, and that it is common that
designs are compromised during implementation to reduce construction costs. Unless the
water policy is reviewed to give clear direction on roles and responsibilities and on
postconstruction support, this trend of focusing on the infrastructure development and poor
sustainability will continue.
Both government- and donor-financed projects need to budget for the hardware and software.
Budgets are needed for community mobilization and sensitization, the preliminary studies,
design studies, capacity strengthening component, and postconstruction support. This may
mean higher per capita costs but this would be preferable to the wasted sunk costs of
abandoning existing schemes.
Source: Yemane and Defere n.d.
Access Disparities by Wealth and Consumption
With 35 million people gaining access to improved sources but still 40 million rural
Ethiopians without access to improved service, was it predominantly wealthier or poorer
people who captured this gain? Ethiopia’s progress in providing access to improved water
supply in rural areas is relatively equitable. Estimating the progress across different
consumption and wealth quintiles, it is clear that, regardless of the metric, people across
all quintiles have experienced a significant jump in access. Using wealth quintiles derived
from an asset index, the poorest quintile saw a 27 percent increase in access compared
to 36 percent by the wealthiest quintile between 1995 and 2012. Using the consumption-
based method, the difference in access rates is even less with only a 7 percentage points
difference between the lowest and highest consumption quintiles in 2011 (figure 4.5 and
figure 4.6).
Compared to the evenly spread access to improved sources, access to piped water from
stand posts in rural areas—representing around one-third of improved water access—is
more skewed across quintiles. Based on consumption quintiles, the distribution of piped
water access is only marginally tilted toward those with greater purchasing power
(figure 4.7). However, based on wealth quintiles this distribution is more skewed toward
wealthier populations with a 33 percentage points difference between the poorest and the
wealthiest (figure 4.8). Though part of this greater skew towards wealthier populations is
due to the inclusion of water supply and sanitation in the asset index used to calculate
wealth (a problem of endogeneity), it may also point to affordability of piped water compared
to other improved sources.
Access Disparities by Geography
Though the progress was even across categories of wealth and consumption, there are clear
disparities across Ethiopia’s regions (see map 4.1). Between 2000 and 2016, access to
improved water supply more than doubled in percentage terms from just under 20 percent
to just under 50 percent. Progress across Ethiopia’s five large regions has been strong.
Maintaining the Momentum while Addressing Service Quality and Equity 33
Figure 4.5: Rural Drinking Water Coverage by Wealth Quintile in Ethiopia, 1995–2011
100
80
60
Percent
40
20
0
Poorest Second Middle Fourth Richest
Quintile
Unimproved Other improved Piped on premises
Source: DHS, 2017.
Note: Wealth quintile trend is based on subset of surveys (DHS) leading to steeper slope than JMP trend data. Water supply and
sanitation variables removed from DHS asset index.
Figure 4.6: Rural Drinking Water Coverage by Consumption Quintile in Ethiopia,
1995–2011
100
80
60
Percent
40
20
0
Poorest Second Middle Fourth Richest
Quintile
Unimproved Other improved Piped on premises
Source: WMS/HICES, 2011.
Note: Wealth quintile trend is based on subset of surveys (DHS) leading to steeper slope than JMP trend data. Water supply and
sanitation variables removed from DHS asset index.
34 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 4.7: Access to Rural Piped Water from Public Stand Posts by Consumption
Quintile in Ethiopia, 2011
40
35
30
25
Percent
20
15
10
5
0
Poorest Poorer Middle Richer Richest
Quintile
Source: World Bank calculations based on WMS/HICES 2011.
Figure 4.8: Access to Rural Piped Water from Public Stand Posts by Wealth Quintile in
Ethiopia, 2011
40
35
30
25
Percent
20
15
10
5
0
Poorest Poorer Middle Richer Richest
Quintile
Source: World Bank calculations based on DHS 2011.
Access in two emerging regions, Gambela and Benishangul-Gumuz, has also increased rapidly.
However, progress in Afar and Somali regions, which started from a low base, stand out as
having fallen further behind other regional states (figure 4.9). There are multiple reasons why
they have fallen behind, including that: they receive less rainfall than other regions, have more
complex hydrogeology (see map 4.2), have weaker regional and woreda administrations, and,
are sparsely populated by people practicing agropastoralist and pastoralist livelihoods.
Maintaining the Momentum while Addressing Service Quality and Equity 35
Map 4.1: Coverage of Improved Water Supply across Woredas in Ethiopia, 2007
Units of measurement – Total
Improved Coverage = Total
0.0–0.2
0.2–0.3
0.3–0.4
0.4–0.6
0.6–0.8
0.8–1.0
Source: Housing and Population Census 2007.
Map 4.2: Hydrogeology Index in Ethiopia, 2016
Hydrology Index
0
1
2
3
4
6
8
9
12
Sources: ODI and BGS, 2016.
Note: See Appendix C: Hydrogeological for more details.
36 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 4.9: Access to Improved Sources of Water in Rural Areas by Region in
Ethiopia, 2000–16
90
80
70
60
50
Percent
40
30
20
10
0
2000 2005 2010 2015
Tigray Affar Amhara Oromiya
Somali BG SNNPR Gambela
Sources: DHS 2000, 2011, and 2016.
Note: BG = Benishangul-Gumuz; SNNPR = Southern Nations, Nationalities, and People Region.
It is clear that variation in disparities within regions is even greater than that across
regions.3 While annual rainfall,4 and to a lesser extent hydrogeology, explain the interregional
variance—particularly the difficulty of providing improved water supply in Afar and Somali—
they do not adequately explain the variation in access rates within regions. Exploring a
further layer of positive and negative factors helps explain the differential progress within
regions. On the negative side, areas dominated by agropastoralist and pastoralist
livelihoods within otherwise large regions had particularly low access. On the positive side,
areas with higher levels of access were in areas dominated by agrarian livelihoods targeted
by the PSNP (see appendix B for an explanation of data sources, supporting analysis, and
regression model) (see map 4.3).
Woredas dominated by agropastoralist and pastoralist livelihoods were just over half as likely
to have access to improved water as agrarian woredas (see figure 4.10). This includes regions
that have significant numbers of agropastoralist and pastoralist woredas, such as Oromia and
SNNPR (see figure 4.11). This data suggests a systemic failure to deliver improved water
supplies to pastoralist and agropastoralist areas even in regions where access levels were
higher than in the pastoralist regions of Afar and Somali (appendix B).
These broad patterns of failing to deliver to pastoralist and agropastoralist areas are
supported by a more detailed analysis comparing access to improved water with rates of
poverty across woredas. Just under 80 percent of woredas with both a high proportion of
poor households and the lowest levels of improved water coverage5 were dominated by
pastoralist and agropastoralist livelihood types whose households live in remote, low
population density areas (less than 50 people per square kilometer). In contrast, over 80
percent of the woredas with both a high proportion of poor and high improved water
coverage were agrarian woredas targeted by the PSNP (see figure 4.12). For example, one
group is in the Wolayita Maize and Root Crop livelihood zone in SNNPR. These are very high
Maintaining the Momentum while Addressing Service Quality and Equity 37
Map 4.3: Productive Safety Nets Program in Woredas and Responsible Agency in
Ethiopia, 2010
Erob
Mereb Lekhe
Tahtay Adiabo Gulomekeda
Laelay Adiabo Ahferom
NW. Tigray Laelay Maichew Dalol
Tahtay Maichew
Adwa Saesi Ts ae d’aemba
Tahtay Koraro
Tigray Medebay Zana
Asgede Tsembila
Werie Lekhe Hawzien
E. Tigray
W. Tigray Naeder Adet Atsebi Wenberta
Koneba Berahle
Kilte Awlaelo
Kola Temben
Tselemti Degua Temben
Zone2
C. Tigray
Adiarkay Tselemt Tanqua Abergele Enderta Afdiera
Abala
Saharti Samre
Debark Beyed Erebti
Abergele Hintalo Wajirat
Dabat Janamora Elidar
W. Hamra Alaje
Megale
Sahila S. Tigray
Wogera Egdamohoni
Ziquola
N. Gonder Sokota Raya Azebo Teru
Misrak Belesa Ofla Yalo Dufti
Mirab Belesa Dehana
gazgibla Alamata
Afar Zone4 Elidar
Ebinat Bugna N. Wello Gulina
Mirab Belesa Awra
Kobo
Lasta
Gidan Zone1
Lay Gayiot Ewa
Meket Gubalafto Dufti
S. Gonder
Simada Delanta Wadla Habru Chefra
Amhara Bahir Dar Tach Gayint
Dawunt Ambassel
Asayta
Worebabo
Simada Tenta Tehuledere Mille
Kuta ber Adaare
Mek dela
Bati Afambo
S. Wello Argeta
W. Gojam Sayint Ajibar Telalak
Metekel Gonca Siso Enessie Mahal sayint
Dessie Zuriya
Agew Awi Argoba
E/Sar Mider Legambo
Albugo Oromiya Dewe
Debra Sina Woreilu Dewa Chefa Dewa Harawa
Ben Gunniz Legehida
Wogdi Ketta/Kelala
Githe Rabel Artuma/dalifagie
E. Gojam Aruma Fursi Zone5 Gewane
Jama
Asosa Shinile
Legend
Shebel Berierifa Menz Gera Mider Fursi Bure mudayetu
Gile Timuga Afdem Erer Shinelle
Menz Keya Gebriel
Menz Mama Mider
Menz Lalo Mider
Zone3
Regions
Semurobi gelallo
N. Shewa (R4) N. Shewa (R3)
Kamashi Kuyu
Zones
Horo Gudru Abiohu Gnea Dulecha
Wuchale Amibara Dire Dawa Jars
W. Wellega Argolela Tera Argoba spacial
Tongo SW Gro gutu Meta Kersa
Rombolcha
Kimbibit Assagert
E. Wellega
PSNP woredas
Haramaya Gurs
G um
Dobba
Meiso Tullo
Deder HUNDENIE Jijiga
Kurfachele Harshin
West Shewa Awash fentale Babile
AA Zone4 Chiro Bedeno
Fedis
Mesela Girawa
AA Zone3 Fantalle Guba Qoricha Gemachis Melka Belo
Kelem AA Zone6
Anchare Habroo E. Harerge Midhega
Babile
Boosat Kuni
S.W. Shewa W. Haraerge
E. Shewa Merti Aseko
Gole Oda
Illubabor Boke
D\Habour
Dedota Dodota Golecha(ARSI)
Zone 1 Dodota Darelebu
Meyu Mukke Degehabur
Zone 3 Gurage Meskan
Arsi
Mareko
Selti Z Dugda
Jimma Lega Hida
Yem SW Hadiya
Gambella Gibe Misna
A/T/J/Kombolcha
DalochaLanfaro Seru Fik
Unlmmu Seru
Gpmboro Lemmu Selti
Zone 2
Sheka Oromiya Soro Shahego
Alaba
Arsi Negelle
Gololcha(Bale)
Shala Sewane
Godere Duna Demboya Alaba
Warder
Kacha Bira KT
Tembaro Kore
Kefa Gena Bosa Shaahemene
Siraro Ginir
B oloso- Bombe Boloso Awasa zuna
Duguaria fan West Arsi Goro
Dawro Kingoo Koysha
Sodo zuria
Boricha Shebedino
Rayitu
Somali
Loma Offa Dale Sidama Dawe Kechen
Barbare
Kinso Diday Humbo Leka Abaya Aleta wondo Bale Korahe
Chuko Bona zurila
Kucha Boreda
SNNPR Demba goffa
Geze goffa
Dilla zuria
Dara Hulla Bensa Harene Bulki
Bench Maji Dita
Mirab abaya Wonago Arerosa Gura Damole
Basketo SW Oyda Zala Dalo Mena
Dardamole Chencha Yingacheffe Gode
Nbadebrest Gamo Gofa Galanaa Kocherle Gedeo
Kemba A/minchizuria
Bonke
Amaro
Meda Walabu
Amaro SW Melka Sodda
Derashe
Guji
Dirashe SW Burji Mustahil
South Omo Konso Burji SW Dugda Dawa
Charati
Hargelle Barie
Konso SW Liben Afder
Yangatom Filtu
Yabello
Hamer
Taltelle Liben
Daesenech Borena Hudet
Arero
Dolobay
Doloodo
Dilo
Dahahas
Dire
Miyoo
Moyale
0 75 150 300 450 600
kilometers
Source: FAO.
Figure 4.10: Improved Water Coverage by Dominant Livelihood Type in Ethiopia,
2007 and 2010
45
40
35
Improved water coverage (%)
30
25
20
15
10
5
0
Cropping Agropastoralist Pastoralist
Livelihood type
Source: World Bank calculations based on the merged 2010 LIU livelihoods database with 2007 Census.
38 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 4.11: Improved Water Coverage with Regions, by Livelihood Type
60
Improved water coverage (%)
50
40
30
20
10
0
CR AP CR AP CR AP PA AP PA CR AP PA
Gambella SNNPR Oromiya Afar Somali
Livelihood type
Source: World Bank calculations based on the merged 2010 LIU livelihoods database with 2007 Census.
Note: AP = agropastoralist; CR = cropping; PA = pastoralist; SNNPR = Southern Nations, Nationalities, and People Region.
Figure 4.12: Improved Water Coverage by Woreda’s Dominant Livelihood Type and
whether the Woreda is a Recipient of the PSNP Safety Net
60
50
40
Percent
30
20
10
0
No safety net Safety net No safety net Safety net No safety net Safety net
Cropping Agropastoralist Pastoralist
Other improved water source Piped water from public tap
Source: World Bank calculations based on the merged 2010 LIU livelihoods database with 2007 Census - http://foodeconomy
.com/wp-content/uploads/2016/02/Atlas-Final-Web-Version-6_14.pdf.
Note: Data in figure show that PSNP-targeted woredas have higher coverage than non-PSNP woredas in agrarian areas but not
pastoralist areas. PSNP = Productive Safety Nets Program.
Maintaining the Momentum while Addressing Service Quality and Equity 39
population density woredas (>300 people per square kilometer). Although these areas
have difficult hydrology (HI=2), they are served by relatively high levels of piped water
schemes (41 percent piped of 61 percent improved), indicating that they have received
attention from the regional water bureaus (Oromia and SNNPR) and their development
partners to overcome the difficult hydrogeology through multi-village piped schemes.
While the PSNP is associated with higher rates of access to improved water supply in agrarian
cropping woredas, this is not the case in pastoralist and agropastoralist woredas. Across
Ethiopia, woredas targeted by the PSNP reported significantly higher levels of access to
improved water than those not targeted. However, further analysis reveal that these differences
are only significant across agrarian cropping woredas but not across pastoralist and
agropastoralist woredas. Pastoralist and agropastoralist woredas targeted by the PSNP do not
have better access to improved water, quite possibly because compex hydrogeology is a barrier
not overcome with the funding available through the program. Yet, even where hydrogeology is
complex in agrarian woredas, GoE and development partners manage to overcome these
difficulties through the design and implementation of piped schemes, but this is less evident
in pastoralist and agropastoralist areas.6
Within agrarian areas local variations in access to improved water supplies may reflect
interactions between topography, hydrogeology, and accessibility. Some less poor rural areas
with low improved water coverage have invested in self-supply. These are remote, low population
density areas with agrarian production systems that generate a surplus, such as the western
enset growing areas of SNNPR or lower density sorghum growing areas of Amhara. In these
areas where the hydrogeology is relatively easy, large numbers of households have hand-dug
their own unimproved wells.
Many areas worst affected by the El Niño triggered drought of 2015-16 were already known as
seasonally vulnerable because of a combination of technical and physical constraints. They are
areas with few springs and little or no shallow groundwater for dug wells, and they are difficult
or impossible to reach with truck-mounted drilling rigs for accessing deeper groundwater. Such
areas fall between the cracks of service delivery modalities: they are unsuitable for basic
spring development and dug wells, and too difficult and expensive to reach with drilled shallow
wells and deeper boreholes.
Access Disparities by Service Qualities along the Service
Delivery and Results Chain
Sustainable Development Goal (SDG) Target 6.1 relates to drinking water: “By 2030, achieve
universal and equitable access to safe and affordable drinking water for all.” It aims to achieve
universal access, rather than just halving the proportion of the population without access.
Next, it calls for equitable access, which implies reducing inequalities in service levels between
population subgroups. Finally, it specifies that drinking water should be safe, affordable, and
accessible to all. To meet the threshold for a safely managed service, the improved source
must meet three conditions:
•• Accessibility: the source should be located on premises (within the dwelling, yard, or plot).
•• Availability: water should be available when needed.
•• Quality: water supplied should be free from fecal and priority chemical contamination.
If any of the three conditions are not met, but the improved source is within 30 minutes of the
home, it will continue to be categorized as a basic service.
This section examines these service qualities along the service delivery and results
chain: (a) time to source; (b) water availability; (c) quality of water; and (d) diarrhea and
40 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 4.13: Service Quality along Results Chain between T60 and B40 Households in Ethiopia, 2016
Treatment of
Time to source water Stunting in children
65% Availability of Quality of water 16% Diarrhea in children under five years old
Top 60% <= 30min water at source under five years old 43%
88% 9% low risk 11%
The larger the disparity the further apart
Availability of Quality of water
Bottom 40% Time to source water at source Diarrhea in children
59% 88% 9% low risk under five years old Stunting in children
Treatment of
<= 30min 13% under five years old
water
37%
6%
Sources: Time to source, DHS 2016; availability of water, ESS 2016; quality of water, ESS 2016; water treatment, DHS 2016; diarrhea and stunting, DHS 2016.
Note: B40 = bottom 40 percent of the wealth index; T60 = top 60 percent of the wealth index.
malnutrition outcomes. This is done for both the top 60 percent (T60) and the bottom 40
percent (B40) of the wealth distribution (figure 4.13). The section then presents what this
means for the SDG baseline for the rural water supply subsector.
Accessibility is a criterion for both basic and safely managed drinking water services using
the indicator of time to fetch water (go, queue, collect, and return). The Joint Monitoring
Programme (JMP) uses a travel time indicator for accessibility.7 Households reporting
collection of water from an improved source that is not on premises but takes 30 minutes
or less (for round-trip travel, collection, and queuing) are classified as having basic services,
while those using improved sources that take over 30 minutes are classified as having
limited services.
Between 2000 and 2011 the proportion of households collecting water within 30 minutes
dropped from 65 percent to 57 percent. This is because in 2011 a greater proportion of
households collected water from more distant improved sources than from closer unprotected
sources (see figure 4.14). Only by 2016 did the proportion of people able to fetch water within
half an hour return to the 2000 level (figure 4.14). So while 35 million people gained access
to improved water sources from 2000–16, the number of people able to collect water in less
than 30 minutes increased only by around 15 million people.
Though women-headed households (47 percent) have slightly better access to water than
male-headed (44 percent) households in rural areas, women (71 percent) and female children
(15 percent) bear the burden of fetching water. The only exception to this is in the Somali
region where in 30 percent of households men were the primary fetchers of water. This is
maybe attributable to the median time to source being two hours compared to 30 minutes or
less in other regions. However in Afar, which had a median time of two hours to fetch water, the
burden fell to women in 80 percent of households.
Availability and sufficiency of water. Availability is an important criterion for assessing drinking
water service levels.8 In the Ethiopia Socioeconomic Survey-Water Quality Testing Component
(ESS-WQT 2016) water quality module, two questions were asked about availability and
sufficiency of water:
1. In the past two weeks, was the water from this source not available for at least one full day?
2. Has there been any time in the last month when you did not have water in sufficient
quantities?
If the answer to the second question was yes, the respondent was asked the main reason that
he or she did not have water in sufficient quantities.
Maintaining the Momentum while Addressing Service Quality and Equity 41
Figure 4.14: Households Able to Fetch Water within 30 Minutes in Ethiopia, 2000–16
70
60
50
Households (%)
40
30
20
10
0
30 60 30 60 30 60
2000 2011 2016
Improved Unimproved Surface
Sources: DHS 2000, 2011, and 2016.
Note: Data show changing composition of sources over time.
Across all rural areas, at the time of this survey, households reported that water was
available (88 percent) and sufficient (83 percent) most of the time. There was variation
across source types: piped water from stand posts (66 percent) was less frequently
available than that from protected wells (93 percent) or protected springs (96 percent).
Rainwater collection systems used almost exclusively in Somali region—cisterns or
berkhads—were the least reliable with nearly 60 percent of households using them
reporting that water in the past two weeks had not been available from these sources.
However, in rural areas, availability and sufficiency become critical in seasonal or chronic
drought. Detailed water audits conducted along a highland–lowland transect in eastern
Oromia highlighted the problem of seasonality, very low levels of water use, and the
importance of wealth in shaping service levels (Coulter et al, 2010; Tucker et al. 2014).
Very few households in any livelihood zone exceeded the domestic (drinking, cooking,
personal hygiene, laundry) water requirements recommended by the Sphere project (Sphere
Project, 2011) for humanitarian emergency situations (7.5–15 liters per capita per day), let
alone reached the levels recommended for nonemergency situations. The majority of
households used 8–12 liters per capita per day, levels that present a high level of health
concern (Howard and Bartram 2003). Moreover, poorer households consistently used less
water than their better-off counterparts, particularly for hygiene, and especially in the dry
season.
The drought associated with the current El Niño cycle has also raised questions around the
resilience of services and their underlying functionality. By April 2016, the peak of the El
Niño drought, the GoE reported that around 10 million people across six regions were in
need of emergency assistance; of these around 6 million (in over 160 priority woredas)
were affected by acute water shortages (Howard et al 2016). Real-time monitoring of water
access conducted by World Vision and Oxfam from January to March 2016 revealed that
in January, at the start of monitoring, 85 percent of hand-dug wells had failed completely
(box 4.2). A key response has been water point rehabilitation, suggesting that the drought
exacerbated—or drew attention to—long standing problems of repair and maintenance
(UNICEF 2016).
42 Maintaining the Momentum while Addressing Service Quality and Equity
Box 4.2: Lessons from the El Niño Drought
The El Niño–triggered drought of 2015–16 was one of the worst in decades. In June 2015, the
GoE declared the failure of the spring (belg) rains. This affected smallholder farmers and
pastoralists in the northeastern rangelands of Afar and northern Somali region. Weak and
erratic summer (meher) rains then tipped many pastoralists and meher-dependent farmers
into crisis. By April 2016, the GoE reported that 10.2 million people in six regions needed
Hand pump water supply point for Aboakokit School and local community, Aboakokit Kebele, Fogera Woreda,
Amhara Region.
© Chris Terry/World Bank
box continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 43
Box 4.2: Continued
emergency assistance, from which 5.8 million people were affected by acute water shortages
in 166 woredas. Following a WASH Gap Analysis led by the United Nations Children’s Fund
(UNICEF) and the Ministry of Water, Irrigation and Electricity (MoWIE), the population in need
of emergency water supply, sanitation, and hygiene (WASH) interventions quickly rose to
8.9 million people across 223 woredas.
Piecing together WASH impacts and responses is difficult. Assessments have been periodically
updated, but the criteria and methods used to assess WASH-related problems have evolved
over time. What seems clear is the scale of the drought-related WASH problem took government
and its development partners by surprise, and major arguments broke out about data on the
number of water points that were drying out and about how best to respond.
In January 2015, the GoE sanctioned a real-time monitoring program designed to improve the
timeliness and accuracy of WASH reporting across six drought-affected regions: Afar, Amhara,
Oromia, Southern Nations, Nationalities, and People Region, Somali, and Tigray. Supported by
UNICEF, Oxfam, and World Vision, teams of enumerators collected data on the functionality of
water points, consumption levels, and the time and distance for water collection. Results for
phase 1 (January to March 2015) indicated that 40 percent of improved sources had failed
completely; 85 percent of dug wells had failed; 45 percent of respondents were using less
than 5 liters per capita per day; and 66 percent of households were spending over one hour
per day collecting water—in some cases walking up to 10 hours per day. A planned phase 2
of the monitoring work was cancelled by the GoE.
Data have not been officially published but are widely reported in summary form. What
they reveal is, first, there were major problems with the underlying functionality and
performance of systems, predrought. Second, they appear to show that dug wells were
particularly vulnerable. However, the widespread failure of wells could be attributed, in
part, to underlying problems of poor siting, construction, and maintenance. Following the
El Niño drought, below average rains in the south and east of the country caused by the
negative Indian Ocean Dipole have now left 5.6 million people in need of emergency
humanitarian assistance.
Sources: UNICEF 2016; key informant interviews 2016.
Quality of water at source. To be considered safe, drinking water must be free from
pathogens and elevated levels of harmful substances at all times. The highest priority
water quality parameter globally, and in most countries, is contamination of drinking water
with fecal matter.9 The ESS-WQT 2016 is the first large-scale water quality testing to have
been carried out in Ethiopia. The survey tested two samples for E. coli: one at the point of
collection, and one directly from a glass used for drinking. At point of source 4,513 valid
tests were conducted (see appendix D for methods and more detailed results).
Though there was little variation across wealth or geography over nine out 10 rural samples
tested positive for E. coli, and nearly seven out of 10 samples were classified as high (11–100
colony-forming units per 100 milliliters) or very high risk (>100 colony-forming units per
44 Maintaining the Momentum while Addressing Service Quality and Equity
100 milliliters). E. coli was detected across all source types in rural areas. Protected wells
(99 percent) and springs (93 percent) were equally at risk of fecal contamination as unprotected
sources (95 percent). Only boreholes (87 percent) and stand posts (80 percent) were marginally
lower in the proportion of sources in which E. coli was detected and in the overall level of risk
from fecal contamination (see figure 4.15 and figure 4.16).
Figure 4.15: E. Coli Risk Levels at Point of Collection by Rural Water Supply Type in
Ethiopia, 2016
100
90
80
70
60
Percent
50
40
30
20
10
0
ta r
e
g
w d
rin d
w d
ct ter
er
ic te
ol
rin
g te
sp cte
g te
at
bl wa
lle a
p
l
g
l
n
eh
el
el
du tec
du tec
sp
co ainw
w
io
te
or
pu ed
ce
o
ro
ro
d
l/b
Pr
te
np
np
R
rfa
p
el
Pi
ec
U
U
Su
w
ot
be
Pr
Tu
Water supply source
E. coli >100 E. coli 11–100 E. coli 1–10 E. coli <1
Sources: ESS 2016 Water Quality Survey.
Figure 4.16: Main Source of Household Drinking Water by Type in Ethiopia, 2016
30
25
25
20
20
Percent
15 13 14 13
10
7
5
5
1
0
ho r
rin d
l
rin d
l
r
ce
ip /
el
el
dp tap
re ll o
e
sp cte
sp cte
at
w
w
fa
le
g
g
e
bo we
w
r
e
d
te
d
an c
Su
in
ot
st bli
te
e
ro
be
ct
Ra
Pr
ec
Pu
np
te
Tu
ot
ro
U
Pr
np
U
Water supply source
Sources: DHS 2016.
Maintaining the Momentum while Addressing Service Quality and Equity 45
Previous, smaller water quality surveys reported lower levels of contamination but lacked the
scale and representativeness of the ESS. There have been a number of small-scale water
quality surveys (e.g., Kebede et al. 2017) but only one other water quality survey carried out at
any scale across Ethiopia (WHO 2010). This survey, called the Rapid Assessment of Drinking-
Water Quality (RADWQ) was carried out in 2004–05 across 1,602 households. Though it is
representative of improved types of water supply used in the country, it does not report
separately on urban and rural areas. The RADWQ survey reports lower average levels of
microbiological contamination than the ESS survey. Thermotolerant coliforms were detected in
32 percent of borehole samples, 45 percent of protected dug wells, and 56 percent of protected
springs. For some regions and types of source, however, such as protected springs in SNNPR,
thermotolerant coliforms were detected in 79 percent of the samples. The ESS’s larger scale,
enabling a greater reach into rural areas, and its stratified sample design, enabling disaggregated
reporting for urban and rural areas, may account for the higher levels of microbiological
contamination reported.
Treatment of water. Though the ESS-WQT 2016 reports some improvement to water quality
at point of use when treated, only 5 percent of rural households treated water. The DHS
2011 and 2016 report slightly higher rates of treatment in rural areas at around 8 percent.
The main methods households used were chlorinating (5 percent) and boiling water
(2 percent).
Households that reported treated water at the household level were more likely to see a
decrease in E. coli levels (19 percent) than households that did not report treatment
(10 percent). Water treatment is one of the few variables in the service delivery chain that
shows variation across wealth quintiles with households in the T60 (16 percent) more
likely to treat water than households in the B40 (6 percent). However, given the very low
levels of water treatment in rural areas, this does not appear to be a significant contributor
to a divide in health outcomes.
Implications of Service Quality on the SDG Baseline
Though there is little differentiation by wealth the level of service available to Ethiopia’s
rural population is very low: an SDG baseline of just 5 percent of people having access to
safely managed drinking water. Across the service delivery and results chain, the main
finding relating to wealth is that there is very little differentiation whether by (a) time to
source; (b) water availability; (c) quality of water at source; (d) diarrhea; or (e) malnutrition.
The only small difference is in water treatment, but the overall levels of treatment are so
low that these are unlikely to influence outcomes. Rather, the analysis of links along the
chain highlights that both poorer and wealthier households face an equally low level of
service with (a) limited time saving being realized; (b) seasonal and drought risks to
availability and sufficiency; (c) poor water quality; and (d) very low levels of point of use
treatment. With failures throughout the service delivery chain, current rural service levels
are unlikely to deliver on the health, let alone the putative economic benefits, of rural water
supply interventions.
The SDG baseline for safely managed rural drinking water is just 5 percent determined by
the lowest element of the three conditions of (a) accessibility (the source should be
located on premises within the dwelling, yard or plot); (b) availability (water from an
improved source should be available when needed); and (c) quality (water supplied should
be free from fecal and priority chemical contamination). Even if there were higher levels
of water on premises, the quality of water would be the next element to determine the
baseline.
The SDG baseline for a basic service of rural water supply is 26 percent (see figure 4.17). This
is where the three conditions of safely managed are not met, but the improved source is within
30 minutes of the home.
46 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 4.17: Estimates of Safely Managed Rural Drinking Water in Rural Ethiopia,
2016—SDG Methodology
SDG ladder
100
Elements of safely managed 14
80
30
60
Percent
56
46
40 30
20 26
21
5 7 5
0
Improved Improved within Improved Improved Improved Safely managed
30 minutes on available free of drinking water
roundtrip premises when needed contamination services
Surface water Unimproved Limted service Basic serivce Safety managed
Source: ESS-WQT 2016.
Note: SDG = Sustainable Development Goal.
However, neither of these definitions for safely managed or basic services deal with a final
condition of the SDG: affordability. The following section examines affordability exploring some
of challenges that there would be in expanding access to piped water.
Implications of a Shift Toward Piped Water
Supply on Affordability
While expenditure on nonpiped sources is very low the expenditure on piped water and water
from vendors rises sharply across consumption quintiles (see figure 4.18). The 2011 Household
Income and Consumption Economic Survey (HICES) collected expenditure data on both food
and essential nonfood items, including water. In rural areas the survey reports average actual
expenditure on water to be Br 62 per person per year (US$3.7), equating to an implied
subsector turnover of US$230 million in 2011.
This pattern of expenditure is reflected in a much smaller survey of tariffs across 100
schemes in Ethiopia conducted for the 2009 Ethiopia PER. The results of this small survey
help explain this pattern. First, only 55 of the schemes have instituted a regular tariff (i.e.,
a user payment per bucket, monthly, or annual), 45 of which also have a maintenance fund.
Water tariffs are extremely low except for motorized piped schemes in which tariffs average
just under Br 0.5 per 20 liters. Motorized piped schemes use diesel engines to pump
water from boreholes, usually to an overhead tank, from which water is distributed to stand
posts. These schemes have high operational costs since they have to buy diesel regularly
for water pumping.
Maintaining the Momentum while Addressing Service Quality and Equity 47
Figure 4.18: Average Total Consumption per Person per Year in Ethiopia, 2011
140
120
Ethiopian Br (millions)
100
80
60
40
20
0
Poorest Poorer Middle Richer Richest
Nonpiped improved sources Public stand post Private vended water
Source: HICES 2011.
Note: “Consumption per person” refers to adult equivalent.
Table 4.1: Average Tariff by Scheme Type and Payment Method
Tariff (Br)
Source/scheme type Pay annually Pay monthly Pay per bucket
Protected spring n.a. 0.71 n.a.
Hand-dug well 11.00 1.15 n.a.
Shallow borehole 6.00 1.31 0.07
Spring with piped distribution n.a. 10.00 0.10
Motorized deep borehole with n.a. n.a. 0.47
piped distribution
Source: PER 2009.
Note: n.a. = not applicable.
At the equivalent of Br 25 per cubic meter, the tariff for these rural motorized schemes is over
five times the average urban tariff per cubic meter and 25 times the lowest urban tariff bands
(see figure 4.19). Consuming just 20 liters per person per day would be equivalent to just
under Br 200 per person per year, which is more than the 5 percent affordability threshold
commonly used to gauge affordability. Many of these motorized piped schemes are in pastoralist
and ago-pastoralist lowland areas.
Another small-scale study of water use conducted in Shinile woreda in Somali region and
Konso woreda in SNNPR (Dessalegn et al. 2013) reports that the poorest households are
most severely affected by the high costs of rural water. They have the least labor to release,
the fewest assets to collect and store water, and the least cash to pay for it. They are also more
likely to forego income-generating activities in favor of water collection, and more likely to see
the condition of their livestock deteriorate because of constrained water access. The study
reveals that water fees also affect access, particularly for poorer households.
48 Maintaining the Momentum while Addressing Service Quality and Equity
In view of the shift envisaged to more complex piped schemes under GTP II, the affordability of
water services and cost-sharing arrangements will need to be examined carefully. Evidence
from national surveys, smaller studies, and the case study (box 4.3) suggest that affordability
of rural water from piped schemes, particularly motorized piped schemes, can be a real barrier
for poorer households to access and explains the skewed distribution of access to piped water
in rural areas. In circumstances of shocks such as the poor harvests from recent drought
events, the cost of water can have a profound effect on availability of cash income and on rural
indebtedness.10
Figure 4.19: Trends in Access to Rural Sanitation
100
80
60
Percent
40
20
0
2000 2005 2011 2016
Ethiopia, 2000–16
Improved Unimproved Open defecation
Source: DHS, 200, 2005, 2011 & 2016.
Box 4.3: Poor Households Receiving Safety-Net Funding from PSNP Excluded
from Access to Improved Piped Water
Mareko is a food insecure woreda in the Gurage zone of SNNPR that benefits from the PSNP.
Ilala Gebiba Kebele in Mareko woreda has a motorized scheme that lifts water from a well at
a depth of 270 meters. About six years ago the diesel generator used drive the water pump
was replaced with electric- powered engine to reduce the cost of water production. Water is
sold at Br 0.25 for a jerry can. Households also contribute Br 100 annually to cover
maintenance costs. Households that cannot pay are excluded from accessing the piped
water scheme.
box continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 49
Box 4.3: Continued
Ansade Seid, Ilala Gebiba Kebele in Mareko Woreda, SNNPR.
© Chris Terry/World Bank
While the borehole and one of its distribution points is within 200-meter distance to Ansade Seid,
a mother of five, and to Shumba Bukeri a mother of three, both families cannot afford to use
water from this source. Until last year Ansade bought water from the piped scheme at Br 0.15
per jerry can, but both Ansade and Shumba now collect water from a muddy pond close to their
house, which is also used for animal watering. They use this water for both cooking and drinking
purposes. At times they boil the water and filter it through a cloth for drinking. Ansade adds
cement powder, which she takes form her workplace, to help settle the sediment in the water.
box continues next page
50 Maintaining the Momentum while Addressing Service Quality and Equity
Box 4.3: Continued
Shumba Bukeri, Ilala Gebiba Kebele in Mareko Woreda, SNNPR.
© Chris Terry/World Bank
, receiving Br 710 per month for four months of the
Both families are beneficiaries of the PSNP
year, until the beginning of the rainy season. The children of both families also benefit from
feeding program at the local school. During the rainy seasons, the husbands are able to get
work laboring on other peoples’ farms while both Ansade and Shambu look after cattle for
payment of basic needs (feeding, watering, and provision of shelter). Their income barely
meets the family’s monthly need for food, and even though they receive the PSNP support they
are unable to buy water from the improved piped water source. It is not due to lack of awareness
about the benefits of clean water. It is simply that buying food is prioritized over buying water.
WASH committee members evaluating Asnade’s and Shambu’s situation agreed to consider
their case with some agreeing to enable them to receive one jerry can of water for each
household per day free of charge. But since water sold is metered, providing water free of
charge requires a special arrangement.
Source: Yemane and Defere n.d.
Maintaining the Momentum while Addressing Service Quality and Equity 51
Model latrine of Asersash Melese, 1-5 Leader, Ayjaseta Kebele in Fegeta Lakoma Woreda, Amhara Region.
© Chris Terry/World Bank
52 Maintaining the Momentum while Addressing Service Quality and Equity
Rural Sanitation Subsector Analysis
National Status and Trends
Improvements in access to sanitation in rural Ethiopia has benefited from the transformative
approach to the delivery of basic health care services implemented by the government. MoH’s
flagship Health Extension Program (HEP) operates with the premise that access and quality of
primary health care for communities can be improved through the transfer of health knowledge
and skills to households. This focused approach based on behaviorial change aligns with
emerging thinking within the rural sanitation subsector and with the government’s policy of zero
hardware subsidies for household latrines.
The training and deployment of health extension workers (HEWs) at the kebele level through
the HEP has provided a mechanism to promote sanitation and hygiene behaviors and adoption
of low-cost latrine technologies at scale. The HEP is structured around packages of health
messages delivered by around 38,000 HEWs. These packages are organized around 16
thematic areas, of which seven relate to sanitation and hygiene behaviors. Despite the financing
challenges of the HEP and scale of the tasks expected from the HEWs, including modules in
the HEP packages on ways to change sanitation and hygiene behaviors have provided the basis
for notable progress in latrine coverage. Regional health bureaus and woreda health offices
have harnessed the HEP and outreach of the HEWs to significantly improve the sanitation
situation in rural areas after 2000.
Clear GoE strategies, high level of political commitments for improving sanitation, and the
empowerment of regional bodies through an ongoing decentralization process have created a
conducive enabling environment for sanitation and hygiene promotion and service delivery. In
2005 the MoH’s National Hygiene and Sanitation Strategy (NHSS) focused on three main
areas: (a) safely manage excreta; (b) safe water chain from a source to point of use; and
(c) hand washing with soap after defecation. This was followed in 2006 by the Universal
Access Plan (UAP), which targeted 100 percent sanitation coverage.11 The development of the
NHSS Strategic Action Plan (2011), supported by the National Community-Led Total Sanitation
and Hygiene (CLTSH) Guideline, the National Sanitation Marketing Guidelines, and other
protocols, belatedly provided the tools and methodologies to guide implementation.
Ethiopia was recognized in the 2015 JMP report (UNICEF/WHO 2015) as having achieved
the largest global decrease in the proportion of the population practicing open defecation.12
In 2000, the DHS recorded that open defecation13 rate (those households without access
to a latrine) in rural areas was at 92 percent. By 2016 Ethiopia reduced the proportion of
the population practicing open defecation to 39.1 percent, which is an average reduction
of over 3.5 percent per year since 2000. It should however be noted that progress has
slowed in recent years, with a reduction of only just over 1 percent per year between 2012
and 2016.
While the reduction in open defecation has resulted in the uptake of latrines, most latrines
built in rural areas are unimproved.14 The 2016 DHS reports access to unimproved latrines
in rural areas was 52.5 percent, compared to just 5.7 percent of households with improved
latrines15. The progress in reducing open defecation is commendable; however, the
significant number of unimproved latrines raises questions over the public health impact
of this change. While unimproved latrines can increase convenience and dignity for
individuals, they are less likely to safely remove feces from the environment and not result
in the expected health benefits. While data on latrine use remain limited, studies show
that behavior change is less likely to be sustained by users of unimproved latrine due to
the less pleasurable experience and the cost of maintaining less robust infrastructure. In
part this slippage could explain the slowdown in reduction of open defecation in recent
years, as household return to open defecation practices.
Maintaining the Momentum while Addressing Service Quality and Equity 53
Box 4.4: Health Extension Workers Support Improvement in Sanitation
Abakokit Keble (Faguta woreda in South Gonder zone) is an example of success in the woreda.
After following the initial engagement of the HEWs on sanitation and hygiene promotion, it
achieved 100 percent latrine coverage. However, the communities’ initial response to CLTSH
was latrinization, with little focus to quality and sustained use. The poor quality latrines and
person behavior have been test by annual rain that bring flooding to the areas. Most latrines
are destroyed each year, and residents are now fed up with annually rebuilding their latrines,
resulting in latrine coverage of only 5.2 percent.
The HEWs engaged the communities in the kebele to achieve open-defecation-free status, and
provided some technical support on how to build traditional pit latrines. However, the HEWs’
capacity to provide technical support was inadequate when it came to building improved pit
latrines with a cleanable floor and wall ensuring privacy. In fact, in the case of Abakokit, the
demand is beyond just improved latrine but for more sustainable latrine technologies suitable
for areas prone to water-logging. The HEWs struggled to meet the community’s needs, and are
in a vicious circle in which they continue to promote the same hygiene and sanitation messages
with decreasing success. As a result, the HEWs, who have many other tasks assigned to
them, shift their focus to other areas in which progress is more realistic. As a result, Abakokit’s
family and other families have returned to open defecation.
Although this is a single case, in general, HEWs have focused on promoting latrine construction
and have done less to promote safe excreta disposal and sustained use of latrines. Unless a
clear strategy for hygiene promotion focuses on sustained use of latrines, along with means
to support households to climb up the sanitation ladder, the trend of communities reverting
back to open defecation will continue.
Source: Yemane and Defere n.d.
The low uptake of improved latrines in rural areas are driven by both demand and supply
factors. From the demand side, there is a strong emphasis on households stopping open
defecation and building basic latrines. HEWs often lack knowledge of the importance of building
a hygienic latrine, and therefore provide communities with limited information on why they
should invest in an improved latrine or how to build one. This is compounded by supply-side
factors: most communities lack someone with the knowledge and skills to construct an
improved latrine, and products to support this construction are not available in the local market.
Where products and services are available they are often not affordable or above a price
households are willing to pay, due to individuals’ lack of knowledge of the importance of
investing in a latrine. There are also limited microfinance products available to support
households build latrines.
Access Disparities by Geography and Livelihoods
Significant variation in the sanitation coverage can be observed among rural populations in
different regions (figure 4.20). The most significant disparity is in open defecation rates, which
range from 18 percent to 85 percent. The regional variation between improved sanitation rates
are less significant, ranging from 1.2 percent to 22.7 percent.
54 Maintaining the Momentum while Addressing Service Quality and Equity
The four large (and predominately agrarian) regions have achieved the most significant
reduction in open defection, dropping from 94 percent to 42 percent between 2000 and 2016
(figure 4.21). The open defecation reduced by 48 percent in the chartered cities, similar to
the large regions during the same period. Despite open defecation in the emerging regions
being lower in 2000 than the other regions, progress has been slowest during the period,
reducing from 82 percent to 56 percent.
Figure 4.20: Rural Sanitation Coverage by Region in Ethiopia, 2016
100
80
60
Percent
40
20
0
l
PR
ia
i
ra
la
a
ay
i
r
gu
ar
al
fa
w
m
be
ha
m
gr
ar
Af
N
da
an
ro
So
am
SN
H
Am
Ti
sh
O
ire
G
ni
D
Be
Sanitation coverage
Improved Unimproved Open defecation
Source: DHS 2016.
Note: SNNPR = Southern Nations, Nationalities, and People Region.
Figure 4.21: Rural Sanitation Coverage Trends in Large Regions, Emerging Regions,
and Chartered Cities in Ethiopia, 2000 and 2016
100
90
80
70
60
Percent
50
40
30
20
10
0
2000 2016 2000 2016 2000 2016
Large regions Emerging regions Chartered cities
Improved Unimproved Open defecation
Source: DHS, 2016.
Maintaining the Momentum while Addressing Service Quality and Equity 55
Figure 4.22: Rural Sanitation Coverage Trends by Regions in Ethiopia, 2000–16
70
50
30
Percent
10
–10
–30
–50
–70
PR
ra
ia
ul
i
a
y
i
a
r
ar
al
fa
a
w
l
m
ng
be
ha
m
gr
ar
Af
N
da
ro
So
a
am
SN
Am
H
Ti
O
sh
ire
G
ni
D
Be
Improved Unimproved Open defecation
Note: SNNPR = Southern Nations, Nationalities, and People Region.
While Afar has the lowest percentage of improved latrine, emerging regions (such as Somali
and Gambella) and the chartered cities have some of the highest percentages of improved
latrines. When regional trends in sanitation coverage are analyzed (see figure 4.22) the large
regions (except for Tigray) have achieved the largest percentage growth in unimproved latrines.
Emerging regions, on the other hand, have translated more modest reductions in open
defecation into greater proportionate increases in improved latrines.
These regional trends can be best explained by the effectiveness of HEP in the regions and
the different approaches that have been promoted. It is clear that HEP has been most
effectively delivered in the large regions and Benishangul-Gumuz. This is because of the
greater capacity of the local government structures and the increased level of financial and
technical support provided by development partners in these regions. The fact that SNNPR
has the lowest levels of open defecation among its rural population can be primarily attributed
to the strong political leadership of Dr. Shiferaw Teklemariam.16 Dr. Teklemariam placed
sanitation high up on his agenda for change, and as a result woreda and kebele health offices
and HEWs dedicated significant time to promoting improvement in sanitation, over and above
other interventions.
The predominant approach promoted by HEWs and development partners in the large regions
has been the CLTSH approach, which emphasizes collective community action to eradicate
open defecation. Because the approach does not provide subsidies for hardware construction
(in line with the national policy), less focus has been placed on the construction of higher
quality (improved) latrines. Poor access to sanitation products in rural areas, due to weak
supply chains, has further compounded the challenge of constructing an improved latrine, with
most rural communities relying on local materials.
There are several explanations for the higher levels of improved latrines in the emerging
regions. The first is that the promotion of the CLTSH approach has not been prevalent in the
emerging regions. While Gambella, Afar, and Somali have high levels of open defecation, the
distribution of subsidized hardware through humanitarian programs have resulted in some of
the highest rates of improved latrines. In addition, the rural populations of the city states of
Dire Dawa and Harari reside close to these large urban centers, providing them increased
access to local markets and affordable sanitation products, which has enabled the construction
of improved latrines.
56 Maintaining the Momentum while Addressing Service Quality and Equity
These differences in coverage and characteristics of coverage also play out within regions. The
2007 Housing and Population Census data have been used to undertake woreda-level
intraregional analysis, while this data are slightly outdated, they provide0 a good indication of
some intraregional trends (see maps 4.4 and 4.5). Woredas with higher level of improved
sanitation coverage tend to also have lower levels of open defecation. The woreda analysis
further confirms the report of the higher coverage in SNNPR, but highlights that there are
number of woredas in southwest SNNPR (Bench Maji and South Omo Zones) that have not
made the progress shown in other areas. In addition, the progress in northern SNNPR is part
of a band of progress from east to west: from Central Oromia (Arsi Zone), northern SNNPR,
western Oromia, and southern Benishangul.
Maps 4.4 and 4.5 clearly show woredas in southern Amhara and eastern and southern
Tigray (Misraqawi and Debubawi Tigray Zones) have higher coverage rates compared to
other woredas in the region. This is in part due to the higher level of external financial
and technical support in these areas, and additional donor support in these areas
since the 2007 census has further been exaggerated this trend. In Tigray, these zones
have benefitted from their proximity to regional capital city of Mekelle, which has
resulted in increased donor financing, access to markets, and political attention.
Islands of success in Benishangul-Gumuz and Afar also exist, which warrants further
investigation.
Intraregional variations in sanitation coverage can to some degree be explained by livelihood
types (cropping, agropastoralist, and pastoralist) (figure 4.23a), and production systems (cash
crops, food crop, crop sales, and livestock) (figure 4.23b). There is significantly higher rates of
open defecation in woredas with livelihood types classified as mostly pastoralist and
agropastoralist, compared to those classified as cropping. There appears to be a systematic
failure to improve sanitation coverage in pastrolist communities, as with the issues regarding
improved water supply.
Map 4.4: Open Defecation Rates in Ethiopia, 2007 Map 4.5: Improved Sanitation Coverage in Ethiopia, 2007
Tigray Tigray
Afar Afar
Amhara Amhara
Benishangul Benishangul
Gumuz Gumuz
Dire Dawa Dire Dawa
Addis Ababa Addis Ababa
Harari Harari
Gambella Oromia Gambella Oromia
Somali Somali
SNNPR SNNPR
Rate (%) Rate (%)
81–100 0–10
61–80 11–20
41–60 21–30
21–40 31–40
4–20 41–68
Source: Housing and Population Census, 2007. Source: Housing and Population Census 2007.
Note: SNNPR = Southern Nations, Nationalities, and People Region. Note: SNNPR = Southern Nations, Nationalities, and People Region.
Maintaining the Momentum while Addressing Service Quality and Equity 57
Figure 4.23: Open Defecation Rates in Ethiopia, by Livelihood Type and Production System, 2007
a. Livelihood b. Production system
100 100
80 80
60 60
Percent
Percent
40 40
20 20
0 0
Cropping Agropastoralist Pastoralist Cash crop Food crop Crop sales Livestock
Source: Population and Housing Census 2007.
Those living in woredas in which cropping, specifically cash cropping, is most prevelant have
the lowest levels of open defecation. However, there appears to be lower open defecation rates
in areas where households consume over half the food they produce, so-called “food crop”
woredas, compared to areas of crop sales. This seems counterintuitive, and unlike water
supply, cannot be explained by the safety nets program (PSNP), since open defecation is
11 percentage points higher in PSNP woredas on average.
Differences in open defecation rates can be observed between pastoralist and cropping
woredas, which further confirms the systematic challenges of addressing sanitation coverage
among these groups even within the regions. Fewer differences are observed between
pastoralist and agropastoralist woredas in Somali and Oromia; however, there is a significant
gap between pastoralist and agropastoralist woredas in Afar (figure 4.24). The most striking
difference is in SNNPR and Gambella where agropastoralist woredas have a significantly higher
level of open defecation than cropping woredas (see box 4.5).
Despite emerging regions’ coverage lagging behind that of the large regions, most people who
lack access to adequate sanitation reside in the large regions (see figure B4.5.1a). Of the total
number of people who still defecate in the open in rural areas 86 percent are in Oromia,
SNNPR, and Amhara; those areas are also home to 94 percent of households with unimproved
latrines. Oromia contains 45 percent of the rural population still practicing open defecation,
many of whom live within pastoralist communities (see figure B4.5.1b).
To bring all the regions to a similar proportionate level of coverage, there is a clear argument
to focus investment in the emerging regions to address the gaps in coverage they are
experiencing compared to the large regions. However, there are just over 2 million people who
openly defecate in the emerging regions, compared to over 25 million in the large regions. To
achieve universal access to sanitation facilities, considerable focus needs to be made on the
large regions. The following section looks at the relationship between poverty and sanitation
coverage in rural areas, and identifies coverage levels among the poorest woreda to further
guide choices concerning the targeting of investment.
58 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 4.24: Open Defecation Rates by Livelihood Type and Region in Ethiopia, 2007
100
Open defecation rates (%)
80
60
40
20
0
ra
G uz l
lla
a
i
ay
ar
lla
a
PR
i
ar
a
i
PR
um u
al
al
al
iy
iy
iy
G ng
ha
Af
Af
be
m
be
m
m
gr
m
m
N
m
N
So
So
So
ha
Am
Ti
SN
SN
ro
ro
ro
am
am
O
O
O
is
G
n
Be
Cropping Agropastoralist Pastoralist
Livelihood type and region
Source: Population and Housing Census 2007.
Note: SNNPR = Southern Nations, Nationalities, and People Region.
Box 4.5: Challenge of Sustaining Sanitation Improvements in SNNPR
Digna Koisha Humbo kebeles in Digna Fango woredas (Wolaita Zone, SNNPR0) is one of the
. While the
poorest woredas in the area with most of its residents benefiting from the PSNP
kebele once reported 100 percent latrine coverage, most latrines are now dysfunctional,
requiring maintenance and renovation. Muntashe Chinkla is a 70-year-old mother of five
daughters and a son, whose once functional latrine now requires rebuilding and sits unused.
She lives with three of her school-aged daughters, and the household’s only source of income
is the agricultural product they sell from their smallholding.
Chinkla buys one jerry can of water per week for drinking purpose at a rate of Br 2.50 per can,
and collects water for other domestic use from traditional sources. Her now dysfunctional
latrine, which her son helped her build, is shared with his family, which places an increased
burden on this failing facility. She realizes her need to improve her latrine but lacks the
resources to hire someone to build a stronger, more permanent structure.
Martha Mathewos has been a HEW for the last nine years, and sees the challenge faced by
many households as their latrines run into despair. As the initial community enthusiasm for
collective action on sanitation wanes, the honeymoon period ends and households return to
open defecation. Mathewos, like other HEWs, lacks the interest and time to continue hygiene
promotion, and although one to five groups were formed as a support system for hygienic
behavior, in practice they have little ability or motivation to improve the situation. Even those
who can afford to improve their latrine are now discouraged to do so, since the collective
box continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 59
Box 4.5: Continued
Muntashe Chinkla, 70 years old. Digna Koisha Humbo Kabele, Digana Fango Woreda, SNNPR.
© Chris Terry/World Bank
decisions made in the past are no longer enforced with the same accountability. The prevalent
poor economic situation and the lack of construction material and skilled labor are other
challenges the households in this kebele must face to either rebuild or improve their latrine.
The dysfunctional and unused latrines scattered across the kebele are a stark reminder to the
community of the once good progress they made in improving the environment of the village.
box continues next page
60 Maintaining the Momentum while Addressing Service Quality and Equity
Box 4.5: Continued
Marta Matthews, Health Extension Worker. Digna Koisha Humbo Kabele, Digana Fango Woreda, SNNPR.
© Chris Terry/World Bank
Source: Yemane and Defere n.d.
box continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 61
Box 4.5: Continued
Figure B4.5.1: Rural Populations in Ethiopia with Unimproved Latrines and Practicing Open
Defecation, by Region, 2016
a. Unimproved latrines b. Open defecation
3% 3%
6%
10%
22%
40%
43% 12%
29% 32%
Oromia SNNPR Amhara Tigray Emerging regions Oromia Amhara SNNPR Tigray Emerging regions
Source: DHS 2016.
Note: SNNPR = Southern Nations, Nationalities, and People Region.
Access Disparities by Wealth and Consumption
Analysis of poverty quintiles using the Welfare Monitoring Survey (WMS), based on
consumption, shows that poverty makes no difference to access to sanitation in rural
areas (see figure 4.25). This data would suggest that the HEP and other strategies used
to create demand for sanitation seems to have been effective for all households irrespective
of poverty levels. However, analysis of DHS data of poverty quintiles, using a wealth index,
shows a difference between rich and poor households in terms of access to sanitation
(see figure 4.26). In the richest quintile open defecation is nearly half that of the poorest
quintile. While the DHS data show inequality of coverage between rich and poor households,
over one-third of the richest 40 percent living in rural areas still defecate in the open and
only 10 percent the richest 40 percent have access to an improved latrine.
The poorest households have the lowest levels of adoption of the three key hygiene behaviors
highlighted in the GoE’s policies and strategies; safe child stool disposal, safe water treatment,
and improved hand washing. There was almost no improved hand washing reported in rural
areas, and low levels of improved child stool disposal (approximately 5 percent for the top
20 percent of the wealth index [T20] and 2 percent for the bottom 20 percent of the wealth
index [B20]) and safe water treatment (approximately 10 percent for the T20 and 2 percent for
the B20; see figure 4.27)
While the association is not that strong, female-headed households have higher rates of open
defecation and lower rates of improved latrines than male-headed households (figure 4.28). Several
factors drive this including access to land, access to skilled labor, and income levels. However, the
data confirm that even if women would prioritize sanitation over and above male counterparts in
decisions on how income were prioritized, other factors constrain them from implementing this.
62 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 4.25: Sanitation Coverage by Rural Consumption Quintile in Ethiopia, 2000–11
100
80
Sanitation coverage (%)
60
40
20
0
Poorest Second Middle Fourth Richest
Rural consumption quintile
Open defecation Other unimproved Shared Improved
Source: WMS 2000–11.
Figure 4.26: Sanitation Coverage by Rural Wealth Quintile in Ethiopia, 2000–11
100
80
Sanitation coverage (%)
60
40
20
0
Poorest Second Middle Fourth Richest
Rural wealth quintile
Open defecation Other unimproved Shared Improved
Source: JMP calculations of DHS 2000–11.
Maintaining the Momentum while Addressing Service Quality and Equity 63
Figure 4.27: Exposure Variables by Economic Level for Rural Populations of Children
under 5 in Ethiopia, 2011
a. Safe child stool disposal b. Safe water treatment c. Improved hand washing
60
Children under 5 (%)
40
20
0 t
er
e
r
st
t
er
e
r
st
t
er
e
r
st
es
es
es
he
he
he
dl
dl
dl
he
he
he
or
or
or
or
or
or
id
id
id
c
c
c
Po
Po
Po
c
c
c
Ri
Ri
Ri
Po
M
Po
M
Po
M
Ri
Ri
Ri
Wealth quintile Wealth quintile Wealth quintile
Source: DHS 2011.
Figure 4.28: Rural Sanitation Coverage–Gender Analysis
100
80
60
Percent
40
20
0
Male-headed households Female-headed households
Improved Unimproved Open defecation
Source: DHS 2016.
Access Disparities by Geography and Poverty
At the national level, there does not appear to be a relationship between relative wealth and
sanitation coverage, however to gain a more detailed insight the maps 4.6 and 4.7 present the
relationship between poverty and open defecation and access to improved latrines at the
woreda level. What is most reveling in this analysis are the extremes, in which there is low
poverty and low coverage or high poverty and high coverage.
Less than 5 percent of people live in an area of low levels of poverty and high levels of
open defecation, and 6 percent with low levels of improved latrine coverage. However,
these woredas fall into three distinct geographic areas (yellow on the map): (a) surrounding
Addis Ababa in the Oromia region; (b) in northern Amhara (North Gondar Zone) and northern
Benishangul-Gumuz (Mektekel Zone); and (c) eastern Somali. The low coverage in the
woredas in northern Amhara and northern Benishangul-Gumuz could partially be explained
64 Maintaining the Momentum while Addressing Service Quality and Equity
Map 4.6: Poverty Relationship to Open Defecation Map 4.7: Poverty Relationship to Improved Latrines
in Ethiopia, 2007 in Ethiopia, 2007
Tigray Tigray
Afar Afar
Amhara Amhara
Benishangul Benishangul
Gumuz Dire Dawa Gumuz Dire Dawa
Addis Ababa Addis Ababa
Harari Harari
Gambella Oromia Gambella Oromia
Somali Somali
SNNPR SNNPR
Open defecation vs poverty rate Improved sanitation vs poverty rate
Low poverty, low open defecation Low poverty, low improved sanitation
Low poverty, high open defecation Low poverty, high improved sanitation
High poverty, low open defecation High poverty, high improved sanitation
High poverty, high open defecation High poverty, low improved sanitation
Medium to either of indicators Medium to either of indicators
Woreda access to improved
Woreda open defecation levels
sanitation
Poverty level <60 60–80 >80 Poverty level <20 20–40 >40
<15 2.8 4.7 <15 6 1
15–30 64.7 15–30 64
>30 13 14.8 >30 26 2
Source: World Bank calculations based on Housing and Population
Census 2007.
Note: SNNPR = Southern Nations, Nationalities and People Region.
by the poor connectivity in the transportation infrastructure and their distance from major
cities. Cultural issues could also play a part in the poor uptake of sanitation facilities. The
woredas in eastern Somali are mostly home to pastoralists with relatively good economic
opportunities. However, their nomadic lifestyle makes it socially and technically challenging
to provide sanitation solutions.
The reasons behind the low sanitation coverage around Addis Ababa are less clear,
considering the relatively high level of road accessibility and proximity to a large urban center,
which offers access to the good and services. This could be explained by the fact that these
areas have more transient populations who move from other regions into the proximity of
Addis Ababa to access employment, and the lack of community felt in these areas. The low
sanitation coverage could be further compounded by the fact that many of the HEWs who
work in these areas are based in Addis Ababa and have less connection with the communities
they serve. It could be concluded that targeting these Oromia woredas might provide an
opportunity for quick results.
Maintaining the Momentum while Addressing Service Quality and Equity 65
As would be expected, there are a very limited number of woredas with high levels of
poverty and high improved sanitation coverage or low open defecation. However, there are
two groups of woredas that fall into this category (blue on the map): (a) central SNNPR;
and (b) southern Benishangul-Gumuz and western Oromia. The woredas in central SNNPR
appear to have benefited from the sustained campaign from the political leaders in SNNPR,
which is a positive message that change can be achieved in a poor area with sustained
political commitment. Southern Benishangul-Gumuz and western Oromia have a long
history of external engagement from civil society and religious groups, which has
complemented the government’s effort to provide services.
There are a substantial percentage of the rural population living in areas of high levels
of poverty and open defecation (14.8 percent) and low coverage of improved latrines
(26 percent), and from an equity perspective those areas should be targeted most urgently.
The largest area that falls into this group is a belt of woredas that cover the south of
Ethiopia across Somali, Oromia, and SNNPR. The high percentage of pastoralists and the
remote location of these woredas contribute to their high poverty levels and the poor
sanitation coverage.
Livelihood type has a larger impact on sanitation coverage than population density.
Figure 4.29 suggests a correlation between population density and open defecation, in
which areas with lower population density experience higher rates of open defecation.
However, when the woredas are split by both population density and by livelihood group (as
in figure 4.30), while that association between high open defecation and low population
density remains, there is a stronger correlation between the different livelihood groups and
open defecation rates.
Overlapping Deprivation and Rural Sanitation Access
Improvements in sanitation, poverty, health, education and water in rural areas have considerably
reduced the proportion of individuals deprived in multiple dimensions. Figure 4.31 depicts the
degree to which those deprived from sanitation and with monetary poverty overlap with
deprivation from access to the key services of health, education, and water. The number of
individuals experiencing more than one out of any three deprivations has been reduced
considerably. This is highest among individuals experiencing deprivation across sanitation,
Figure 4.29: Open Defecation Rates by Woreda Figure 4.30: Open Defecation Rates by Livelihood
Population Density in Ethiopia, 2007 Type and Population Density in Ethiopia, 2007
90 100
80
70 80
Open defecation (%)
Open defecation (%)
60
60
50
40
40
30
20
20
10
0 0
>50 50–100 100–150 <150 >50 50–100 100–150 <150 >50 50–100 >50
Woreda Cropping Agropastoralist Pastora-
list
Source: Housing and Population Census 2007.
66 Maintaining the Momentum while Addressing Service Quality and Equity
poverty, and health access, in which there has been a 47.2 percent reduction in those
experiencing two or three of these deprivations. This further confirms the significant gains
made in both access to sanitation and healthcare services in rural areas during period.
Experiencing deprivation in many dimensions at once makes it difficult to escape poverty; thus,
the overall progress is a positive indication that poor households with access to sanitation may
now be in a better position to see improvements in welfare.
This analysis confirms the positive relationship between access to sanitation and education,
with significant reductions seen in those experiencing overlapping deprivation for sanitation,
poverty, and education. This trend is reaffirmed by national statistics that show a direct
correlation between education levels and access to sanitation. Households with members
who have completed secondary education and beyond are significantly more likely to have
an improve latrine and not practice open defecation, even when one controls for wealth
(figure 4.32).
Figure 4.31: Overlapping Deprivation Trends in Rural Areas in Ethiopia, 2001–11
100
90
80
70
60
Percent
50
40
30
20
10
0
2000 2011 2000 2011 2000 2011 2000 2011 2000 2011
Sanitation, poverty, Sanitation, poverty, Water, poverty, Sanitation, poverty, Water, poverty,
and water and health access and health access and education and education
0 1 2 3
Sources: World Bank calculations using HICES 2000 and HCES 2011.
Figure 4.32: Access to Sanitation by Education Level of Head of the Household in
Ethiopia, 2011
100
80
60
Percent
40
20
0
No education Below primary Primary complete Secondary complete Above secondary
Improved Unimproved Open defecation
Sources: HICES and WMS 2011.
Maintaining the Momentum while Addressing Service Quality and Equity 67
Barriers to Rural Sanitation Access
While Ethiopia has a clear strategy and approach for moving rural households away from open
defecation, policy makers must analyze ways to support the government in the next stage of
transformative change in rural sanitation barriers and drivers to improve sanitation. A number
of factors have driven the high percentage of unimproved latrines and in the inability of people
to constructed improved latrines.
HEWs have focused more on stopping open defecation, rather than the promotion and adoption
of technology solutions that qualify as improved. The CLTSH behavior change approach has
harnessed a community response through individuals’ emotions such as shame, pride, and
collective responsibility, which when implemented effectively has been very powerful. However,
where HEWs have not been provided adequate training and lacked the necessary skills, this
approach risks households being forced to build latrines due to social pressure or even coercion,
and not through a real desire to improve their sanitation situation. Hence poor quality latrines
with minimal investment are built just to meet community requirement, not for personal use.
While evidence on latrine usage in Ethiopia is still limited, global evidence shows that there is
a link between the quality of the latrine and the regularity of use. Latrines that don’t provide a
positive experience for their users (i.e., they smell, are dark, don’t offer privacy, are unstable,
and risk collapse) are not used as much as when a positive experience is had. In addition, poor
quality latrines are more likely to become dysfunctional more quickly than latrines constructed
robustly. This includes using wood and earth for a slab instead of using concrete shallow pits
that fill up more easily, or unlined pits in soil conditions that risk collapse. Hence, moving
people away from practicing open defecation into using poor quality latrines has proven to
support only temporary behavior change.
A new generation of behavior change strategies and messages are required to provide HEWs
with the tools to reinforce the message of collective action and to encourage the construction
of higher quality latrines. A more balanced mix of messages is required. Messages that trigger
key behavior changes, such as stopping of open defecation and creating demand for latrine
use, need to be continued. However, these need to be complemented with more informative
communication, which increases household knowledge of what constitutes a hygienic and
sustainable latrine, the benefits of additional investment, and where to access product and
services to build improved latrines.
The current dearth of sanitation products and services in rural areas is another critical barrier
to people constructing improved latrines. Appropriate products are often not available in local
markets, and when available are often too expensive for most consumers or poorly marketed
to reach the demand for latrines created by HEWs. If over the next decade, Ethiopia is to
replicate the successful transition from open defecation to unimproved latrine with a move to
improved latrine, innovative and low-cost products need to penetrate rural market. Greater
product availability needs to be complemented with appropriate skills, both in construction of
improved latrines and in business expertise to enable enterprises to be established, be made
profitable, and create jobs. The Ministry of Health (MoH) partnership with other government
agencies (such as the Technical and Vocational Education and Training Agency [TVET] and
micro- and small business development agencies) with skills and experience in these areas
will provide a strong foundation for this transition.
The availability of products and services will not have the desired impact on sanitation
uptake if consumers don’t have the necessary finance to purchase them. The government’s
policy of providing to rural areas no hardware subsidies and limited access to finance
(such as microcredit) has hampered households’ ability to invest in their sanitation
facilities. This is a key contributor to latrines being constructed with less durable
68 Maintaining the Momentum while Addressing Service Quality and Equity
materials and to lower standards, as well as the perception from businesses that there
is limited demand for sanitation products and services. However, analysis shows that
those households that have access to credit are more likely to invest in improved latrines
(see figure 4.33). While this is true for all poverty quintiles except the poorest, the
richest quintile has benefited most from access to credit. It is also clear that access to
credit has a bigger impact in urban areas where more products and services are
available(see figure 4.34).
Limited data are available on the financing of businesses, but it is clear that in addition to
making credit available for households to purchase sanitation products, businesses also
need finance to engage in sanitation-based activities. The engagement of TVET and
business development agencies have facilitated credit to new sanitation enterprises
through the provision of training, accreditation, and development of financeable business
models. However, further efforts are needed to engage microfinance institutions and the
Development Bank of Ethiopia to enable sufficient finance to be targeted at businesses of
varying sizes seeking to enter the sanitation market. The Ethiopia Chamber of Commerce
and Sectoral Association can help facilitate market development and linkages to improve
the supply chain.
Figure 4.33: Sanitation Coverage Compared to Access to Credit in Rural and Urban
Regions in Ethiopia, 2011
100
90
80
70
60
Percent
50
40
30
20
10
0
No Access No Access No Access
access access access
Total Rural Urban
Sanitation coverage
Improved Unimproved Open defecation
Source: WMS 2011.
Maintaining the Momentum while Addressing Service Quality and Equity 69
Figure 4.34: Sanitation Coverage Compared with Access to Credit in Poverty Quintiles
in Ethiopia, 2011
100
90
80
70
60
Percent
50
40
30
20
10
0
ss
ss
ss
ss
ss
ss
ss
ss
ss
ss
ce
ce
ce
ce
ce
ce
ce
ce
ce
ce
ac
Ac
ac
Ac
ac
Ac
ac
Ac
ac
Ac
o
o
o
o
o
N
N
N
N
N
Poorest Poorer Middle Richer Richest
Quintile
Implication of Achieving the SDG Targets
The higher sanitation service levels that the SDG targets demand are more applicable in urban
context than in rural settings. However, the key difference for the rural setting is that safely
containing fecal waste in a private improved onsite facility will now only qualify as basic
sanitation access. If the improved latrine is shared, the household will be counted as having
limited sanitation access. To qualify for safely managed access, households will need to safely
contain fecal waste in a private improved latrine, and once full there will need to be evidence
that this waste is safely managed. For onsite facilities there are two modalities for achieving
this: emptying or sealing the pit. There is very limited prospect of off-site sanitation
infrastructures being developed in rural Ethiopia soon, although pit emptying and disposal
services may well become more common.
With such low improved sanitation coverage in rural areas, even reaching basic sanitation
access will require a huge effort. There will also need to be an increased focus on the
sustainability of infrastructure, since the new system will place increased focus on the effective
use and whole life cycle of sanitation infrastructure, not simply its construction.
To accurately monitor progress using the SDG indicators, new data will need to be generated by
the GoE’s sector monitoring systems and national surveys. For example, in the data presented
in figure 4.35, an assumption has been made that half of improved latrines are safely sealed
once full. This data are currently not available, nor are data available on whether pits are safely
70 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 4.35: Rural Sanitation Coverage in Ethiopia, 2016—SDG Methodology
SDG ladder
100
90
Rural sanitation coverage (%)
80
70
60
50
40
30
20
5 4 4 0 ?
10 2 (?) 2 (?)
0
Population Population Population Safely Population Safely Population
using using using disposed using piped transported using safely
improved- improved private on-site or sewer and treated managed
type on-site improved treated off-site sanitation
sanitation sanitation on-site off-site services
facility sanitation
SDG methodology
Safely managed At least basic Limited Unimproved Open defection
Source: World Bank calculation based on DHS 2016.
Note: SDG = Sustainable Development Goal; ? = figure based on best estimate using existing data.
emptied and treated off-site. The current sector monitoring system for rural sanitation needs
strengthening (as documented in a World Bank report [Jones 2015]). This will require additional
investments in capacity and system development.
Capacity Constraints across Rural WASH
Institutional and human resource capacity remains one of the biggest barriers to progress at
all levels of government. Tracking the evolving capacity at different levels of government is
difficult but provides an important variable in the effectiveness of service delivery, as well as
the sustainability of services. As more power has been devolved downward and the number of
administrative units have increased, the capacity and maturity of institutions delegated to
deliver basic services have varied considerably across the country.
An internal World Bank study in 2014 estimates that at the federal level within the water
sector, 63 percent of staff positions were filled and 79 percent filled in the health sector,
compared to the average of 62 percent across the six sectors reviewed (see table 4.2).
Regions and woredas were operating with even lower levels of required staff. In 2013, the ONE
WASH National Programme (OWNP) cite a shortfall of about 40 percent across all technical
cadres from artisans and water technicians to professional engineers, equating to some
47,000 people. It is difficult to see how the mandates of government institutions can be
delivered with this extensive underdeployment of professionals.
Even where staff have been recruited and deployed, there is an ongoing challenge of retaining
personnel, with high turnover of both administrative and technical staff. The gross turnover rate
(voluntary and involuntary) in the water sector was 7.6 percent and 6.3 percent in health in
Maintaining the Momentum while Addressing Service Quality and Equity 71
Table 4.2: Involuntary Turnover by Sector and Professional Level in Ethiopia, Fiscal Year 2013
Percent
Sector Professional Support Manager Total
Water 9.3 2.1 4.7 4.5
Health 6.6 5.1 8.4 6
Six sector average 5.7 2.9 3.9 4.6
Source: World Bank calculation based on available government data.
fiscal 2013, compared to the average across the sectors reviewed of 6.3 percent. Low
government salaries and working in far-flung rural areas are disincentives, with staff preferring
better terms and conditions in towns and cities.
Evidence shows that the most significant turnover type is internal voluntary turnover (transfers
and moves) to other positions within the public sector, which is in principle under the control of
government. The health sector has had one of the highest total involuntary turnover rates,
primarily due to high turnover at managerial level. In the water sector, total turnover was in line
with the average across the six sectors reviewed; however, the involuntary turnover in
professional staff was significantly higher.
Men dominate staff positions in the water sector, while women make up most staff in the
health sector. Data support the perception that in the water sectors there is a higher prevalence
of males in professional positions, such as water engineering, with men making up 71 percent
of the workforce. In contrast, in the health sector, women make up 53 percent of the workforce,
including the roles of HEWs (filled almost exclusively by women). However, this data also
indicates a lack of women further up the health system.
The OWNP and the WIF emphasize the need to improve capacity, and a National Capacity
Building Unit has been established to coordinate efforts. However, the capacity of government
institutions to provide systematic and regular support is limited by staffing constraints, and by
differing interpretations of what support is needed and how best it should be delivered. The
lack of ongoing targeted and tailored training—as well as the lack of other capacity development
tools, such as supportive supervision and mentoring—hamper effective delivery in the WASH
sector. Poor mechanisms to transfer knowledge between staff when turnover occurs further
undermines the limited capacity building efforts.
The vision of the integrated delivery of WASH services is undermined by the low awareness of
the principles, institutional arrangement, and working modalities of OWNP . The potential to
decentralized management of WASH service delivery is immense given the availability of
woreda WASH teams, HEWs, and teachers. However, poor coordination and weak planning
systems between the different institutions at all levels mean that these resources have still
not been maximized.
Notes
1. See the 1994 Ethiopia Housing and Population Census, WHO/UNICEF JMP database.
2. Completed in 2011 and based on a census of households and water points (users and
systems). The census covered 92,000 rural water supply schemes, over 1,600 small towns
and 50,000 schools and health institutions (Butterworth et al. 2013). There are plans to
repeat and improve the exercise: one national census every two years beginning 2017.
3. Based on the highest resolution data available, the levels of variation among woredas
within each region (standard deviation plus or minus 12 percentage points to 22 percentage
points) is greater than that among regions (standard deviation plus or minus 9 percentage
points). (Central Statistics Agency, Housing and Population Census 2007.
72 Maintaining the Momentum while Addressing Service Quality and Equity
4. Though annual rainfall is the basic indicator analyzed here, other related factors, particularly
altitude and evapotranspiration rates, exacerbate the water stress experienced in low
rainfall regions.
5. Poverty headcount ratio and water coverage are one standard deviation below the woreda
mean.
6. Datturi et al. (2015) conclude that multivillage reticulated schemes can achieve impact
at scale, serving a population of over 15 million people with safe water. However, they
note that the costs of repairs associated with frequent breakdowns, power outages,
and pretreatment (e.g., of low fluoride river water) are largely borne by regional bureaus,
not users.
7. Typically surveys ask respondents to estimate the amount of time required to travel to the
water source, queue if necessary, fill containers, and return to the household. While self-
reported journey times are not always precise, they nevertheless provide a useful indicator
of the relative time burden of water collection.
8. The human right to water specifies that water should be “available continuously and in a
sufficient quantity to meet the requirements of drinking and personal hygiene, as well as of
further personal and domestic uses, such as cooking and food preparation, dish and laundry
washing and cleaning. Supply needs to be continuous enough to allow for the collection of
sufficient amounts to satisfy all needs, without compromising the quality of water.”
9. Fecal contamination of drinking water is usually identified through the detection of indicator
bacteria such as Escherichia coli (E. coli) in a 100 milliliter sample. Contamination can be
highly variable in time, and brief contamination events can escape detection with routine
surveillance but still have serious public health outcomes. Ethiopia’s standards are aligned
with WHO Guidelines for Drinking Water Quality.
10. Surveys conducted during the El Niño drought in Oromia and Amhara highlight growing
levels or rural indebtedness associated with reduced off-farm seasonal employment (vital
for poorer households with smaller land holdings) and migration opportunities (see AKLDP
field notes at the website http://www.agri-learning-ethiopia.org/).
11. The UAP’s target was more ambitious than the MDG target, in both aiming for universal
access and setting a deadline of 2012.
12. The JMP relies on a number of government data points and applies some assumption to
reach their coverage figures. The analysis in this report has used the original government
data (DHS, WMS, and the National Census) and not applied any assumptions.
13. Open defecation is the practice of people defecating outside and not into a
designated latrine.
14. Unimproved latrine is a sanitary facility that does not ensure hygienic separation of human
excreta from human contact. Unimproved facilities include pit latrines without a slab or
platform, hanging latrines, and bucket latrines.
15. Improved latrine is a sanitary facility that ensure hygienic separation of human excreta
from human contact. They include flush or pour-flush toilet or latrine to piped sewer system,
septic tank, or pit latrine; ventilated improved pit (VIP) latrine; pit latrine with slab; and
composting toilet.
16. Dr. Shiferaw Teklemariam was the head of the Health Bureau in SNNPR, served as the
Minister of Health, and is now the Minister for the Environment.
References
Butterworth, J., S. Sutton, and L. Mekonta. 2013. “Self-Supply as a Complementary Water
Services Delivery Model in Ethiopia.” Water Alternatives 6 (3): 405–23.
Calow, R., E. Ludi, and J. Tucker. 2013. Achieving Water Security: Lessons from Research in
Water Supply, Sanitation and Hygiene in Ethiopia. Rugby, U.K.: Practical Action Publishing.
Calow, H., and B. Macdonald. 2016. “Climate Change and Water and Sanitation: Likely Impacts
and Emerging Trends for Action.” Annual Review of Environment and Resources 41 (1):
253–76.
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Carter, R. C., and I. Ross. 2016. “Beyond ‘Functionality’ of Hand Pump Supplied Rural Water
Services in Developing Countries.” Waterlines 35 (1): 94–110.
Coulter, L., S. Kebede, and B. Zeleke. 2010. Water Economy Baseline Report: Water and
Livelihoods in a Highland to Lowland Transect in Eastern Ethiopia. Addis Ababa: RiPPLE
Ethiopia.
Datturi, S., F. van Steenbergen, M. van Beusekom, and S. Kebede. 2015. “Comparing
Defluoridation and Safe Sourcing for Fluorosis Mitigation in the Ethiopian Central Rift
Valley.” Fluoride 48 (4): 293–314.
Dessalegn, Mengistu, Likimyelesh Nigussie, Wondwosen Michago, Josephine Tucker, Alan
Nicol, and Roger Calow. 2013. Voices from the Source: Struggles with Local Water Security
in Ethiopia. London: WaterAid.
Howard, G., and J. Bartram. 2003. Domestic Water Quantity, Service, Level and Health. Geneva:
WHO.
———. 2016. Domestic Water Quantity, Service, Level and Health. Geneva: WHO.
Jones, O. 2015. Monitoring Sanitation and Hygiene in Rural Ethiopia: A Diagnostic Analysis of
Systems, Tools and Capacity. Washington, DC: World Bank.
Kebede, S., A. M. MacDonald, H. C. Bonsor, N. Dessie, T. Yehualaeshet, G. Wolde, P. Wilson,
L. Whaley, and R. M. Lark. 2017. UPGro Hidden Crisis Research Consortium: Unravelling
Past Failures for Future Success in Rural Water Supply. Survey 1 Results—Country Report
Ethiopia. Nottingham, U.K.: British Geological Survey.
Sphere Project. 2011. Humanitarian Charter and Minimum Standards in Humanitarian
Response. Rugby, U.K.: Practical Action Publishing.
Tincani, L., I. Ross, R. Zaman, P . Burr, A. Mujica, J. Ensink, and B. Evans. 2015. Regional
Assessment of the Operational Sustainability of Water and Sanitation Services in Sub-
Saharan Africa. Oxford, U.K.: Oxford Policy Management.
Tucker, J., E. Ludi, L. Coulter, and R. Calow. 2014. “Household Water Use, Poverty and
Seasonality in Ethiopia: Quantitative Findings from a Highland to Lowland Transect.”
Journal of Development Studies.
UNICEF (United Nations Children’s Fund). 2016. Ethiopia WASH Cluster Bulletin. New York:
UNICEF. https://www.humanitarianresponse.info/en/operations/ethiopia/document
/-ethiopia-wash-cluster-bulletin-april-2016.
UNICEF and WHO (World Health Organization). 2015. Progress on Sanitation and Drinking
Water: 2015 Update and MDG Assessment. New York: UNICEF.
WHO. 2010. Rapid Assessment of Drinking-Water Quality in the Federal Democratic Republic of
Ethiopia: Country Report of the Pilot Project Implementation in 2004–2005. Geneva: WHO.
World Bank. 2009. Ethiopia Public Expenditure Review. Washington, DC: World Bank.
———. 2014a. Ethiopia Public Expenditure Review. Washington, DC: World Bank.
———. 2014b. Ethiopia—Productive Safety Nets Project Four. Washington, DC: World Bank.
———. 2015. Ethiopia Public Expenditure Review. Washington, DC: World Bank.
74 Maintaining the Momentum while Addressing Service Quality and Equity
Community water point in Harar City.
© Chris Terry/World Bank
Chapter 5
Urban WASH Sector Analysis
Urban Growth and Institutions
The overarching trends in the urban water supply, sanitation, and hygiene (WASH) sector are
best understood from three perspectives: (a) rapid urbanization; (b) as a result, a large-scale
infrastructure investment and service delivery improvement requirement; and (c) a need for
systematic policy and institutional transformation in urban and water sector governance.
Ethiopia’s urban infrastructure and institutions are facing increased stress due to a rapidly
increasing urbanization. In 2012, roughly 17 percent of Ethiopia’s population lived in urban
areas, which is well below the Sub-Saharan Africa average of 37 percent.1 As of 2015,
urbanization rates were around 3.4 percent per year, some estimates anticipate this rate could
soon exceed 5 percent a year. Such an increase would result in 30 percent of the population
living in urban areas by 2028 and tripling of the urban population by 2034.
Urban growth is recognized in the Growth and Transformation Plan (GTP) II as an opportunity
for sustained economic growth and structural transformation. However, if not well managed,
rapid urban growth could present less of a demographic dividend and more of a demographic
problem as cities struggle to provide jobs, infrastructure and services, and housing to more
people. Infrastructure and service delivery are already undermined by the growing urban
population and by stretched municipal budgets.
The urban demographic across the country has shifted with many smaller cities and towns
holding an increasing share of the urban population (see figure 5.1). Addis Ababa is by far the
most populous city, with twice the population of the next five largest towns. However, Addis
Ababa grew at significantly slower rate than other urban areas, at just under 20 percent,
between 2007 and 2015 (see figure 5.2). As a result, while in 2007 Addis Ababa accounted
for 39 percent of the urban population, by 2015 this had reduced to 28 percent. The
16 secondary towns2 grew by 67 percent during the same period, and now have a combined
total population that is greater than Addis Ababa’s.
The largest percentage growth in population is in existing and new urban centers with
populations below 50,000. This has resulted in them accounting for just over one-fourth of the
urban population by 2015 (similar to Addis Ababa’s share), compared to just 17 percent of the
urban population in 2007. This shift has been driven in part by the reclassification of large rural
settlements as urban centers, but this does not distract from the trends for significant growth
in smaller urban areas.
The Ministry of Water, Irrigation and Electricity (MoWIE) is the responsible federal institution for
provision of water supply in urban centers. MoWIE’s main responsibility is formulating the national
urban water supply development and management policies, strategies, and programs, as well as
monitoring and evaluating urban water supply development. The Water Resource Development
Fund (WRDF) is a federal organization that facilitates the development of urban water supplies
on a cost recovery basis, providing on-lending facilities to medium and large towns for water
supply expansion works. WRDF appraises loan applications by town water utilities, provides on-
lending facilities and ensures that loans are paid back and used as revolving funds.
Maintaining the Momentum while Addressing Service Quality and Equity 77
Figure 5.1: Population Growth by Population Size of Towns and Cities in Ethiopia,
2007–15
180
3,500
160
3,000
140
2,500
120
Pop. (thousands)
2,000 100
Percent
80
1,500
60
1,000
40
500
20
0 0
Addis Ababa 100–350 50–100 <50
Pop. of capital, towns, cities (thousands)
2007 2015 Percentage growth
Source: World Bank calculations based on World Bank 2015c and Housing and Population Census 2007.
Figure 5.2: Share of Population by Population Size of Towns
and Cities in Ethiopia, 2007 and 2015
2015
2007
Pop. of capital, towns, cities
(thousands)
Addis Ababa 100–350
50–100 <50
78 Maintaining the Momentum while Addressing Service Quality and Equity
Regional water bureaus develop regional water sector development programs and strategies,
manage water supply projects, and provide support to town water supply utilities. The regional
bureaus develop regional proclamations to establish water utilities and town water boards. The
Bureau of Finance and Economic Development (BoFED) allocates, channels, administers, and
controls financial grants for urban water supply utilities in the region. Loans are directly
channeled from WRDF to town water utilities.
Ethiopia has no stand-alone sanitation policy, but sanitation development strategies are
captured in the health, environment, water, and urban development sector policies. Institutional
arrangements for urban sanitation are complex, with MoWIE, the Ministry of Health (MoH), and
the Ministry of Works, Urban Development and Housing Construction (MoWUDC) sharing
responsibilities for monitoring and oversight of hygiene and sanitation services at the federal
level. This institutional fragmentation and unclear responsibilities have led to gaps in service
provision and challenges in holding utilities accountable for improvements in service quality
and coverage. Each ministry has focused on its own mandate, as well as internal planning and
management systems. Hence, inadequate coordination of planning, design, implementation,
and supervision has resulted in poor quality construction and weak asset management.
At the regional level several bureaus are involved in capacity building, funding, and monitoring
of urban sanitation activities. Regional bureaus with an urban sanitation role resemble the
institutional arrangements at the federal level, and there is generally an office responsible for
sanitation, beautification, and greenery in the regional Urban Development Bureau. Regional
Water Bureaus in some regions are now starting to explore sewered systems, especially if they
are part of the MoWIE’s proposed wastewater interventions in six cities earmarked for sewerage.
Liquid waste management is further supported by the regional health bureau, which focuses
mainly on promoting hygiene and sanitation at household level.
Despite a new policy direction, due to the number of institutions involved in urban sanitation
service delivery and management, it will take some time for the respective institutions to come
to terms with the evolving environment of urban sanitation challenges. In 2017 the relevant
ministries endorsed a cross-sectoral Integrated Urban Sanitation and Hygiene Strategy, with
the aim of aligning relevant strands of existing policies in different sector policy documents.
The integrated strategy takes forward mandates of various ministries in light of new insights
and aligns institutional arrangements for greater effectiveness.
Urban water utilities in Ethiopia are formed from two entities, town water supply and sewerage
enterprises, which hold the function of operator, and town water boards, which are the oversight
body. The town water supply and sewerage enterprises are responsible for the planning,
development, and provision of water supply services in urban areas. As part of their control and
supervisory function, the town water boards are responsible for approving town water supply
and sewerage enterprises’ annual plans and programs, monitoring activities of the enterprises,
and assigning the manager of the enterprise.
Unlike in the telecom and power sector, there is no independent regulatory agency for provision
of urban water supply services in the country. The regional water bureaus, town health offices,
city councils, and town water boards share the burden of different regulatory activity. The
MoWUDC also plays a part in monitoring the standard of municipal services, including water
supply and solid waste.
Water and sewerage entities in each municipality are legally mandated to provide wastewater
services in the larger cities, but municipalities are responsible for solid waste and storm water
management. In most cases municipalities have not been able to coordinate sanitation
services (wastewater, solid waste, and stormwater) effectively. The lack of coordination between
solid waste and liquid waste services, as well as drainage, is a problem since these waste
streams are often mixed together; for example, drainage channels are contaminated with fecal
waste, and are blocked by solid waste.
Maintaining the Momentum while Addressing Service Quality and Equity 79
Elaine Gelan, 23 years old. Water supply connected August 2016, 9 months after application. Kebele 12, Harar, Harari Region.
© Chris Terry/World Bank
80 Maintaining the Momentum while Addressing Service Quality and Equity
Mechanisms and institutional capacity to enforce public health proclamations and pollution
control regulation are weak, even though “polluter pays” principles have been adopted formally.
The existing regulations do not clearly define the minimum standards for services, and are
mostly silent on the urban sanitation delivery chain of collection, transportation, treatment,
and disposal. In addition, town and city leaders currently give very little attention to managing
and mitigating potential pollution impacts of existing and new industries. Coordination between
the industrial, water, and other sectors is currently too weak to manage the impacts of the
envisaged growth in pollution from expanding population and industry. Unchecked and
persistent industrial pollution (tannery, food processing, and textiles sectors) can cause
significant long-term contamination to water bodies and other environmental and health
impacts. Current weak monitoring systems mean detection will take many years, making
cleanup very expensive or impossible.
Capacity building and institutional development is needed across urban utilities and boards
including clearer performance incentives and a more business-oriented approach driven by
a clear business plan with measurable targets. This applies to all functions and roles:
supporting senior strategic leadership approaches and skills; updating technical skills at
the operational level; and developing greater ownership of the institutional development
agenda. More transparent HR systems and databases will enable utilities to hold staff
members accountable for their performance on clearly assigned responsibilities.
The necessary technical and financial resources to adequately support rural administration
transition to urban centers have not been sufficiently acknowledged. As a result, many young
urban municipalities and utilities lack the skills to effectively take up the mandates expected
of them. The strengthening of relevant institutions through the provision of increased levels of
funding, guidance, and up-skilling sector staff is essential to meet the growing water supply
and sanitation challenges faced in urban areas.
Urban Water Subsector Analysis
National Status and Trends
The big shift over the past 20 years is that nearly 10 million people have been added to the
group of people who get their water from a tap in the yard just outside their house (figure 5.3).
By 2015, over half of urban households in Ethiopia got their water from a tap in the yard just
outside their house. Just under another 40 percent fetched water from a neighbor or standpipe
outside their compound. However, less than one in 20 of Ethiopia’s urban dwellers had a tap
inside their house as their main source of drinking water. Over the same period those fetching
water from standpipes outside their compound has remained fairly constant, rising from over
5 million to just over 7 million people.3
For around 60 percent of women and girls living in urban areas, this big shift toward using a
more convenient source of water has avoided a significant economic loss in time used to fetch
water.4 The rest of this section examines how this big shift to piped water in peoples’ yards
has been achieved and why this benefit has fallen disproportionately to wealthier women and
their families.
Evolution of Funding for Urban Water Supply
The progress in urban water supply has been driven by a more diverse set of funding sources
than that for rural water supply. The composition of funding sources changes from (a) when
piped networks emerge in small towns within a woreda to (b) when small towns are recognized
as urban local governments (ULGs) and (c) to when ULGs split off their water supply departments
to form utilities. In 2007 there were already over 200 locations with over 1,000 household
Maintaining the Momentum while Addressing Service Quality and Equity 81
Figure 5.3: Urban Drinking Water Trends in Ethiopia, 1990–2015
100 1
8 6
8
80
37
Coverage (%)
60
74
40
20 56
10
0
1990 2015
Surface water
Other unimproved sources
Other improved source
Piped onto premises
Source: WHO/UNICEF 2016.
connections. By 2015, 140 of these locations were granted ULG status, of which just under
100 of which had ring-fenced their water supply operations (see figure 5.4).
As piped networks first emerge in small towns, an initial critical source of capital investment is
the woreda block grant. In these small towns, from 2008–12, an average of US$30,000 to
US$40,000 per year from woreda block grants went toward the capital costs of establishing
piped networks.
As towns graduated to becoming ULGs, they no longer qualify for woreda block grants and have
to fund capital investment from their own revenues (municipal fees and charges). At these
initial stages of transition, the taxes assigned to ULGs raise only a limited amount of revenue,
which is too little to cover expenditure assignments given to ULGs. Nationwide, municipal
revenues account for just 3 percent of the national tax effort (World Bank 2015c). For smaller
towns this is a critical constraint in growing their water supply operations and means that they
are heavily dependent on regional state and donor investment.
Smaller ULGs have to compete with larger ULGs and utilities for funding from regions and
donors. The allocation of both regional and donor funding is subject to the discretion of regional
state or donor decisions, which makes them, from the ULG perspective, less predictable
investment flows than woreda block grants or municipal revenues.
The regional state funding to urban water supply is drawn from the regional block grants, and
since 2011, the Millennium Development Goal (MDG) special purpose grant has focused on
capital expenditure. From 2008–12, An average of US$44 million per year from these sources
was channeled to ULGs for capital investments in water.
Donor funding is often negotiated directly with specific towns, cities, or utilities, which results
in it being skewed toward larger cities and utilities, particularly Addis Ababa, which received
nearly 40 percent of donor funding (loans and grants) but accounts for only a quarter of
82 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 5.4: Towns Transitioning from Rural to Urban Local Governance, Ranked by Access to Improved Source
of Drinking Water, 2007
100
90
80
70
Percent
60
50
40
30
20
10
0
Mile, Afar
Odo Shakiso, Oromiya
Digluna Tijo, Oromiya
Toke Kutayu, Oromiya
Robe, Oromiya
Amaro, SNNPR
Dendi, Oromiya
Meta, Oromiya
Debub Achefer, Amhara
Fogera, Amhara
Tulo, Oromiya
Jabi Tehnan, Amhara
Gola Oda, Oromiya
Dembia, Amhara
Menz Gera Midir, Amhara
Dangila, Amhara
Becho, Oromiya
Kobo, Amhara
Dabat, Amhara
Enebse Sar Midir, Amhara
Lasta, Amhara
Dale, SNNPR
Kersa, Oromiya
Enemay, Amhara
Ada A, Oromiya
Dubti, Afar
Dejen, Amhara
Haro Maya, Oromiya
Cheko, SNNPR
Merhabete, Amhara
Silti, SNNPR
Dugda, Oromiya
Tehuledere, Amhara
Jile Timuga, Amhara
Mizan Aman town, SNNPR
Hitosa, Oromiya
Shebedino, SNNPR
Burayu Special, Oromiya
Kafta Humera, Tigray
Bahir Dar town Wereda, Amhara
Sawula town, SNNPR
Debre Markos town, Amhara
Woldiya town, Amhara
Abi Adi/town/, Tigray
Fiche town, Oromiya
Korem town, Tigray
Denbi Dollo/town/, Oromiya
Akaki Kaliti, Addis Ababa
Gulele, Addis Ababa
Woliso/town/, Oromiya
Asela town, Oromiya
Adwa/town/, Tigray
Wukro town, Tigray
Kemisie/town/, Amhara
Kirkos, Addis Ababa
Rural to
urban
Future urban areas with >1,000 connections to plot transition Urban areas
Source: Population and Housing Census 2007.
Note: SNNPR = Southern Nations, Nationalities, and People Region.
Figure 5.5: Donor Aid to Urban Water Supply and Sanitation in Ethiopia, 2006–15
300
250
200
US$ (millions)
150
100
50
0
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Commitments Disbursements
Source: OECD DAC CRS database.
Ethiopia’s urban population (see figure 5.5 and table 5.1). The larger utilities also have greater
revenue flows from which they can finance critical small infrastructure investments and
household connections.
Addis Ababa has been the only city allocating substantial own source revenue (> Br 1 billion)
per year to improving water supply. Secondary towns, such as regional capitals, provided some
matching funds to financing from bilateral sources.
Maintaining the Momentum while Addressing Service Quality and Equity 83
Table 5.1: Main Urban Water Supply and Sanitation Donors by Commitments in
Ethiopia, 2006–15
US$, millions
Donor Addis Ababa Other urban Total
World Bank (IDA) 99 289 388
China Exim Bank 148 n.a. 148
African Development Bank n.a. 64 64
United States 2 47 49
France 10 1 10
Italy n.a. 10 10
Japan n.a. 8 8
Other donors n.a. 5 5
Total 258 423 681
Source: OECD DAC CRS database.
Note: n.a. = not applicable.
Recognizing the constraint that smaller ULGs face, and as an instrument for implementing its
cost recovery policy, the GoE established a Water Resource Development Fund (WRDF) under
MoWIE in 2002. The WRDF is a revolving fund that can loan funds from government and donors
to expanding utilities. Since its inception, WRDF has received more than 144 applications for
loans from town utilities all over the country, but has extended loans only to 34 towns with a
value of Br 1.7 billion (US$80 million in 2017 prices). Utilities that have completed their grace
period have started repaying their loans.
Although more than 100 towns are on the waiting list to take up loans, WRDF has not yet
started disbursing from the finance repaid (World Bank 2014a). There is, therefore, still a
particular bottleneck in the funding or financing of water supply and sanitation infrastructure in
towns that graduate to being ULGs after they lose their woreda block grant allocations and are
outcompeted by larger towns and utilities, particularly for donor investment.
Improving the performance and reach of the WRDF would help these new ULGs with their water
supply investment needs. The WRDF has received additional funding to on-lend to utilities, and
the management of the WRDFs is working to streamline its lending and implementation
procedures, increase staffing levels, and address the reluctance by regional water bureaus to
guarantee loans for utilities (reforms that could help small towns with their investments needs).
Cost recovery from tariff holds the potential to generate internal revenue for expansion, but
policy and practice are at odds. The Sector Policy (1999) and Strategy (2001) envisioned a
move toward full cost recovery for urban water supply. However, the success in implementing
full cost recovery policies for town and urban water supplies has been limited. Tariffs
established in most water utilities cover at best operations and some maintenance, which
leaves investments for major rehabilitation and expansion of the systems to be financed by
government or donors. Underpricing and high nonrevenue water (NRW) undermine higher
levels of cost recovery.
In 2011 and 2012 the benchmarking of 76 utilities across the country reported average
revenue per cubic meter sold as just US$0.32 against costs of US$0.29 per cubic meter sold.5
Even the largest utility, Addis Ababa Water and Sewerage Authority (AAWSA), covers only its
operating costs (table 5.2). This narrow margin is in part due to NRW reported as 25 percent
for smaller utilities and over 40 percent for larger utilities.
84 Maintaining the Momentum while Addressing Service Quality and Equity
Table 5.2: Operational Costs and Revenues for AAWSA in Ethiopia, 2011–16
Br, millions
Cost and revenue items 2011 2012 2013 2014 2015 2016
Operating cost 280.2 332.5 519.9 544.8 560.9 665
Salaries and related benefits 106 130.4 138.1 213.8 202.4 240
Electricity 31.3 42.3 53.1 40.6 52.5 62.2
Chemical 45.3 7.3 64.2 84.5 72.1 85.5
Repair and maintenance 18.6 20.8 68.9 35.5 45.2 53.6
Fuel and lubricants 23.6 26.5 25.2 34.8 36.5 43.3
Other operating expenses 55.5 105.4 170.5 135.7 152.1 180.4
Revenue 294.9 386.7 489.9 699 640.4 689.2
Operating cost coverage ratio 1.05 1.16 0.94 1.28 1.14 1.04
Source: AAWSA.
Note: AAWSA = Addis Ababa Water and Sewerage Authority.
Although water tariffs are set by water boards, they need to be endorsed by the respective
regional administration. Where enabled, utilities over the past three to four years in some
secondary towns have started to accumulate tariff revenue for water system expansion.
Adama and Mekelle are examples where utilities have reinvested earnings of around US$4
million in 2016. But with regions reluctant to increase tariffs without seeing improvements in
efficiency, a vicious cycle has constrained the scope for full cost recovery and financial
sustainability.
Access Disparities by Wealth and Consumption
In contrast to the equitable distribution of services in rural areas, relative consumption or wealth
strongly correlate with access to piped water on premises in urban areas. Although in 2015
nearly 12 million people in urban areas had access to piped water in their house or compound,
close to 8 million urban Ethiopians had to fetch water from sources outside their compound
(see figure 5.6). This includes 1 million people who relied on unimproved sources, including
water from vendors and even lakes, ponds, and streams in or close to urban areas. Those
without access to piped water on premises are disproportionately poorer and are members of
lower income households (see figure 5.7).
Some of this inequality in access can be explained by the correlation between city size and
access (see figure 5.8). Multivariate regression confirms this inequitable capture of piped
water on premises by higher income households. The regression results also show that
independent of household income levels, piped water on premises is siginificantly correlated
with town size. Households in Addis were three times more likley to have access to piped
water on premises than medium or large towns. In turn households in medium and large
towns, other than Addis, were more than twice as likely to have access to piped water on
premises than small towns. The broad trend is that as cities grow, their poverty headcount
drops and their levels of piped water on premises rises (although Addis Ababa is an outlier
with both higher levels of access and higher rates of poverty). (See appendix B for data
sources and regression results.)
However, this correlation between city size and access does not help explain what should be
done to address inequality of access. More interesting perhaps is the unexplained variation
among cities of similar sizes, which suggests that some are doing better than others at creating
a poverty reducing environment and at providing access to piped water on premises (see
figure 5.9).
Maintaining the Momentum while Addressing Service Quality and Equity 85
Figure 5.6: Urban Drinking Water Coverage by Wealth Quintile in Ethiopia, 1995–2011
100
80
Percent 60
40
20
0
Poorest Second Middle Fourth Richest
Wealth quintile
Piped on premises Other improved Unimproved
Sources: DHS and WMS/HICES.
Note: Further details in appendix A.
Figure 5.7: Urban Drinking Water Coverage by Consumption Quintile in Ethiopia, 2000–11
100
80
60
Percent
40
20
0
Poorest Second Middle Fourth Richest
Consumption quintile
Piped on premises Other improved Unimproved
Sources: DHS and WMS/HICES.
Note: Further details in appendix A.
86 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 5.8: City Size and Poverty in Ethiopia, 2015
0.5
0.4
Poverty headcount index
0.3
Addis Ababa
0.2
0.1
0
10 11 12 13 14 15
In (city size)
Fitted values of quadratic prediction do not include Addis Ababa
Tigray Amhara Oromiya Somali Benishangul-gumuz SNNPR
Gambella Harari Dire Dawa Addis Ababa Fitted values
Source: World Bank 2015a, 97.
Note: SNNPR = Southern Nations, Nationalities, and People Region.
Figure 5.9: Improved Access by Addis Ababa, City States, and Other Urban Areas in
Ethiopia, 2011
80
70
60
50
40
Percent
30
20
10
0
Addis Ababa Dire Dawa Harari Other urban
Piped to premises Public tap/standpipe Other improved Unimproved
Source: DHS 2011.
Maintaining the Momentum while Addressing Service Quality and Equity 87
An actionable analytical approach is to understand the barriers preventing poorer
households from hooking up to piped water either from the demand or the supply side.
Demand-side barriers prevent households from hooking up to the service, even when the
networks pass close to their homes. Demand-side barriers can include high connection
charges that make hooking up unaffordable; land and housing tenure that disqualify or
make it difficult for households to connect; and other social and economic factors that
may deter households from becoming utility customers (see the case study on Harar City,
box 5.1).
Household survey samples are based on geographic clusters that, at least for urban areas, are
physically small, amounting to no more than a few city blocks. It is therefore possible to
examine the extent to which people lacking access to water supply live in clusters where
infrastructure is available as evidenced by their immediate neighbors being hooked up to the
service (Banerjee et al. 2008; Wodon 2007).
Box 5.1: Case Study of Applying for Connection by Poor People in Harar City
In Harar, many poor people live in the older, high density parts of the town. Like in many towns
in Ethiopia, poor people struggling to meet basic needs live either in kebele or rented housing.
Eleni and W/ro Asamenech represent typical poor women who head households in the low-
income areas of Kebele 12 of Harar City.
Eleni is a daughter of migrants from Amhara region and has lived in Harar City since the age
of three. When she was 12, her father, abandoned the family and left for another woman.
Eleni, now 23, is dependent on her mother as she is disabled, with a limp and speech
difficulty. Her mother, the main breadwinner, works as a cleaner in a government office in Harar
City. They live in social housing, known as kebele housing, renovated by an NGO.
W/ro Asamenech is a 75-year-old woman living with her 14-year-old grandson from her
deceased daughter. She lives in a poor community in her one-room residence that was built
by an NGO. In the past, she used to work as a house help. She is now very weak and is
dependent on donations from people in her neighbourhood.
Access to electricity and water services is available in this low-income neighborhood. Many
houses have electricity connections, but fewer houses have water connections due mainly to
the high cost of and cumbersome process of connecting. Getting a water connection in Harar
includes filling out an application along with a copy of a property title deed, copy of an identity
card, a passport size photo, an advance payment of Br 500 for the water meter, plus an
additional Br 1,400 payment or more depending on the pipe length requirement from the
service water main up to the yard tap. For people in kebele housing, a supporting letter from
the kebele is required instead of a copy of the property title deed.
Eleni and W/ro Asamenech do not have water connections and so buy water from the
neighborhood public tap paying six to eight times more than if they had their own connection.
Beside the hardship of the higher cost, carrying is a real challenge for both women.
box continues next page
88 Maintaining the Momentum while Addressing Service Quality and Equity
Box 5.1: Continued
Asamenech Semei, 75 years old. Applied for water connection twice, still waiting as of December 2017. Kabele 12,
Harar, Harari Region.
© Chris Terry/World Bank
The Water for Life Project is being implemented by the Harar utility to improve services to low-
income households. The project is financed by the governments of The Netherlands and
Ethiopia aim to provide 25,000 low-income people with a common water tap for three to five
low-income households. W/ro Asamenech and two other neighbors were among the selected
beneficiaries of this project. At the time of finalizing the connection, W/ro Asamenech agreed
box continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 89
Box 5.1: Continued
for the younger neighbors to process the requirements for the connection, not knowing that
one of the neighbors would change the location of the tap from a communal area to being
installed in her compound, which is up the hill from where W/ro Asamenech lives. Consequently,
W/ro Asamenech does not benefit from this new tap since she cannot walk up the hill. So she
continues to buy water at a higher price from houses closer by.
When Eleni went to the utility for the first time, she had a supporting letter from an NGO
explaining her situation and requesting a water connection free of charge. The utility, instead
of receiving her application, told her to wait. Eight months later Eleni decided to try again. This
second time the utility had received funding to connect poor HIV victims, but she was still told
to wait a month. Returning a month later, the utility told her to submit an application. On that
same day Eleni filed her application. Three working days after her application was filed, Eleni
got her own water connection. So grateful for getting a connection Eleni allowed her neighbors
to collect water from her tap free of charge, though in the future she has not ruled out the
possibility of selling water to her neighbors.
W/ro Asamenech, motivated by Eleni’s story, went to get a supporting letter from the Keble
and took her application to the utility and is now awaiting their response. A staff member at
the utility who knows her well is trying to team her up with other poor neighbors who are also
looking for water connections. Yet the chance of finding one seem to be low, since most
households in the immediate vicinity have their own private connections.
Source: Yemane and Defere n.d.
Supply-side problems were concentrated in the urban areas of the Somali, Benishangul-
Gumuz, and Gambella regions, though Oromia with its large number of emerging small towns
also faced greater supply than demand-side barriers (see figure 5.10). Of the 184 urban
primary sampling units (PSUs) in the DHS 2011 only five did not have any piped water at all.
These were all in small towns in the emerging regions of Somali, Gambella, and Benishangul-
Gumuz. In these small towns, even the wealthiest households were almost entirely reliant on
water delivered by vendors and had no access to any form of piped water (figure 5.11). In a
further 13 PSUs there was piped water but no household connections. These were scatted
across the country, including in the cities of Addis Ababa, Dire Dawa, and Harari, representing
towns or peri-urban areas in which the water supply entity or utility had not or was not able to
connect households. A further 44 PSUs had fewer than 30 percent of households with piped
water on premises. All these PSUs, totaling 62, with no or very limited access to piped water,
might be considered to have a basic supply-side problem—one that makes it logistically
difficult or impossible to connect households to the network (e.g., no utility to make
connections, very limited water networks, insufficient water resources). Urban areas like
these are home to about a quarter of urban Ethiopians, including around 1 million poorer
households (below 40 percent of the wealth quintile [B40]), most (>95 percent) of which do
not have piped water on premises.
Demand-side barriers were more prevalent in cities and regional capitals. In the remaining two-
thirds of PSUs (122), more than 30 percent of households had water to their premises but still
had significant numbers of households not hooking up to the network. These might be
90 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 5.10: Proportion of PSUs in Ethiopia with Supply- or Demand-Side Barrier to
Hooking Up Households, 2011
100
90
80
70
60
Percent
50
40
30
20
10
0
a
ar
i
ay
a
ra
PR
a
la
uz
i
an
ar
al
ab
aw
iy
be
Af
ha
m
gr
um
ar
rb
N
m
Ab
D
So
am
H
Ti
Am
SN
lu
ro
l-G
ire
O
Al
s
G
di
gu
D
Ad
an
sh
ni
Be
Barrier to hooking up households
Demand Supply
Source: DHS 2011.
Note: PSU = primary sampling unit; SNNPR = Southern Nations, Nationalities, and People Region.
Figure 5.11: Coping Strategies in Areas of Small Towns in Ethiopia with No Piped
Water, 2011
100
Household head main source of drinking water (%)
90
80
70
60
50
40
30
20
10
0
Poorest Poorer Middle Richer Richest
Enumeration Area without piped water
Protected wells and springs Tanker or cart Unimproved
Source: DHS 2011.
Maintaining the Momentum while Addressing Service Quality and Equity 91
Figure 5.12: Share of Urban B40 and T60 Households Hooked Up to Available Urban
Water Supply in Ethiopia, 2011
100
90
80
70
Percent 60
50
40
30
20
10
0
uz
ar
i
ay
a
i
la
PR
a
a
ra
ar
al
iy
ab
aw
be
Af
ha
m
um
gr
ar
m
N
Ab
So
D
am
H
Ti
SN
Am
ro
l-G
ire
O
s
G
gu
di
D
Ad
an
sh
ni
Be
T60 B40
Source: DHS 2011.
Note: B40 = bottom 40 percent of wealth index; SNNPR = Southern Nations, Nationalities, and People Region; T60 = top
60 percent of wealth index.
considered areas where there is a problem related to affordability or other socioeconomic
barriers to connecting. Across these PSUs 82 percent of wealthier households were connected
(top 60 percent of the wealth quintile [T60]) while only 44 percent of the poorer households
(B40) were connected (see figure 5.12).
Some of the greatest disparities in access are within the larger cities, including Addis Ababa,
Dire Dawa, Bahir Dar in Amhara, and Awasa in the Southern Nations, Nationalities, and People
Region. In these urban areas, home to three-quarters of urban Ethiopians, over 3 million poorer
households do not have access to piped water on premises.
Addressing inequality in urban areas therefore requires two quite different responses: (a)
capital investment for towns facing supply barriers; and (b) incentives to hook up customers
in cities with demand barriers. The first needs to target urban areas, mainly smaller towns,
with supply-side barriers. These urban areas need capital investment to expand their
production facilities and distribution networks so all residents can hook up to the service,
including close to a million poorer households (B40). The second response is in mainly
larger cities, which experience demand-side barriers. These urban areas already have
extensive water supply networks, but 3 million poorer households (B40) are struggling to
hook up to them. From both survey data and from case material the main barrier is the
connection process, including the connection charge. Once connected affordability of water
is not a major barrier. In these cities, municipalities and utilities need to be incentivized to
connect poorer customers.
92 Maintaining the Momentum while Addressing Service Quality and Equity
Separating Service Affordability from Other Barriers to
Hooking Up
The HICES 2011 reports average actual expenditure on water in urban areas to be Br 168 per
person per year (US$10), equating to an implied industry turnover of US$93 million a year.
Expenditure rises across quintiles, particularly for privately vended water; the implied revenues
to private vendors are higher than those for utility water piped to premises. This suggests that
there is both a vibrant water market and opportunity for utilities to win back market share from
private vendors (figure 5.13).
The average tariff in Ethiopia was reported as Br 5 per cubic meter (US$0.29) in 2011. There
are variations across the country, within the tariff structure of each utility, and between public
and vended water (see figure 5.14). Where there are high operational costs, typically driven by
the costs associated with pumping water, average tariffs are higher where gravity-fed average
tariffs are lower. There is no mechanism of cross-subsidy across utilities. At the lower bands
of the tariff structure, equivalent to consumption of 40 liters per person per day, tariffs are just
below Br 1 per cubic meter (US$0.05) on average. For a household consuming at this level, the
annual per capita spent is around Br 60 per year (approximately US$3.6).6,7
Actual expenditure in urban areas by quintile indicates that even the poorest are paying more
than Br 60 (approximately US$3.6) per person per year. Though it is not possible to estimate
the volume of water being purchased, households with piped water on premises spent less per
person than households that have to fetch water from a public source and much less than
households that had to buy from vendors (figure 5.15). This holds true across all consumption
quintiles and points to the actual ability, if not willingness, of poor households to pay for water.
It also points to the obvious financial benefits of being connected to a utility, particularly given
that households with piped water on premises are likely to use more water than those without.
Extending utility water supply to all households could reduce the amount that poor, unconnected
households pay for water.
Figure 5.13: Total Expenditure per Year by Urban Households on Water, by Wealth
Quintile and Source in Ethiopia, 2011
120
100
80
Br (millions)
60
40
20
0
Poorest Poorer Middle Richer Richest
Wealth quintile
Piped to premises Public stand post Private vended water
Source: HICES 2011.
Maintaining the Momentum while Addressing Service Quality and Equity 93
Figure 5.14: Annual Water Bill for Households Consuming 6 m3 of Water per Month in Ethiopia
6
5
4
US$
3
2
1
0
Dessie
Merawi
Woldia
Arerti
Hawassa
Sendefa
Kombolcha
Kuy
Modjo
Meki
Sebeta
Debark
Alem Tena
Yirgachefe
Sawla
Muk Turi
Fenoteselam
Haik
Dilla
Negelle Borena
Adigrat
Areka
Axum
Addis Kidam
Debre Sina
Debre Tabor
Kemissie
Tililli
Yejube
Debrebirihane
Bedele
Asella
Butajira
DDWSSA
Debrework
Gondar
Halaba
Holeta
HWSA
Mersa
Batu
WTWSSE
Sululta
Burayu
Dukam
Shashemene
Bishoftu
Ambo
Arsi Negele
Alamata
Burie
Lalibela
Woreta
Wukro
Gore
Woliso
Metehara
Rama
Dangela
Adet
Dejen
Addis Zemene
Debremarkos
Haramaya
Fiche
Source: IBNET.
Note: Source of water is through a household or shared yard tap.
Figure 5.15: Annual Average per Capita Expenditure, by Water Source in Urban Areas
in Ethiopia, 2011
1,200
991
1,000
800 731
Br (millions)
600
500
400 361
310
217 200
200 142 151
87 95 95 111
62 76
0
Poorest Poorer Middle Richer Richest
Wealth quintile
Piped to premises Public stand post Private vended water
Source: HICES 2011.
These results reinforce the argument that it is the connection process, rather than affordability,
that is the real barrier to equitable access. While there are no consolidated sources of
connection charges, the qualitative work undertaken for this study in urban areas raises three
barriers for those wanting to connect. First is a connection charge, usually around Br 500.
Second is that utilities require people hooking up to pay the cost of connecting pipe work. Third
are the nonfinancial transaction costs of connecting linked to the time and social capital that
people have to put into getting a connection (see case study in box 5.1). With connection
charges trumping affordability as a barrier to hooking up, greater attention should be paid to
incentivize utilities to hook people up rather than the current focus on keeping tariffs low.
94 Maintaining the Momentum while Addressing Service Quality and Equity
Access Disparities by Service Quality Along Service Delivery
and Results Chain
The service delivery and results chain for urban water supply is examined to see what differential
benefits accrue to the wealthier (T60) compared to poorer (B40) households (see figure 5.16).
The section concludes by presenting what this means for the SDG baseline for the urban water
supply subsector.
Accessibility of water is the primary divider in urban areas, increasing both direct and indirect costs
for poorer households. In urban areas two factors measure the differential access between
wealthier (T60) and poorer households (B40). First is whether households have access to piped
water on premises and, as a result, lower costs per cubic meter, discussed in the previous
subsection. Second is the time they take to fetch water. In urban areas of Ethiopia both these
factors show large differentials, but piped water on premises is the bigger divider with only a quarter
of poorer households (B40) having piped water on premises compared to just under 90 percent for
the households in the T60. Only 9 percent of wealthier urban households spent over 30 minutes
fetching water compared to over 40 percent of poorer households. Most of the remaining burden
of fetching water in urban areas therefore falls to women and girls from poorer households.8
Availability and sufficiency of water are better for those who walk to the source. Availability is an
important criterion for assessing drinking water service levels. This is the only factor in the
service delivery chain in which there is an inversion of advantage: poorer households report that
their primary source of water was not available for at least one full day in the past two weeks.
However, this differential is largely because poorer households are much more likely to fetch
their water from a source outside their compound. What it does signal is that piped water supply
to premises suffers from frequent outages, highlighting the need to improve service levels.9
IBNET10 data on continuity of supply, an upper bound for availability of water from utilities, are
reported to be 18 hours out of 24. Utilities also report supplying an average of only 30 liters
per capita per day. Neither of these indicators are strongly driven by town size.
Quality of water at source was the second big divide in urban areas. By far the most common
sources of water used by households across urban areas are piped water on premises
Figure 5.16: Disparities Driven by Relative Wealth along Service Delivery and Results Chain in Ethiopia, 2016
Access to piped Quality of
water on premises, water at source,
88% 85% low risk Diarrhea in
children under 5,
Time to source, 1%
91%
≤ 30 min. Treatment of Stunting in
T60 water, children under 5,
Availability of 16% 14%
water,
58%
The larger the disparity,
the further apart
Availability of
water,
34% Treatment of Stunting in
water, children under 5,
B40 16% 14%
Time to source,
59% Diarrhea in
≤ 30 min. children under 5,
1%
Access to piped Quality of
water on premises, water at source,
25% 15–46% low risk
Sources: Access to piped water on premises: DHS 2016; availability of water: ESS 2016; diarrhea and stunting: DHS 2016; quality of water: ESS 2016; time to
source: DHS 2016; water treatment: DHS 2016.
Note: B40 = bottom 40 percent of wealth quintile; T60 = top 60 percent of wealth quintile.
Maintaining the Momentum while Addressing Service Quality and Equity 95
Figure 5.17: Water Quality in Addis Ababa, Figure 5.18: Main Source of Household Drinking
Secondary Towns, and Small Towns in Ethiopia, Water in Urban Areas in Ethiopia, 2016
2016
70
63
100
60
90
80 50
70
40
60
Percent
Percent
50
30
40
30 20
12 13 11
20
10
10
1
0 0
Addis Ababa Secondary towns Small towns Piped to Piped to Public tap Bottled All other
premises neighbor or kiosk water sources
E. coli <1 E. coli 1–10 E. coli 11–100 E. coli >100
Source: DHS 2016.
Source: ESS 2016 (Water Quality Survey).
Note: SDG = Sustainable Development Goal.
(including to neighbor) and piped water at public taps (see figure 5.17). Together, these account
for 89 percent of primary drinking water sources (figure 5.18) While water from both these
source types was contaminated in at least half of cases surveyed, there were very large
differentials across geography. Water quality in Addis Ababa (only 15 percent of source
contaminated with E. coli) was much better than in other large urban areas (54 percent of
sources contaminated), which in turn was far better than small towns (85 percent of sources
contaminated) (see figure 5.19).
Only by a small proportion of households treated water, even in urban areas. The DHS 2016
reports that fewer than 12 percent of urban households treated water. While there is a
differential between the proportion of wealthier (T60, 16 percent) and poorer households (B40,
6 percent) treating water, the more significant point is that nearly one-third of households in the
wealthiest quintile do so. The main forms of treatment in urban areas are boiling water (3 percent)
and adding chlorine tablets (7 percent).
Implications of Service Quality on the SDG Baseline
The SDG baseline for safely managed urban drinking water is estimated to be 38 percent, and
the baseline for a basic service of water supply in urban areas is estimated at 71 percent (see
figure 5.20). Water quality and water availability will be primary challenges to improving access
to safely managed water in urban areas. Addressing both will require significant investment in
water treatment, reducing NRW, and increasing water production. This is especially the case for
utilities that serve secondary cities and small towns.
This section has also highlighted the challenge of ensuring equity in urban water supply. In
urban areas there are large differences between the services experienced by wealthier
versus poorer households. Without proactive and progressive realization of access to
safely managed services for all, poorer households will continue to (a) be less likely to
have piped water to premises; (b) spend more time fetching water; (c) receive a worse
quality of water; and (d) therefore, suffer the consequences of higher prevalence of diarrhea
and malnutrition.
96 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 5.19: E. Coli Risk Levels at Point of Collection by Urban Water Supply Type in
Ethiopia, 2016
100
90
80
70
60
Percent
50
40
30
20
10
0
p
e
n
k
er
es
l
k
g
g
er
l
el
el
ta
an
ol
io
os
rin
rin
at
w
at
is
w
eh
ct
ic
lt
ki
w
sp
em
sp
w
g
lle
g
bl
al
or
er
du
ed
du
ce
co
sm
ed
pr
d
pu
l/b
at
te
ttl
rfa
ed
d
w
ct
el
on
er
ec
er
Bo
ith
te
Su
w
te
ct
d
at
at
ec
ot
d
tw
pe
ro
te
be
w
w
pe
Pr
ot
np
ro
in
ar
Pi
Tu
d
Pi
Pr
Ra
np
pe
C
U
U
Pi
E. Coli <1 E. Coli 1–10 E. Coli 11–100 E. Coli >100
Source: ESS 2016 (Water Quality Survey).
Figure 5.20: Estimates of Safely Managed Drinking Water in Urban Areas in
Ethiopia, 2016—SDG Methodology
SDG ladder
100 Elements of safely managed 2
3
23
80
60
35
Percent
96
40
73 71
20 43
38 38
0
Improved Improved within Improved Improved Improved Safely managed
30 minutes on available free of drinking water
roundtrip premises when needed contamination services
Surface water Unimproved Limted service Basic serivce Safety managed
Source: ESS-WQT 2016.
Note: SDG = Sustainable Development Goal.
Maintaining the Momentum while Addressing Service Quality and Equity 97
Kechene Transfer Station, Addis Ababa.
© Chris Terry/World Bank
98 Maintaining the Momentum while Addressing Service Quality and Equity
Urban Sanitation Subsector Analysis
National Status and Trends
Between 2000 and 2005 there was a dramatic improvement in onsite sanitation coverage of
urban areas, despite the lack of a clear strategy, but this has not been sustained over the last
decade (see figure 5.21). As in rural areas, there was a significant reduction in open defecation,
from 29.87 percent to 12.68 percent. However, unlike in rural areas, there was a significant
uptake of improved latrines, from 1.88 percent in 2000 to 44.24 percent in 2005. But the lack
of continuation of this positive trend is a strong indication that services have not been able to
keep up with growing urbanization. In addition, while data are still limited, the number of public
and communal latrines in urban areas fall far short of demand, leaving many low-income
people without latrine services.
Latrine coverage does not provide a complete picture of whether sanitation is being safely
managed in urban areas. The lack of appropriate data hampers the analysis of the effectiveness
of sanitation systems beyond simply household containment of fecal waste. However
inadequate management of fecal waste across the service chain in densely populated areas
is having an impact beyond just the household level, causing the pollution of urban rivers and
water bodies (see figure 5.22).
Government data show that in 2011, 55 percent of all latrines in urban areas were shared
by more than two households (see figure 5.23). Interestingly, the percentage of shared
latrines is very similar between those households using unimproved and improved
latrines. The 2016 DHS estimates that 60 percent of households using improved latrines
in urban areas are sharing, and more than half of these are sharing improved pit latrines
(see figure 5.24).
Figure 5.21: Urban Sanitation Coverage in Ethiopia, 2000–16
100
90
80
70
60
Percent
50
40
30
20
10
0
2000 2005 2011 2016
Improved Unimproved Open defecation
Source: DHS., 2000–2016.
Maintaining the Momentum while Addressing Service Quality and Equity 99
Figure 5.22: Sanitation Service Chain in Ethiopia
Reuse and
Containment Emptying Transport Treatment
disposal
Safe reuse and disposal of fecal wastes
Unsafe discharge of faecal wastes
Sewerage Septic tanks Other improved Unimproved Open defecation
Source: DHS.
Figure 5.23: Share of Improved and Unimproved Private and Shared Latrines in
Ethiopia, 2011
45%
55%
Shared latrines Private latrines
Source: WMS 2011.
100 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 5.24: Urban Sanitation Coverage with Shared Latrines in Ethiopia, 2000–11
100
80
60
Percent
40
20
0
2000 2005 2011
Improved: private Improved: shared Unimproved: private
Unimproved: shared Open defecation
Source: WMS, 2000–2011.
Shared latrines are more prevalent in larger towns and among tenant renting
accommodation. A logit regression analysis was undertaken to examined variables that
may be correlated with increasing or decreasing likelihood that households share toilet
facilities (see appendix F for details). The results indicate that households were more
likely to share toilet facilities in larger towns than in small towns. Households were
significantly less likely to share toilet facilities when they owned rather than rented the
house they lived in.
Households in the highest urban consumption quintile were less likely than other households
to share toilet facilities. However, for other consumption quintiles there was not a significant
correlation with shared use of toilet facilities. The variables for education level, gender of
household head, and even use of an improved toilet facility were not significantly correlated
with shared use of toilet facilities. The results of this regression suggest that it would be worth
investigating further the relations between tenure status of household and the sharing of toilet
facilities.
Households with greater numbers of household members were also less likely to share toilet
facilities with other households. The squared function of household size was examined in a
separate model but was not found to be significant. This last result requires further investigation
to understand the relation between household size and sharing of toilet facilities.
There is no clear policy regarding urban sanitation; however, the sector documents state
that households are responsible for building and managing their own latrine facilities. As
a result of this policy direction, public investment in containment has been very low with
the exception of communal and public latrines and poor quality septic tanks to service
condominium housing. The policy does not clarify how to support poor households to build
latrines or connect to sanitation services along the service chain. There is also currently
no policy directive to motivate or enforce land and property owners to provide adequate
sanitation facilities to their tenants.
Maintaining the Momentum while Addressing Service Quality and Equity 101
Access Disparities by Geography and City Population
Urban sanitation coverage varies between towns in different regions (see figure 5.25). To
analyze regional variations in urban sanitation coverage, urban centers are clustered into four
groups.11 Sanitation coverage in Addis Ababa is the highest among, and is the only city with a
municipal sewerage system, even though this serves only 10 percent of the city’s population.
The coverage in the chartered cities is similar to that of Addis, with over 70 percent of
households having access to an improved latrine. Coverage in the towns and cities in the
agrarian and emerging regions is notably lower, with considerable open defecation still taking
place in urban centers in the emerging regions.
Unsurprisingly, Addis Ababa represents the single largest urban challenge in Ethiopia, with
9 percent of all unimproved latrines and 4 percent of all households that practice open
defecation in urban areas (see figure 5.26). However, the sheer size of the urban population
in the large regions and the relatively poor coverage mean that most households with
unimproved latrines (69 percent) and that practice open defecation (61 percent) in urban
areas are across these four large regions.
When Addis Ababa is excluded, there is no significant difference in the sanitation coverage
between towns with different population sizes (see figure 5.27). Open defecation remains
highest in the secondary towns,12 which are expected to expand significantly in the coming
years. This can be explained by the large new and transient population moving to these
areas for job opportunities. As demonstrated by regression analysis, as towns get larger,
households tend to increase the sharing of toilet facilities. Households living in Addis Abba
and regional capitals are almost three times more likely to share toilet facilities than
households in smaller towns.
Despite relatively similar patterns of coverage, many factors will impact the strategies taken to
address these challenges in coming years, including population density and growth, water
supply, and capacity of institutions. Tools that could help towns address sanitation challenges
include developing sanitation investment plans, and setting out institutional arrangements and
management of service delivery models.
Figure 5.25: Trends in Access to Urban Sanitation across Regional Groups in Ethiopia,
2000 and 2016
100
90
80
70
60
Percent
50
40
30
20
10
0
2000 2016 2000 2016 2000 2016 2000 2016
Addis Ababa Chartered cities Agrarian regions Emerging regions
Safely managed Improved Unimproved Open defecation
Source: DHS. 2000 & 2016.
102 Maintaining the Momentum while Addressing Service Quality and Equity
Figure 5.26: Share of Total Urban Population, People with Unimproved Latrines, and
Practicing Open Defecation in Ethiopia, 2016
Total urban
population
Unimproved
latrines
Open
defecation
Addis Ababa Chartered cities
Large regions Emerging regions
Source: DHS 2016.
Figure 5.27: Access to Sanitation in Urban Areas by City Population in Ethiopia, 2007
60
50
40
Percent
30
20
10
0
Addis Ababa 100,000–350,000 50,000–100,000 < 50,000
Improved sanitation Unimproved sanitation
Open defecation
Source: Housing and Population Census 2007.
Maintaining the Momentum while Addressing Service Quality and Equity 103
Access Disparities by Poverty
Unlike in rural areas, where wealth does not appear to be a key factor in determining sanitation
access levels, in urban areas wealth is a driver of sanitation access. Only 5 percent of the
richest quintile practice open defecation in urban areas, compared to 45 percent of households
in the poorest quintile. While the percentage of improved latrine is much greater in urban
areas, most improved latrines are owned by the richest quintile (see figure 5.28).
Wealth appears to have less impact on whether households have a shared or private latrine
(see figure 5.29). Some variations are seen, such as only one in five households in the B40
with improved latrines have a private latrine compared to half of households in the T60.
However, the split of shared and private for all wealth groups with unimproved latrines is
approximately half and half.
Figure 5.28: Urban Sanitation Coverage by Poverty Quintile in Ethiopia, 2005 and 2016
100
90
80
70
60
Percent
50
40
30
20
10
0
2005 2016 2005 2016 2005 2016 2005 2016 2005 2016
Poorest Poorer Middle Richer Richest
Wealth quintile
Safely managed Improved Unimproved Open defecation
Source: DHS 2005 and 2016.
Figure 5.29: Share of Private Latrines by Wealth Quintile in Ethiopia, 2011
100
80
60
Percent
40
20
0
Poorest Poorer Medium Richer Richest
Wealth quintile
Improved: private Improved: shared
Unimproved: private Unimproved: shared
Source: WMS 2011.
104 Maintaining the Momentum while Addressing Service Quality and Equity
Access Disparities by Tenants Compared to Home Owners
Nearly two-thirds of urban residents live in rented accommodation, with privately rented
households constituting the largest and growing group, but there is an ongoing change to the
structure of the housing and rental market in urban areas. Kebele housing is on the decline due
to GoE’s ambitious condominium construction program, but it made up 24 percent of housing
in Addis Ababa in 2007 and slightly below 20 percent, on average, across all cities in 2007.
The construction of condominium houses aims to replace poor quality kebele housing with
more robust housing stock, which in theory should benefit the poorest households. In the first
phase of the Integrated Housing Development Program (IHDP), 244,436 units were completed,
170,000 of which were in Addis Ababa, and during the current phase of the program, the
government plans to build 50,000 units per year in Addis Ababa.
However, the World Bank Urbanization Review (2016) finds that for the bottom third of
households, IHDP condominiums are not affordable. As a result, poorer households use them
to generate income by renting them to wealthier households, creating a new breed of relatively
poor landlords. The removal of kebele housing in the center of Addis Ababa and other cities
has forced an increasing number of poorer households to live on the peripheries. These
households rent from private landlords and farmers in peri-urban areas, creating yet another
new group of landlords.
As demonstrated by the previous regression analysis, those living in rented accommodation
are significantly more likely to have a shared latrine irrespective of whether it is improved or
unimproved. This is even though the sanitation coverage patterns in urban areas looks very
similar for both households that own and households that rent their properties (see figure 5.30).
At the national level, of households that own their property and have access to an improved
latrine, 71 percent have private latrines and 29 percent are shared. This is compared to
23 percent private latrines and 77 percent shared latrines among households that rent their
property and have an improved latrine. A similar pattern can be observed in house owners and
tenant households with unimproved latrines.
A World Bank study on urban sanitation across ten towns and cities finds that 16 percent of
condominium residents surveyed were using dry pit latrines because their indoor flush toilets
were not functioning. The problems were related to poor quality plumbing installations, badly
Figure 5.30: Sanitation Coverage among Urban Households Owning or Renting Properties in Ethiopia, 2011
a. Property ownership b. Rental property c. Property ownership d. Rental property
Improved Unimproved Open defecation Improved: private Improved: shared
Unimproved: private Unimproved: shared
Open defecation
Source: WMS 2011.
Maintaining the Momentum while Addressing Service Quality and Equity 105
constructed or undersized septic tanks, and low water pressure. Sanitation facilities do not
appear to have been adequately planned and effectively implemented in Ethiopia’s new
generation of housing infrastructure.
Landlords and tenants are less inclined to invest in building a private latrine. For household
renting from kebele councils, major renovations by tenants are not currently permitted. Tenants
of private landlords also choose or are not incentivized to make repairs or upgrade household
basic infrastructure for fear of increased rents. There is currently no regulation that forces
landlord to rent houses with private sanitation facilities.
Sanitation Solutions across the Service Chain
While the problems of open defecation and unsafe containment remain significant in urban
areas, policy makers in sanitation infrastructure and services in urban areas need to look
beyond conventional on-site sanitation technologies to address the whole sanitation service
chain (see figure 5.31). Fecal sludge13 is often accumulated in poorly built latrine pits, and then
discharged directly into storm drains, open water bodies or the ground, or manually removed
and dumped into the neighborhood or the wider environment.
Ethiopia has limited large-scale sewerage and treatment infrastructure. The only sewerage
networks are in Addis Ababa and manage across three catchments: Akakai, Kality, and Eastern.
Reception facilities, such as Addis’s treatment plants in Kaliti and Kotebe, do not have adequate
capacity to deal with the city’s volume of sludge. The World Bank has financed the expansion
of the Kality sewerage system to add capacity of 90,000 cubic meters per day, once completed
in late 2017. A further 15 decentralized WWTPs have recently been completed or are still under
construction and will come online in 2018. These will provide a conveyance and treatment
capacity of 60,500 cubic meters per day.
Conventional sewers are not the solution in many urban centers due to their high cost, reliance
on large volumes of water, and challenges of installation in densely populated and unplanned
settlements. As a result, the GoE’s Integrated Urban Sanitation and Hygiene Strategy (2017)
sets out a new vision for urban sanitation infrastructure and services, which emphasizes
achieving safe wastewater management. The strategy combines the traditional approach of
improving existing on-site and sewer-based solutions, with fecal sludge management services,
investing in more decentralized WWTPs, and introducing wastewater reuse.
To date there has been limited investment in these alternatives, resulting in a lack of
appropriate desludging services, as well as limited infrastructure to facilitate treatment
of wastewater. Only a limited number of municipalities have vacuum trucks to desludge
latrines and septic tanks, while fleet management and operation is patchy, and mechanical
failure is common. For example, AAWSA owns 104 vacuum trucks and regulates a fleet of
58 private vacuum truck operators. Recent World Bank Group analysis (2016) finds only
62 percent of AAWSA’s trucks were functional. More worryingly sludge is mostly released
into the environment without adequate treatment due to the absence of reception
facilities.
Figure 5.31: Sanitation Service Chain
Capture Storage Transportation Treatment Reuse/disposal
106 Maintaining the Momentum while Addressing Service Quality and Equity
Box 5.2: Accountability for Urban Sanitation Service Delivery in Addis Ababa
In Addis Ababa, there is no formal accountability between citizens, AAWSA, and local
administration because the board members are all government representatives. However,
AAWSA established a customer forum, in which representatives of AAWSA branch offices
and subcity offices and customers meet quarterly. The arrangement has provided some
Water customers reception at Gulele Branch, AAWSA.
© Chris Terry/World Bank
box continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 107
Box 5.2: Continued
degree of accountability among the different groups, but it has still some limitations.
The main limitation is that the forum cannot pass binding resolutions and can be interpreted
differently by the groups. Another major limitation is that it focuses on service delivery
routine issues and neglects broader strategic issues, such as on how to address poor
families and land management issue.
In the case of Addis Ababa, the separation of roles between the utility and the local
administration is clearly delineated because of AAWSA branch offices’ accountability
(responsible for operations and service delivery) to the AAWSA head office, and subcities’
accountability to the municipality. The structure of Addis Ababa city, which is organized as a
region, also forces division of roles in a clearer way than in smaller towns. The role of residents
is reflected in their representatives on the city council.
There is conflict of interest between the woredas (health stations), which want affordable
solutions for public health, and AAWSA, which focuses on addressing large infrastructure
projects (such as sewerage) and neglects pro-poor solutions. There is a perception from both
sides that they are pushing challenging issues to the other party. The lack of the woredas’
clear understanding of AAWSA policies leads to further misunderstanding.
Accessing land is very challenging in Addis Ababa, and woredas are unwilling to change
policies or administrative rules to address urban sanitation. In addition, AAWSA does not
seem inclined to change its service delivery model to address the urban poor. If effective
accountability mechanisms are not established, the utility will continue with its priority of
infrastructure-driven approaches. Neglecting more diverse and pro-poor sanitation solution
will lead to further marginalization of poor families.
There is a need to improve the institutional framework for urban sanitation, create policy
integration among the different actors, and create awareness on the need for policy reform.
Further improvements in accountability can be achieved through the formalization of the
customer forum. There is also a need to establish formal links between AAWSA branches and
subcities with a proper framework to engage solution-targeted dialogue. Addis Ababa could
develop a citywide forum, including municipalities, to harmonize interests and achieve
sustainable solutions for all and create branch-level, customer-focused platforms.
Financing plans should be designed to support pro-poor interventions and create incentives
for increased accountability to poor customers. Better managed shared latrines, credit
mechanism for building latrines, and incentives for landowners to build latrines will improve
service delivery for poor households. The introduction of these strategies will require a
combination of incentives to utilities and municipalities, and the establishment of performance
targets and monitoring.
Source: Yemane and Defere n.d.
108 Maintaining the Momentum while Addressing Service Quality and Equity
Sanitary suppliers, Merkato, Addis Ababa.
© Chris Terry/World Bank
Maintaining the Momentum while Addressing Service Quality and Equity 109
Most of networked sanitation services are not available or affordable to the poorest communities
in urban areas. Utilities target households they perceive are able and willing to pay. Furthermore,
existing technologies are unable to reach densely populated slum areas where poor households
reside, and when they can pay, often the quality of the latrine means a risk that the desludging
will damage the latrine. Hence, the AAWSA strategy for these groups has been to construct and
outsource mobile and fixed public and communal latrines in low-income and public areas.
These have the potential to create income and job opportunities for small enterprises.
There is a need to shift to a new paradigm that addresses sanitation across whole cities. Such
a shift would need to include systemic policy and institutional transformation, and create a
framework that promotes a range of technologies and solutions. Cities and towns would need
to develop investment strategies addressing challenges and growing demand across the
sanitation service chain in different urban environments and for different wealth groups. Such
an approach would also require responding to the lack of reliable water supply within cities. To
set up such mechanisms along the service chain and provide the institutional system to carry
it requires clearly defined and organized delivery mechanisms, as well as mobilization and
allocation of adequate fiscal resources.
Role for the Private Sector
Despite a huge market opportunity, private sector participation in the delivery of sanitation
products and services in urban areas is currently limited. Water utilities and local governments
have not harnessed the potential of the private sector to improve the efficiency of sanitation
service provision. This is in part because many key elements to create a conducive enabling
environment for private sector participation are still not in place.
The private sector, from large to micro-business, has opportunities across the sanitation service
chain in urban areas (see figure 5.32). In relation to the containment, the private sector is
producing and selling latrine pans, but these are mostly priced out of reach of the poorest
section of society. This goes some way to explain why the richest quintiles have most of the
improved latrines in urban areas. The private sector has yet to fully take on the challenge of
innovating a lower cost latrine option for poor households to tap the growing need for on-site
Figure 5.32: Opportunities for Private Sector Engagement across the Service Chain in Ethiopia
Access to Emptying Treatment Disposal
toilet and transport or reuse
Residential and Collect and deliver Fecal sludge Organic
institutional toilets fecal sludge treatment matter
Retail stores and Biogas
Call center Water
public toilets plant
Source: CGIAR, IWMI, and World Bank.
110 Maintaining the Momentum while Addressing Service Quality and Equity
Box 5.3: Example Case of a Household in a Densely Populated and Inaccesible
Area’s Attempt to Empty Latrine Facilities
The case study documents the process of accessing a pit emptying service from AAWSA
branch office. Girma Abebe and his family live in a compound with eight households that share
a latrine in poor working condition. Due to the large number of users, the latrine fills quickly
and needs emptying to remain functional. The road leading to the compound is narrow and
difficult to access it with a conventional vacu-truck.
AAWSA is responsible for the provision of fecal sludge management services including pit
emptying. The Gulele Branch Office (under Woreda 3 Administration) is the service provider.
There are also private vacuum truck operators, but their primary focus is businesses and
conventional houses. The Health Station provides health services and hygiene promotion to
Girma Abebe, Addis Ababa.
© Chris Terry/World Bank
box continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 111
Box 5.3: Continued
Shared latrine, Addis Ababa.
© Chris Terry/World Bank
the residents. With one HEW supporting 500 households to access water supply and
sanitation service, households can go directly to the branch office and apply for fecal sludge
services, but it can take some time. The service is provided more quickly if the family has a
letter from the health station stating the urgency of the situation. The household contacts
HEW, HEW facilitates the paperwork in the health station, and the application is sent to the
branch office. The household makes the payments and the branch will send vacuum trucks to
empty the latrine.
box continues next page
112 Maintaining the Momentum while Addressing Service Quality and Equity
Box 5.3: Continued
The family applied through the correct channels to have their latrine emptied. They obtained a
supporting letter from the health station and went to the branch office in 2015 and paid the
charge for the service. However, the latrine was not emptied due to its inaccessibility. In 2016,
the family reapplied for emptying and paid the fee again. After it was identified that AAWSA’s
vacu-trucks could access the latrine to empty it, the issue was forwarded to the woreda.
The woreda HEW and health office came to assess the situation and agreed to facilitate
construction of a new latrine. They attempted to allocate land, which was initially was taught
to be public land, but was found to be private, and they still look for viable solution. The
likelihood of achieving a sustainable solution is very low. It requires introducing a new service
delivery model, or encouraging other service providers to enter the market. It also depends on
the woreda to give priority on its policy of land allocation to move from revenue-based approach
toward service provision. That seems at present unlikely without high-level policy intervention.
Source: Yemane and Defere n.d.
sanitation solutions among low-income urban communities. Some plastic latrine pans are
starting to emerge in the market, but their production and marketing has not been done to scale
to date.
Small and medium enterprises have opportunities in both managing public latrines and in
providing services for emptying and transportation of domestic waste. Examples of private
engagement in these areas include the private management of public latrines built by AAWSA.
However, the long-term viability of these businesses will depend on consumer demand and
willingness to pay, as well as the enterprises developing business models that might include
provision of complementary products and services. Due to these businesses relying on the
wider service chain, the availability and cost of complementary services in the service chain
will also impact their long-term success.
The private sector has the capacity to innovate to reduce costs and find solutions to service
provision for the poorest households. Existing large trucks are not suitable for emptying pits
and emptying and transporting fecal sludge from densely populated low-income areas. There
is a need to introduce new technologies that would be better serve and provide viable business
opportunities to this market segment. Currently the private sector is not prepared to take
the risk of investing in such research and development in an untested and infant market.
Partnership between the public and private sectors on such research offer opportunities to
develop solutions for low-income households.
While the situation is improving, the public sector lacks the skills to engage with private sector
in an effective manner. For the government to effectively facilitate these market opportunists,
contract management skills need to be developed in municipalities and utilities, and the legal
frameworks for engaging private partners have to be clarified and refined. For example, there
is currently no policy for effective regulation of the removal and treatment of fecal sludge. While
private vacuum trucks operate side by side with the utility’s trucks, investing in such a business
is a risk for entrepreneurs if market regulation is unclear.
Another major challenge is the difficulty of accessing seed money for startup activities for
small operators. This issue is a serious constraint because small operators lack both
Maintaining the Momentum while Addressing Service Quality and Equity 113
Figure 5.33: Urban Sanitation Coverage in Ethiopia, 2016—SDG Methodology
SDG ladder
100
7
Urban sanitation coverage (%)
80
43
60
40
35
50
20
16 14 16
? ?
0 0
Population Population Population Safely Population Safety Population
using using using disposed using transported using
improved- private private on-site or piped to and treated safely
type improved improved treated sewer off-site managed
sanitation sanitation on-site off-site sanitation
facility sanitation services
SDG methodology
Safely managed At least basic Limited Unimproved Open defecation
Source: World Bank calculation based on DHS 2016.
Note: SDG = Sustainable Development Goal; ? = figure based on best estimate using existing data.
adequate private equity and the ability to mobilize external financial resources. While some
progress has been made in freeing up private capital through increasing liquidity and
introducing guarantees to reduce the risk to the bank, in many case the banks’ collateral
requirements, particularly cars and houses, are still too stringent. The most success to date
in mobilizing finance for new businesses has been through microfinance lenders lending to
new businesses organized by government agencies. However much more needs to be done if
private enterprises of different scales are going to make a meaningful contribution to sanitation
service provision in urban areas.
Implication of Achieving the SDGs Targets
The SDG targets and monitoring system reflects the progress required across the sanitation
service chain in urban areas. The status looks more encouraging compared to the rural SDG
assessment, however as discussed above the institutional and technological improvement
required to achieve safely managed sanitation access in urban areas are significantly more
complex (see figure 5.33). The SDG indicators in the urban context further highlights the
complexity of monitoring progress across the service chain.
114 Maintaining the Momentum while Addressing Service Quality and Equity
Notes
1. Unless otherwise stated, population figures in this report are taken from the Ethiopian
Central Statistics Agency. The Sub-Saharan average is from the World Bank World
Development Indicators (WDI). Urban population refers to people living in urban areas as
defined by national statistical offices.
2. Population between 100,000 and 350,000 people.
3. People fetching drinking water from plot or premises has risen from 1.2 million to
10.7 million between 1995 and 2015. People fetching water from standpipes or neighbors
has gone from 5.4 million to 7.1 million over the same period (WHO/UNICEF 2016).
4. DHS 2011 reports that women (72 percent) and girls (15 percent) are primary fetchers of
water in rural areas and in urban areas (women 69 percent and girls 8 percent) but over
60 percent urban households have access to water in their yard compared to less than
2 percent in rural areas. Female- and male-headed urban households have equal access
to water on premises (about 57 percent).
5. See IBNET’s website: https://www.ib-net.org/.
6. At 2011 exchange rates.
7. IBNET 2011 data for Ethiopia.
8. Data for access and time to fetch water form DHS 2016.
9. Data for availability from ESS 2016.
10. International Benchmarking Network for Water Supply and Sanitation Utilities.
11. Addis Ababa, the chartered cities of Dire Dawa and Harari, and urban centers in the large
regions and the emerging regions.
12. Secondary towns are a distinct group with a population between 100,000 and 300,000
people.
13. Fecal sludge is a highly variable mix of raw and partially digested feces and urine, along
with different amounts of contaminated wastewater, and in some places solid waste and
other materials.
References
Banerjee, S., Q. Wodon, A. Diallo, T. Pushak, H. Uddin, C. Tsimpo, and V. Foster. 2008. “Access,
Affordability and Alternatives: Modern Infrastructure Services in Sub-Saharan Africa.”
AICD Background Paper 2, Africa Infrastructure Country Diagnostic, World Bank,
Washington, DC.
WHO (World Health Organization)/UNICEF (United Nations Children’s Fund). 2016. “WHO/
UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygiene 2016
Annual Report.” WHO, Geneva. https://washdata.org/sites/default/files/documents
/reports/2017-07/JMP-2016-annual-report.pdf.
Wodon, D. A. 2007. Growth and Welfare Under Demographic Transitions and Economies of
Scale.
World Bank. 2014. Ethiopia Public Expenditure Review. Washington, DC: World Bank.
———. 2015a. Ethiopia Poverty Assessment 2014. Washington, DC: World Bank.
———. 2015b. Ethiopia Urbanization Review: Urban Institutions for a Middle-Income Ethiopia.
Washington, DC: World Bank.
———. 2016. World Bank Urbanization Review 2016. Washington, DC: World Bank.
Yemane Y., and E. Defere. n.d. “Learning Journeys Commissioned for the Ethiopia WASH
Poverty Diagnostic.” World Bank, Washington, DC.
Maintaining the Momentum while Addressing Service Quality and Equity 115
Shumba Bukeri, Mareko Woreda, SNNPR, cannot afford to pay for water from a community water point 200 yards from her house.
© Chris Terry/World Bank
Chapter 6
WASH, Nutrition, and Health
Inadequate water supply, sanitation, and hygiene (WASH) services can result in exposure to a
wide range of pathogens and cause many health problems. The ingestion of contaminated
water, food, or soil as a result of the unsafe management of human excreta, or poor personal
and domestic hygiene, provide routes of transmission for numerous microorganisms that can
cause diarrhea and other important infections. Despite the increase in access to WASH
services in Ethiopia, the poor quality of services provided have constrained the potential of
WASH services to contribute to improvements in health outcomes.
The under-five mortality rate in Ethiopia has decreased by 72 percent since 1990, when it was
205 deaths per 1,000 live births, to 59 deaths per 1,000 live births today (UNICEF/WHO/
World Bank 2015). This large drop in under-five mortality is the result of both preventive and
curative interventions. WASH interventions target preventing the spread and so burden of
disease experienced by people.
Dehydration from diarrhea is still ranked as the second leading cause of child mortality in
Ethiopia and persists as a significant public health problem.1 The prevalence of diarrhea has
halved from 24 percent to 12 percent from 2000 to 2016 (DHS 2000 and DHS 2016).
Neglected tropical diseases (soil-transmitted helminth infection, schistosomiasis, and
trachoma), for which inadequate WASH is a risk factor, also persist as public health problems
in Ethiopia. Studies in Ethiopia have reported an association between using an unimproved
water source and higher prevalence of childhood diarrhea, with children in households not
using an improved water source around twice as likely to experience episodes of diarrhea
(Godana and Mengistie 2013; Mekasha and Tesfahun 2003; Mihrete, Alemie, and Teferra
2014). However, while there is some good evidence that water quality is associated with
diarrhea, there are few studies assessing water availability (distance to source) as a risk factor.
There is evidence in the wider literature that open defecation increases the odds of children
under five having diarrhea. Children in households that practice open defecation were more
than twice as likely to have diarrhea as children from households using a latrine. In addition,
children from households that do not practice proper infant feces disposal have over twice the
odds of having diarrhea; in one urban setting, the presence of feces in the compound increased
the odds of children having diarrhea by nearly two times (Godana and Mengistie 2013;
Mihrete, Alemie, and Teferra 2014). It has also been found that children under five were up to
twice as likely to have diarrhea if their caregivers did not wash their hands at critical times
(Eshete 2008).
Malnutrition is an acute health risk and can also have long-term negative effects. Stunting
is a powerful risk factor for disease and death and is associated with 53 percent of
infectious disease related deaths in developing countries (Schaible and Kaufmann 2007).
Malnutrition can also have long-lasting wider negative effects, including on poor mental
development, impacting school achievement and future employment prospects. This risks
long-term disadvantages for affected individuals and negative impact on wider growth and
development goals.
Undernutrition still presents a significant problem, despite good progress since 2000. Diarrhea
and environmental enteropathy2 can lead to chronic problems with absorbing nutrients, leading
to stunting, wasting, and being underweight (see figure 6.1). DHS 2016 data show that among
under-five children, 38.4 percent, 23.6 percent, and 9.9 percent were stunted3, underweight, and
wasted, respectively. However, similar to the 2011 data, the DHS 2016 data do not report a
Maintaining the Momentum while Addressing Service Quality and Equity 117
Figure 6.1: Trends in Nutritional Status of Children under Age Five in
Ethiopia, 2000–16
a. Child stunting in Ethiopia, 2016
38%
of children under 5 are stunted
b. Nutritional status of children in Ethiopia, 2000–16
60
50
40
Percent
30
20
10
0
Stunting Wasting Underweight Global hunger
index scores
2000 2005 2011 2016
Sources: DHS; IFPRI Global Hunger Index database 2016.
substantial differential in stunting between B40 (43 percent) and T60 (37 percent) in rural areas.
While other environmental factors, most notably sanitation, are known to influence stunting
rates, the cumulative effect of factors clearly benefits wealthier more than poorer households.
Regions of Ethiopia show significant variation in the distribution of child stunting and children
being underweight, as shown in maps 6.1 and 6.2. There is a high prevalence of stunting and
underweight children in areas of both high and low water supply and sanitation coverage. This
is because there are many drivers for children being underweight and stunted, including
maternal nutrition; food availability and nutritional value of food intake; overall health; and
geographic and environmental factors such as access to water, sanitation, health, and
education services.
The negative impacts of poor WASH conditions and other external factors are, however,
concentrated among certain groups, reflecting broader structural inequities relating to poverty
and geography. Overall measures of exposure and susceptibility are positively associated.
118 Maintaining the Momentum while Addressing Service Quality and Equity
Map 6.1: Share of Children Stunted in Ethiopia, 2017
Eritrea
Yemen
Tigray Percent
Sudan
No data
15–25
26–35
Afar Djibouti
36–42
Amhara GULF
43–49
50–62
Benshangul Gumuz
Dire Dawa Somalia
Addis Ababa Harari
Gambella
Oromia
Somali
SNNPR
Kenya
Source: Sohnesen et al. 2017.
Map 6.2: Share of Children Underweight in Ethiopia, 2017
Eritrea
Yemen
Tigray Percent
Sudan No data
10–24
25–30
Afar Djibouti
31–37
Amhara GULF
38–46
47–65
Benshangul Gumuz
Dire Dawa
Addis Ababa Harari Somalia
Gambella
Oromia
Somali
SNNPR
Uganda Kenya
Source: Sohnesen et al. 2017.
Maintaining the Momentum while Addressing Service Quality and Equity 119
Figure 6.2: Exposure, Susceptibility, and Risk Indexes for Children under Five in
Ethiopia, 2011
a. Exposure index b. Susceptibility index c. Risk index
8
6
National
4
2
0
8
Index score
6
Rural
4
2
0
8
6
Urban
4
2
0
t
er
e
er
t
t
er
e
er
t
t
er
e
er
t
es
es
es
es
es
es
dl
dl
dl
or
ch
or
ch
or
ch
or
ch
or
ch
or
ch
id
id
id
Po
Po
Po
Ri
Ri
Ri
M
Po
M
Po
Po
M
Ri
Ri
Ri
Wealth quintile
Source: DHS 2011.
That is, those with the worst WASH conditions are also more vulnerable due to inadequate
health. Children with poor WASH conditions also suffer from poor access to health and nutrition.
This is true in rural and urban communities. These correlations between exposure and
susceptibility add to (and are likely caused by) the underlying difference in wealth and urban–
rural inequalities (see figure 6.2). More details of this are provided in appendixes I and J.
Regions of Ethiopia with the largest disparity in disease risk between the poorest (below
20 percent of the wealth index [B20]) and wealthiest (top 20 percent of the wealth index [T20])
quintiles are in Tigray and Addis Ababa. Areas with children at the highest risk index values are
concentrated in the southeast and northeast of Ethiopia, with children from Afar being
particularly vulnerable to disease. Panels a–c of map 6.3 show a finer scale spatial resolution
map of the disease risk index value distribution across children under five in Ethiopia. Areas
with the highest risk index values are concentrated in the southeast and northeast, while the
children with the lowest risk index values are concentrated in the west in the overall map
(panel a) and the top 60 percent (T60) of the wealth index population (panel c). For the below
40 percent (B40) of the wealth index children population, there are larger areas of the higher
risk index values (>7.25) in the north and south, and to a lesser extent in the center.
120 Maintaining the Momentum while Addressing Service Quality and Equity
Map 6.3: Risk Index Values in Ethiopia for Populations of Children under Five, 2011
a. Overall b. B40 C. B60
<6
6–7
7–8
8–9 Kilometers
>9 0 250 500
Source: DHS 2011.
Note: Maps are at 5 km2 resolution. B40 = below 40 percent of wealth index; T60 = above 60 percent of wealth index.
Figure 6.3: Relationship between Community-Level Access to Water or Sanitation Services and Stunting in
Ethiopia, 2011
a. Sanitation: Improved b. Sanitation: Other unimproved c. Sanitation: Open defecation d. Water: Access to improved water
5 55 50
4 50 5
45
3 45
2 40
Stunting=1
Stunting=1
Stunting=1
Stunting=1
40 4
1
35 35
0
30 3
–1 30
25
–2
20 2 25
0 0.25 0.50 0.75 1.0 0 0.25 0.50 0.75 1.0 0 0.25 0.50 0.75 1.0 0 0.25 0.50 0.75 1.0
(Primary sampling unit) (Primary sampling unit) (Primary sampling unit) (Primary sampling unit)
Source: DHS 2011.
Analysis shows water supply and sanitation coverage needs to reach an advanced level within
a community before stunting starts to reduce (see figure 6.3). Until fewer than 25 percent of
households within a community practice open defecation there is very limited impact on child
stunting rates. However once over 75 percent of the community stop defecating in the open,
significant improvements in stunting are observed. In the same way very little impact is seen
on stunting until more than 50 percent of households have improved latrines.
Maintaining the Momentum while Addressing Service Quality and Equity 121
Most concerning in the Ethiopian context, unimproved latrine coverage has very limited impact
on stunting, with only marginal improvements shown in communities with high coverage of
unimproved latrines. In addition, even high coverage of poor quality sanitation services has
very limited impact on stunting, compared to improved latrines. Therefore, there needs to be a
focus on ensuring households don’t build unimproved latrines and build improved latrines.
Significant improvements in stunting are observed only when access to improved water supply
reaches 70 percent, but prior to this point improved water access has a very limited impact on
stunting. The poor water quality data presented in this report make this finding unsurprising,
and reinforce the need to increase the quality of water for all households to realize the health
benefits. The insufficient protection even “improved” water sources provide against malnutrition
is aggravated by the extremely low level of point-of-use water treatment in the Ethiopia, which
has clear protective effects.
This analysis shows that increases in quality of services need to be combined with reductions
in inequality of access to water supply and sanitation services within a community. Although
Sustainable Development Goal (SDG) targets for universal “safely managed” WASH are
extremely ambitious, this analysis demonstrates that both universality and higher service
levels are outcomes that matter most for WASH interventions to contribute to wider human
health and development goals.
Notes
data
1. “Country Profile: Ethiopia,” accessed March 29, 2016,available from http://www.health
.org/print/4314.
2. Environmental enteropathy, also known as tropical enteropathy or environmental enteric
dysfunction (EED), is a condition or subclinical disorder believed to be due to frequent
intestinal infections.
3. Children whose height-for-age is less than two standard deviations below the median
(−2 SD) of the reference population are considered short for their age or stunted,
a condition reflecting the cumulative effect of chronic malnutrition.
References
Eshete, W. B. 2008. “A Stepwise Regression Analysis on Under-Five Diarrhoael Morbidity
Prevalence in Nekemte Town, Western Ethiopia: Maternal Care Giving and Hygiene
Behavioral Determinants.” East African Journal of Public Health 5 (3): 193–8.
Godana, W., and B. Mengistie. 2013. “Determinants of Acute Diarrhoea among Children
Under Five Years of Age in Derashe District, Southern Ethiopia.” Rural Remote Health
13 (3): 2329.
Mekasha, A., and A. Tesfahun. 2003. “Determinants of Diarrhoeal Diseases: A Community
Based Study in Urban South Western Ethiopia.” East African Medical Journal 80 (2):
77–82.
Mihrete, T. S., G. A. Alemie, and A. S. Teferra. 2014. “Determinants of Childhood Diarrhea
among Under-Five Children in Benishangul Gumuz Regional State, North West Ethiopia.”
BMC Pediatrics 14 (1): 1–9.
Schaible, U. E., and S. H. E. Kaufmann. 2007. “Malnutrition and Infection: Complex
Mechanisms and Global Impacts.” PLoS Medicine 4 (5): e115. doi:10.1371/journal
.
pmed.0040115.
122 Maintaining the Momentum while Addressing Service Quality and Equity
., A. A. Ambel, P
Sohnesen, T. P . Fisker, C. Andrews, and Q. Khan. 2017. “Small Area Estimation
of Child Undernutrition in Ethiopian Woredas.” PLoS ONE 12 (4): e0175445. doi:10.1371
/journal.pone.0175445.
UNICEF, WHO (World Health Organization), World Bank, and UN DESA (United Nations
Department of Economic and Social Affairs) Population Division. 2015. Levels and Trends
in Child Mortality 2015. New York: UNICEF.
Maintaining the Momentum while Addressing Service Quality and Equity 123
Mekonei Jare, 70 years old. Digna Koisha Humbo Kabele, Digana Fango Woreda, SNNPR.
© Chris Terry/World Bank
Chapter 7
Conclusions and
Recommendations
The Government of Ethiopia (GoE) has been successful at linking its decentralized generic
service delivery machinery with the sector policy direction, plans, and capacity to rollout basic
water supply, sanitation, and hygiene (WASH) services at an industrial scale. This has been
done with strong country leadership that directs both domestic public and overseas aid
resources well where WASH services are basic and public access (nonrivalrous, nonexclusive
goods). However, where WASH services have added value and a private dimension (rivalrous
and exclusive goods), progress on implementing the policy direction, particularly on cost
recovery, has been limited and the sector outcomes regressive, with wealthier households
disproportionately capturing the benefits of public expenditure.
The rollout of basic WASH services has been equitable across wealth groups albeit less
equitable across livelihood types. Basic water services in rural areas include public water
points (protected wells, springs, and boreholes). Basic sanitation and hygiene services have
been achieved through knowledge disseminated through health extension workers (HEWs)
across the country. Looking ahead, the challenge for basic WASH services is to improve the
quality while achieving universality.
Two priorities in rural water supply are improving water quality and reducing the time spent
fetching water. First, to ensure that rural water services deliver their potential health benefits
the microbiological quality of water needs to be addressed. This requires (a) improving
implementation quality to ensure that protected supplies are well constructed (e.g., with crack-
free masonry and grout seals); (b) site selection that minimizes sanitary risks (e.g., no latrines
or other sources of pollution nearby); (c) sanitary conditions at water points (e.g., keeping
animals away from water sources for domestic drinking water); (d) implementing regular water
testing protocols; (e) instituting controlled chlorination of improved sources; and (f) hygiene
education to encourage household management of safe water chains. Second, rural water
supply needs to deliver on the economic promise of freeing up people’s time by bringing
services closer to people’s homes. While 35 million rural people gained access to improved
water, only half this number are able to fetch water within half an hour. As a result, women, who
bear the brunt of the water-fetching burden, have not seen the full economic benefits from the
transition to improved water. In addition, the poor quality of water delivered has not resulted in
the expected health benefits.
Functionality of schemes continues to be a problem stemming from weaknesses in upstream
planning at regional level and financing of postconstruction support by woreda water desks.
A contributor to the lengthy water-fetching times is nonfunctional systems. In additional
to mechanical breakdowns, recent droughts have exposed the vulnerability of water points to
drying up. At the regional level, attention in the planning and design process is needed to
better match types of water intervention with hydrological or hydrogeological conditions. At the
woreda level, more operational budget is needed for water desks to backstop village and
scheme water management committees. This includes checking whether cost recovery
mechanisms are working and to facilitate the sourcing and fitting of spare parts when water
committees need help in keeping systems running.
The greatest challenges to achieving universality of basic services are in pastoralist and
agropastoralist areas. Across Ethiopia, woredas dominated by agropastoralist and pastoralist
Maintaining the Momentum while Addressing Service Quality and Equity 125
livelihoods were just over half as likely to have access to improved water as agrarian woredas.
Government programs targeted at the poorest areas, both from within the sector and broader
poverty reduction programs (such as the Productive Safety Nets Program (PSNP) and the Food
Security Program), have increased water access in food insecure agrarian areas. However, they
have been less successful in areas dominated by pastoralists and agropastoralists. Reasons
for this include (a) the community infrastructure funding under the PSNP public works component
has been too small to address the complex hydrogeological conditions in agropastoralist and
pastoralist areas; (b) both government and nongovernmental organization (NGO) water actors
have struggled to find adequate ground water sources to drill for; (c) alternative storage
technologies to collect rainwater run-off have been underdeployed (e.g., sand dams, underground
dams, infiltration galleries); and (d) the standard regional planning process has not been as
successful at engaging with agropastoralists and pastoralists as they have in agrarian areas.
In 2009 the GoE set up the Ministry of Federal Affairs principally to close the service and
capacity gap between large and emerging regions. As part of the recent rollout of the Millennium
Development Goal (MDG) special purpose grant the regions of Afar and Somali drew on capacity
in larger regions to set up drilling agencies. While this may be part of the solution, the same
larger regions are having difficulty delivering services to pastoralists and agropastoralists in
their own regions. This suggests that both the existing technologies and the service delivery
interface in pastoralist and agropastoralist areas need revisiting for water supply and sanitation
services. Addressing this gap, therefore, requires building further technical expertise in areas
with difficult hydrogeology. It also means finding ways for the decentralized service delivery
machinery to interface with pastoralist and agropastoralist communities, both to address their
specific needs and ensure they are a vocal stakeholder in finding solutions.
In view of the shift envisaged from point sources to piped schemes under the Growth and
Transformation Plan (GTP) II, the affordability of rural water services and cost-sharing
arrangements will need to be examined carefully. Evidence from national surveys and qualitative
studies suggests that affordability of rural water from piped schemes, particularly motorized
piped schemes, can be a real barrier for poorer households. The costs, which range from five
to 25 times that of urban utility water, partly explain the skewed distribution of access to piped
water in rural areas. As this shift is planned, careful attention needs to be given in the design
stage to keep recurrent costs down and so not to jeopardize the equitable goals with which
basic services have been rolled out in Ethiopia (see box 7.1).
Box 7.1: Rural Water Supply Recommendations
• Reduce microbiological contamination of rural water sources by (a) ensuring protected
sources are well constructed, sited, and managed to avoid contamination; (b) implementing
regular water testing protocols; (c) instituting controlled chlorination of improved sources;
and (d) promoting household management of safe water chains.
• Raise functionality rates of existing improved water sources to increase access rates and
reduce the travel time for fetching water.
• Improve siting of new water points to deliver time savings for fetching water, and, where
possible, extend existing piped schemes to provide public stand posts (bearing in mind
affordability).
• Further research how time-to-source relates to topography and invest in planning and
design skills to improve the matching of water supply technology with hydrological and
hydrogeological conditions.
box continues next page
126 Maintaining the Momentum while Addressing Service Quality and Equity
Box 7.1: Continued
• Address remaining geographic inequities by building further technical expertise in areas
with difficult hydrogeology, and develop planning methods that engage pastoralist and
agropastoralist communities.
• Specifically target woredas and kebeles with low levels of basic access across all regions.
• Harness government mechanisms, such as technical and vocational education and
training agencies (TVET) agencies and universities, to improve the availability of skilled
staff for recruitment into the civil service.
• Improve staff retention, especially at the woreda level, by ensuring staff members have
operational budgets to carry out their roles in backstopping rural water supply.
The two priorities for rural sanitation should be to improve the quality of latrines used across
Ethiopia and effectively target those households that were not reached in Ethiopia’s last
sanitation push. Without more universal coverage and a higher level of service provision, the
positive health benefits expected from improved sanitation will not materialize.
The health system needs to reinvigorate its efforts to address the next phase of sanitation and
hygiene promotion in Ethiopia. Progress in rural sanitation has benefited from the systematic
inclusion of sanitation promotion in the Health Extension Program (HEP); however, the slowing
of progress in recent years shows a fatigue within the system. This is partly due to the lack of
evolving communication messages within the HEP , as existing messages become redundant or
fail to influences new audiences. In addition, HEWs’ lack of knowledge on what constitutes
improved latrines and the negative impact of poor quality latrines have made unimproved
latrines an acceptable standard of progress for HEWs and the households they serve.
Moving the millions of households in rural areas up the sanitation ladder is going to require a
combination of demand- and supply-side approaches. Weak supply chains of sanitation
products and services, as well as supporting financing options, have meant households have
not had access to the technical or financial solutions required to move up the sanitation ladder.
Prioritizing the engagement and development of the private sector to provide products and
services will reduce the burden on the health system and create innovation and jobs in the
sanitation sector.
Analysis shows that when access to effective health care and education services are combined
with improved WASH services, more positive health outcomes have been achieved. Reducing
vulnerable children’s susceptibility to poor environmental condition and increasing access to
basic health care can reduce stunting rates and the cycle of poverty in which poor families are
locked.
While the last phase of Ethiopia’s sanitation and hygiene promotion in rural areas has been
delivered in a relatively equitable manner across wealth quintiles, there are a number of
geographic inequities. These are driven primarily by livelihood types, with a clear systematic
failure to effectively address sanitation coverage within pastoralist communities. While it is
clear that pastoralist communities’ coverage lags behind those of other areas, in terms of the
scale of the problem, significant efforts need to be placed in addressing the large numbers of
people without access to improved sanitation in Oromia; Amhara; and the Southern Nations,
Nationalities, and People Region (SNNPR).
Maintaining the Momentum while Addressing Service Quality and Equity 127
Although poverty has not been a significant barrier to improving sanitation, as the GoE
pushes for increasing the quality of latrines to higher service levels, poverty may increasingly
become a barrier to access. Strategies need to be put in place to ensure the poorest
households don’t fall behind as sanitation service levels increase and Ethiopia strives for
universal coverage.
Achieving the GoE and Sustainable Development Goal (SDG) targets will require strong and
sustained leadership and champions at all levels. It has been proven that the greatest success
in the reduction of open defecation has occurred when HEP has been complemented by strong
political support and external engagement of development partners.
Box 7.2: Rural Sanitation Recommendations
• Health extension workers, and employees among the wider health delivery system, need
to be reinvigorated with new communication strategies and tools to address the changing
landscape of sanitation coverage.
• Behavior change communication needs to look beyond the eradication of open defecation,
and support households to improve the quality of their sanitation services and make
linkages with wider health promotion, such as nutrition and early childhood initiatives.
• Tailored demand creation tools and community engagement strategies need to be
developed to target pastoralist communities.
• Build on the supply-side activities to increase the role of private sector in service delivery,
including (a) deepen new institutional partnerships to promote business development;
(b) create a conducive market-based environment to support the establishment of
businesses to provide sanitation products and service; (c) ensure sanitation business
development is mainstream in wider job creation and cash for work programs; and
(d) align supply-side initiatives with renewed demand creation strategies.
• Review the financing approach for rural sanitation, including (a) working with financial
institutions to develop financing products for households and small-scale businesses;
(b) consider innovation grants to drive down costs and stimulate mass production of
affordable sanitation products; and (c) review the policy on hardware subsidies to explore
targeted subsidies to the poorest households possibly through existing mechanisms,
such as the Productive Safety Nets Program (PSNP).
The challenge for value added WASH services is addressing equity while improving quality and
sustainability. The rollout and uptake of value added services—the stepping stone toward
safely managed services—over the past 20 years, mainly in urban areas, have resulted in an
additional 10 million people gaining access to piped water on premises and 8 million people
building improved latrines.
In urban water supply, services with added value and a private dimension have had active
uptake, with wealthier households disproportionately capturing piped water on premises. This
has unintentionally resulted in disadvantaging poorer households, the majority of whom still
fetch water from outside their compounds at public taps or purchase from private vendors.
Poorer women, therefore, spend more time fetching water than wealthier women, and water
quality consumed by poorer households is considerably worse than that consumed by wealthier
households. This is borne out in the differential health and nutrition outcomes in urban areas:
there are higher rates of diarrhea and stunting among children under five in poorer households.
128 Maintaining the Momentum while Addressing Service Quality and Equity
Differential access in urban areas has both supply and demand side barriers. Supply-side
barriers, in which very limited network availability affects around 1 million poor households, are
found predominantly in small towns across Ethiopia. Demand-side barriers, in which people
have not connected to the networks that exist in their neighborhoods, are a feature of larger
towns and cities and affect around 3 million poor households.
Actual expenditure in urban areas, even by the poorest households, was greater than existing
utility tariffs, equivalent to 40 liters per person per day. This holds true across all consumption
quintiles and points to the actual ability, if not willingness, of the poor to pay for utility water.
It also points to the obvious financial benefits of being connected to a utility—particularly as
many households were paying more for water from public stand posts or private water vendors.
Extending utility water supply to all households could reduce the amount that the unconnected
poor pay for water.
These findings reinforce the argument that it is the connection process, rather than affordability
of services, that is the main barrier to equitable access. The qualitative work undertaken for
this study in urban areas has identified three barriers for those wanting to connect. First is a
connection charge, usually around Br 500. Second is that utilities require people hooking up
to pay the cost of connecting pipe work. Third, there are nonfinancial transaction costs of
connecting linked to the time and social capital that people have to put into getting a connection.
With connection costs trumping affordability as a barrier to hooking up, greater attention should
be paid to incentivize utilities to hook people up to utility services.
Investment to address the supply-side constraints is needed especially for towns that have
transitioned from being classified as rural to urban local governments (ULGs). As towns make
this transition to becoming ULGs, they lose access to woreda block grants but have yet to build
up own source revenue capacity for investment. The MDG special purpose grant for capital
investment introduced in 2011 may be part of the solution, but it is too early to tell. However,
the MDG grant is highly discretionary in nature, being multisector (for rural or urban areas), and
so does not favor targeting this transitional demographic. Rather, a specific transitional
infrastructure financing arrangement is needed to plug this gap for this fast growing segment
of urban settlements (see box 7.3).
Box 7.3: Urban Water Supply Recommendations
• Address equity while improving quality and sustainability of utility supplies.
• For newly graduated ULGs with supply-side problems, develop a rural–urban transition
grant and improve the functioning and reach of the Water Resource Development Fund
(WRDF) to help small towns invest in their water supply production, treatment, and
distribution needs—bridging this “coming of age” problem.
• For larger towns and cities with demand-side problems, incentivize utilities to develop flexible
connection arrangements for poorer households to hook up to the utility supply, such as by
(a) streamlining the application and connection request process; (b) allowing shared
connections with flat tariff rates; and (c) amortizing connection charges within the tariff.
• Give utility boards clear policy conditions that give them more flexibility in tariff setting to
improve financial autonomy for inward investment and domestic borrowing, e.g. linking
reductions in nonrevenue water (NRW) to tariff increases.
box continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 129
Box 7.3: Continued
• Reduce microbiological contamination by (a) implementing regular water testing protocols;
(b) instituting controlled chlorination of improved sources; and (c) promoting household
management of safe water chains.
• Improve urban water security through (a) medium- and long-term planning for water
source sustainability; (b) ensuring utilities play an active role in wider water governance
discussions; and (c) initiating integrated urban water management.
Rapid and mostly unplanned urbanization continues to pose the major challenge to improving
urban sanitation access in the coming years. The stagnation of progress in urban sanitation
shows the current institutions, investment levels, and innovation are struggling to adapt to the
new pressures being placed on urban areas. The weak institutional framework in Ethiopia has
resulted in a lack of clear leadership in sanitation, since roles and responsibilities are still not
clearly understood between government agencies. As a result, while other urban infrastructure
and service development initiatives have received significant resources over the last 10 years,
urban sanitation has not received the necessary level of funding.
Adequate urban sanitation infrastructure and services still lags due to limited service provision
across the sanitation service chain. Addressing this must be the highest priority in the coming
year. Greater relative wealth and the increased availability of products and services in urban
areas have resulted in higher access to sanitation compared to rural areas, and most
significantly a higher proportion of improved latrines. While sanitation has provided privacy to
the urban population, the poor management of fecal sludge across the service chain in highly
populated areas continues to poses a significant environmental and health risk. The
enforcement of government pollution laws has been weak and has not provided the incentive
for individuals, businesses, or state actors to address this challenge.
Wealth has a significant impact on service levels in urban areas, with most of those with
access to improved latrines being in the top 60 percent (T60) of the wealth quintile of the
urban population. Those with safely managed services remain solely in the richest quintile.
Urban households in the bottom 40 percent (B40) have the highest rate of open defecation
and lowest level of latrine access. In addition, there is a significantly higher percentage of
shared facilities in urban areas, and a big driver of this relates to property ownership, with
families living in rented accommodations much more likely to share latrines.
While Addis Ababa provides the single largest challenge in addressing urban sanitation, the
shift in urban demographics shows smaller towns are growing at faster rates than the largest
urban centers and now represent a significant proportion of the urban population. Many of
these urban centers have recently graduated from rural woreda status. If tackled quickly there
is an opportunity to get ahead of the curve, but this will require significant investment in
developing the institutional capabilities in these towns.
As in rural areas, the private sector can reduce the burden on public systems and budgets. The
current low sewerage coverage level, high cost and challenge of fitting sewers in fast expanding
and unplanned cities means most transportation will be through vacuum trucks, which provides
a great opportunity for the private sector to engage. However, there are opportunities across
the sanitation service chain for the private sector to engage in. A critical part of the enabling
environment in the urban sanitation sector will be clear and appropriate regulation to guide the
parameters of engagement for new private entrant to the market (see box 7.4).
130 Maintaining the Momentum while Addressing Service Quality and Equity
Box 7.4: Urban Sanitation Recommendations
• Sanitation planning in urban areas should take a citywide approach to tackle the full
service chain and ensure fecal sludge is safely captured, transported, and treated.
• Increased clarity and understanding of institutional roles and responsibilities to manage
urban sanitation services and implement existing pollution regulations are needed. The
swift and effective implementation of the Integrated Urban Sanitation Strategy is critical
to achieve this.
• Public investment is needed in infrastructure to support fecal sludge management across
the service chain, including in treatment plants and, where appropriate, in sewers.
• New financing strategies need to be developed to improve services for the growing urban
poor, including targeted subsidies to improve household infrastructure, facilitate sewer
connections, and encourage the use of fecal sludge transportation services.
• There needs to be alignment with new urban safety net initiative as a mechanism to both
target the poorest household and stimulate new private sector initiatives.
• Public investment needs to be better linked to enabling investments in the urban housing
sector and the private sector to bring innovation and efficiency across the service chain.
• Increased alignment with urban housing initiatives to tackle poor quality sanitation
infrastructure in new and rented accommodation, including (a) a combination of incentive
and regulation for landlords; (b) greater responsiveness of kebele administrations to
support tenants to undertake home improvements; and (c) building regulation for new
condominium housing to ensure sufficient standards of sanitation infrastructure and
supporting services are provided.
• The government needs to develop and implement a clearer regulatory framework to
incentivize private operators to enter the market.
• Invest in building institutional capacity to drive and deliver the GoE and SDG targets
through citywide approaches and to facilitate services provision across the sanitation
service chain.
The analysis in this report has shown that the health burden of inadequate access to WASH
services is disproportionately borne by poorer children and those in vulnerable geographic
areas. Children in poor households are up to 2.7 times more likely to be underweight and
five times more likely to be severely underweight. The analysis suggests that overlapping
vulnerabilities may substantially modify the impact of WASH investments. Children with poor
WASH conditions also suffer from poor access to health and nutrition.
Children in poor households have higher exposure and susceptibility than children in rich
households, with the B40 having approximately 50 percent of the cumulative share of the
susceptibility and risk. Children in poorer households are also more vulnerable to the risks
posed by poor WASH due to low nutrition and access to key health interventions (oral rehydration
treatment [ORT] and vitamin A).
According to the sanitation and water improvement panels shown in map 7.1, children from
Afar would experience the highest risk reduction in response to water or sanitation access
improvements, but all regions would benefit from water or sanitation improvements. Children
from Tigray and Gambella would also experience a reduction in risk, but less than the other
regions, this is likely because children from these regions have lower risk index values.
Maintaining the Momentum while Addressing Service Quality and Equity 131
Map 7.1: Effect of Water Supply and Sanitation Access Improvement on WASH Risk Reduction in
Ethiopia, 2011
a. Unimproved to improved b. Increased household access to most c. Improvement in sanitation
in water access improved water source
Tigray Tigray Tigray
Afar Afar Afar
Benishangul- Benishangul- Benishangul-
Amhara Amhara Amhara
Gumuz Dire Dawa Gumuz Dire Dawa Gumuz Dire Dawa
Harari Harari Harari
Addis Ababa Addis Ababa Addis Ababa
Oromia Oromia Oromia
Gambela Somali Gambela Somali Gambela Somali
SNNPR SNNPR SNNPR
< 1.25
1.25–2.24 < 2.00
2.25–3.24 2.00–2.99
3.25–4.24 3.00–3.99
Kilometers
4.25–5.25 4.00–4.99 Kilometers
0 250 500
> 5.25 5.00–6.00 0 125 250 500
Source: DHS 2011.
Note: WASH = water supply, sanitation, and hygiene.
In Ethiopia, the national enteric burden associated with inadequate WASH is 11,135 disability-
adjusted life years (DALYs) per 100,000 children per year, which is approximately 75 percent
of the Global Burden of Disease (GBD) enteric burden estimated for the country. The WASH-
related enteric burden is lower within urban than in rural populations, but the disparities in both
are equivalent. The burden for the poorest communities is 1.8 times as high as the burden for
the richest in rural communities, and 5.4 times higher for the poorest households than the
richest in urban communities (see box 7.5).
Box 7.5: Targeting WASH Investment for Health Benefits
• As the health benefits of improvement in water supply and sanitation are not seen until
coverage levels reach universality, more focus should be placed on ensuring communities
are fully served with improved services and that behavior change is sustained across the
whole communities.
• This analysis describes how WASH-related risk is distributed across wealth quintiles,
between rural and urban populations, and by location. A simple next step would be to
map existing World Bank programs in Ethiopia against these factors to assess to what
extent investments are reaching the populations that stand to gain the most.
• Geographic targeting of WASH investments to areas with higher concentrations of children
vulnerable due to poor nutrition and health access offers a simple compass for reaching
the most vulnerable that might facilitate cross-sectoral planning, delivery, and monitoring.
• Regional distributions of exposure, susceptibility, and risk index values in the B40
population indicate that every region has highly vulnerable children. This emphasizes the
importance of combining geographic and economic targeting of health investment.
• The government needs to implement pro-poor targeting in the sector coordinating with
social protection programs that focus on households with young children who are
economically vulnerable.
132 Maintaining the Momentum while Addressing Service Quality and Equity
In summary, improving and expanding both basic and safely managed WASH services calls for
continuing GoE’s twin track development of its core country systems for decentralized service
delivery and its sector policy direction that together have driven progress at scale over the past
decade and more. On top of the challenges of delivering services under the MDG framework,
GoE and its development partners now need to consider the additional rigor required in
delivering on the SDGs. With the estimated SDG financing gap running into billions of dollars a
year, much more than incremental improvements to past progress are needed. The reward for
making this transition from MDGs to SDGs is the real prospect of delivering on the health and
economic gains that have been elusive under the MDG framework.
The transition to the SDGs needs to be done with two supporting factors in mind: (a) a massive
upgrading of skills in the public and private sector, and (b) a full integration of WASH service
delivery into the broader water governance agenda. Transitioning to the SDGs will require a very
significant upgrading of skills in the public sector and much greater use of the economywide
capacity. In the public sector greater effort is needed to ensure institutions have the right mix
of skills, including in many new areas (such as water quality and private sector engagement)
required to tackle the challenges achieving the SDG targets pose. In parallel to evolving the
skill sets within public institutions, strong systems need to be put in place to ensure the
effective transfer and institutionalization of knowledge. The reskilling and knowledge retention
need to be combined with an increased recognition that the private sector has complementary
skills to support the significant expansion and improvement in services. By effectively
harnessing the skill and resources of the private sector, the GoE has the ability to reduce
pressure on human resources in the public sector, as well as shift the burden away from the
government’s fiscal budget.
To date, WASH service delivery in Ethiopia has largely operated in a silo, disconnected from
wider concerns about water availability and competing demands from other users. As plans to
deliver the SDGs are drawn up, the higher service levels associated with safely managed
services will begin to compete with other fast growing demands for water. With the GoE
simultaneously promoting household irrigation based on self-supply, and the increase in large-
scale commercial irrigation for horticulture competition for water at local and basin scales,
trade-offs are inevitable. Ethiopia’s progression up the water service ladder, and its ability to
sustain higher levels of service for rural and urban users, will depend increasingly on
the ability of public institutions to manage water resources for a range of competing uses. The
implication is that those working on WASH services will need to play a much more active role
in wider planning and policy debates around water allocation and sustainability than they
currently do. This will be a long-term process. Good water governance, including measures to
protect the quality and quantity of water needed for drinking water services, will likely take
decades to build.
Maintaining the Momentum while Addressing Service Quality and Equity 133
Appendix A
Poverty Calculations
Different methods of wealth quintiles and consumption quintile analysis reveal different aspects
of inequality in Ethiopia. Here we compare DHS and HICES methods.
•• Method 1: National population split into uneven urban and rural wealth quintiles
•• Method 2: Rural and urban population split into even wealth quintiles
•• Method 3: Rural and urban population split into even consumption quintiles
Figure A.1: Access to Water by Wealth Quintile Analysis in Ethiopia, 2000 and 2011
a. Method 1: JMP—estimated trends b. Drinking water trends by c. Drinking water trends by
of drinking water coverage by wealth quintile rural wealth quintile urban wealth quintile
Rural Urban 100 100
Ethiopia
1995 2012 1995 2012
Piped on premises 0 0 10 17
80 80
Poorest Other improved 18 45 56 73
Unimproved 82 55 34 10
Piped on premises 1 0 19 36 60 60
Percent
Percent
Second Other improved 21 47 68 61
Unimproved 78 53 13 3
40 40
Piped on premises 1 0 27 60
Middle Other improved 18 55 66 39
Unimproved 81 45 7 1 20 20
Piped on premises 1 0 57 73
Fourth Other improved 23 56 42 26
0 0
Unimproved 76 44 1 1
t
nd
e
th
t
t
nd
e
th
t
es
es
es
es
Piped on premises 4 1 83 88
dl
dl
ur
ur
co
co
or
ch
or
ch
id
id
Fo
Fo
Po
M
Po
M
Richest Other improved
Se
Se
28 64 17 11
Ri
Ri
Unimproved 68 35 0 1
Unimproved Other improved Piped on premises
Poorest Second Middle Fourth Richest Poorest Second Middle Fourth Richest
1,000s of people per WQ (2011): 12,688 12,688 12,688 12,688 12,688 2,788 2,788 2,788 2,788 2,788
a. Method 2: HBS - estimated trends of b. Drinking water trends by c. Drinking water trends by
drinking water coverage by wealth quintile rural wealth quintile urban wealth quintile
(based on national quintiles)
Rural Urban 100 100
Ethiopia
2000 2011 2000 2011
Piped on premises 0 0 0 1 80 80
Poorest Other improved 4 22 0 65
Unimproved 96 78 100 35
Piped on premises 0 0 0 0 60 60
Percent
Percent
Second Other improved 8 38 0 88
Unimproved 92 62 100 12 40
40
Piped on premises 0 0 0 7
Middle Other improved 12 46 3 71
Unimproved 88 54 97 22 20 20
Piped on premises 0 0 0 6
Fourth Other improved 21 56 50 68
0 0
Unimproved 79 44 50 26
Se t
nd
e
th
t
t
nd
e
th
t
es
es
es
es
dl
dl
Piped on premises 0 1 31 53
ur
ur
co
co
or
ch
or
ch
id
id
Fo
Fo
Po
M
Po
M
Se
Ri
Ri
Richest Other improved 35 72 58 43
Unimproved 65 27 11 3 Unimproved Other improved Piped on premises
Poorest Second Middle Fourth Richest Poorest Second Middle Fourth Richest
1,000s of people per WQ (2011): 15,162 15,352 15,289 14,337 3,235 321 139 153 1,115 12,211
Sources: DHS 2000 and 2011.
Maintaining the Momentum while Addressing Service Quality and Equity 135
Figure A.2: Access to Water by Consumption Quintile Analysis in Ethiopia, 2000 and 2011
a. Method 3: JMP—estimated trends b. Drinking water trends by c. Drinking water trends by
of drinking water coverage by wealth quintile rural consumption quintile urban consumption quintile
(separate rural and urban quintiles)
Rural Urban 100 100
Ethiopia
2000 2011 2000 2011
Piped on premises 1 0 14 25 80 80
Poorest Other improved 15 37 71 65
Unimproved 84 63 15 11
Piped on premises 1 1 20 31 60 60
Percent
Percent
Second Other improved 18 42 65 58
Unimproved 82 58 15 11 40 40
Piped on premises 0 1 28 38
Middle Other improved 19 38 65 54
Unimproved 81 61 7 8 20 20
Piped on premises 0 1 34 43
Fourth Other improved 19 43 61 50
0 0
Unimproved 81 57 6 7
t
nd
e
th
st
t
nd
e
th
st
Piped on premises 0 2 53 59
es
es
dl
dl
e
e
ur
ur
co
co
or
ch
or
ch
id
id
Fo
Fo
Richest Other improved
Po
M
Po
M
21 42 41 37
Se
Se
Ri
Ri
Unimproved 79 56 6 4 Unimproved Other improved Piped on premises
Poorest Second Middle Fourth Richest Poorest Second Middle Fourth Richest
1000s of people per WQ (2011): 14,179 13,753 13,414 12,132 8,114 552 981 1,311 2,617 6,587
2011 annual consumption Br per quintile 1,891 2,970 3,857 5,062 9,837 1,891 2,970 3,857 5,062 9,837
a. Method 2: HBS - estimated trends of drinking water b. Drinking water trends by c. Drinking water trends by
coverage by wealth quintile (based on national quintiles) rural consumption quintile urban consumption quintile
Rural Urban 100 100
Ethiopia
2000 2011 2000 2011
Piped on premises 1 0 16 35 80 80
Poorest Other improved 15 36 69 58
Unimproved 84 63 15 7
Piped on premises 1 0 27 42 60 60
Percent
Percent
Second Other improved 18 42 65 51
Unimproved 82 58 8 6 40
40
Piped on premises 0 1 35 50
Middle Other improved 19 39 59 44
Unimproved 81 60 6 6 20 20
Piped on premises 0 1 46 58
Fourth Other improved 19 41 47 38
0 0
Unimproved 81 58 7 4
t
nd
e
th
t
t
nd
e
th
t
es
es
es
es
Piped on premises 0 2 62 65
dl
dl
ur
ur
co
co
or
ch
or
ch
id
id
Fo
Fo
Po
M
Po
M
Se
Se
Richest Other improved
Ri
Ri
21 41 33 32
Unimproved 79 56 5 4 Unimproved Other improved Piped on premises
Poorest Second Middle Fourth Richest Poorest Second Middle Fourth Richest
1000s of people per WQ (2011): 12,371 12,359 12,362 12,355 12,361 2,367 2,368 2,368 2,366 2,366
2011 annual consumption Br per quintile 1,796 2,806 3,588 4,545 7,374 3,125 4,883 6,516 8,934 18,493
Source: WMS and HICES. 2000 and 2011.
136 Maintaining the Momentum while Addressing Service Quality and Equity
Appendix B
Linear Regression Model of
Improved Water Supply in
Rural Areas of Ethiopia
Coverage of improved water (protected and piped water supply) was significantly higher in
woredas dominated by agrarian cropping livelihoods than it was in woredas dominated by
pastoralist livelihoods. Possible determinants of access to improved water were examined
using multivariate analysis. All regions where agropastoralist and pastoralist livelihoods are
practiced (Somali, Afar, Oromia, and Southern Nations, Nationalities and People Region [SNNPR])
were correlated with significantly lower access to improved water. The one exception was
Gambella region, which has agropastoralist woredas but did not have improved water coverage
that was significantly lower than other regions.
The relative mean poverty headcount ratio of the woreda explains the largest share of the
variation observed. However, independent of relative poverty, the woredas with cropping
dominated livelihoods or those with easier hydrology or hydrogeology had significantly higher
levels of access to improved water.
Across Ethiopia, woredas targeted by the Productive Safety Nets Program (PSNP) reported
significantly higher levels of access to improved water than woredas not targeted by PSNP.
However, further analysis revealed that these differences were only significant across agrarian
cropping woredas but not across agropastoralist or pastoralist woredas. Average annual rainfall
and population density of woredas, though returning significant results, had only very small
effects on improved access to water supply.
Method and Data Sources
To examine the possible determinants of improved access to water in Ethiopia the WASH
Poverty Diagnostic (WPD) merged woreda level estimates from the following sources:
•• Housing and Population Census 2007: water supply and sanitation data
•• HICES 2011: woreda-level poverty headcount estimates from the small area estimation
work done under the Ethiopia Poverty Assessment
•• Boost database: woreda-level spending data (capital and recurrent)
•• Livelihoods Integration Unit: livelihood types and zones, rainfall, population density
•• PSNP: woredas targeted by PSNP in 2010
•• Hydrological Index (HI): index of the technological difficulty (or ease) of exploiting water
based on the variation in hydrological and hydrogeological factors across Ethiopia based
on British Geological Survey (BGS) data developed in 2016
Maintaining the Momentum while Addressing Service Quality and Equity 137
Woreda-level estimates were used rather than using household data directly since a number of
the variables (HI, population density, livelihoods, and rainfall) were available only at woreda
level (they are not part of household survey data).
First, a t-test was done on mean improved water access between the two groups: (a) agrarian
cropping areas (CR) and (b) agropastoralist and pastoralist areas (NCR) (figure B.1). Second,
an ordinary least squares (OLS) regression model was then built to explain the variation in the
Figure B.1: Mean Improved Water Coverage Levels by Livelihood Type in Rural Areas
in Ethiopia, 2007
. ttest improved_water , by( group)
Two-sample t test with equal variances
Group Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
Cr 556 .388741 .0072733 .1715017 .3744545 .4030276
NCR 107 .2418692 .0152254 .1574929 .2116833 .272055
combined 663 .3650377 .0068988 .1776354 .3514916 .3785838
diff .1468718 .017876 .1117713 .1819724
diff = mean(Cr) - mean(NCR) t = 8.2162
Ho: diff = 0 degrees of freedom = 661
Ha: diff < 0 Ha: diff != 0 Ha: diff > 0
Pr(T < t) = 1.0000 Pr(|T| > |t|) = 0.0000 Pr(T > t) = 0.0000
. ttest improved_water , by( group) unequal
Two-sample t test with unequal variances
Group Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
Cr 556 .388741 .0072733 .1715017 .3744545 .4030276
NCR 107 .2418692 .0152254 .1574929 .2116833 .272055
combined 663 .3650377 .0068988 .1776354 .3514916 .3785838
diff .1468718 .0168735 .1135457 .180198
diff = mean(Cr) - mean(NCR) t = 8.7043
Ho: diff = 0 Satterthwaite's degrees of freedom = 158.325
Ha: diff < 0 Ha: diff != 0 Ha: diff > 0
Pr(T < t) = 1.0000 Pr(|T| > |t|) = 0.0000 Pr(T > t) = 0.0000
.
Source: World Bank data.
Note: Top of figure shows simple t-test results for with equal variance, and bottom of figure shows results without equal variance.
Cr = cropping-dominant woredas; NCR= agropastoralist- and pastoralist-dominant woredas.
138 Maintaining the Momentum while Addressing Service Quality and Equity
Figure B.2: Ordinary List Squared Regression Results for Possible Determinants of
Improved Water in Rural Areas of Ethiopia
. reg imp_wat poverty pop_den rain psnpdummy Livhod_dummy i.hydoindex_new i.region
Source SS df MS Number of obs = 659
F(14, 644) = 23.70
Model 6.94928357 14 .496377398 Prob > F = 0.0000
Residual 13.4855645 644 .020940317 R-squared = 0.3401
Adj R-squared = 0.3257
Total 20.434848 658 .031056 Root MSE = .14471
imp_wat Coef. Std. Err. t P>|t| [95% Conf. Interval]
poverty -.1888641 .0444429 -4.25 0.000 -.2761346 -.1015936
pop_den .0002722 .0000675 4.03 0.000 .0001396 .0004048
rain -.0001088 .0000288 -3.77 0.000 -.0001655 -.0000522
psnpdummy .0536959 .0147039 3.65 0.000 .0248226 .0825692
Livhod_dummy .1039398 .0297297 3.50 0.001 .045561 .1623186
hydoindex_new
2 .0720592 .0211346 3.41 0.001 .0305581 .1135604
3 .0780186 .0258925 3.01 0.003 .0271747 .1288624
region
2 -.2044332 .046704 -4.38 0.000 -.2961437 -.1127227
3 -.0984595 .0311878 -3.16 0.002 -.1597016 -.0372174
4 -.1979022 .0301896 -6.56 0.000 -.2571841 -.1386202
5 -.2155759 .0423232 -5.09 0.000 -.298684 -.1324678
6 -.1427942 .0440178 -3.24 0.001 -.2292299 -.0563585
7 -.1753249 .0323677 -5.42 0.000 -.2388839 -.1117659
12 -.0172276 .0523254 -0.33 0.742 -.1199766 .0855214
_cons .4818979 .0497604 9.68 0.000 .3841858 .5796101
Source: World Bank regression results using data from the 2007 census, GoE HICES 2011, and HCES 2011.
dependent variable of access to improved water (not improved=0; improved=1) observed
across rural Ethiopia (figure B.2). The following independent variables were included:
•• Poverty headcount (continuous variable as percentage)
•• Population density (continuous variable as people per square kilometer)
•• Rainfall (continuous variable long-term mean rainfall in millimeters per year from GoE
Ethiopian Livelihoods Atlas)
•• Agrarian compared to agropastoralist and pastoralist (binary variable dummy:
pastoralist=0; agrarian=1)
•• PSNP woreda (binary variable PSNP dummy: woredas not in PSNP=0; woredas in
PSNP=1)
Maintaining the Momentum while Addressing Service Quality and Equity 139
•• Hydrological Index (three dummy variables: hard=0; medium=1; easy=2)
•• Regions (categorical variable using improved water coverage by region: Tigray=1; Afar=2;
Amhara=3; Oromiya=4; Somali=5; Benishangul-Gumuz=6; SNNPR=7; Gmabella=12)
Third, simple t-tests were done to check whether there was a significant difference in the mean
access to improved water between woredas targeted by the PSNP and those not targeted. This
was done separately for (a) woredas dominated by agropastoralist or pastoralist livelihoods
and (b) woredas dominated by agrarian cropping livelihoods.
Results
The simple t-test to check whether there was a significant difference in the mean access to
improved water between the cropping- and agropastoralist- and pastoralist-dominant woredas
returned significant differences for both equal and unequal variance assumptions.
•• The OLS regression model results explain just over one-third of the variation in woreda
level estimates for access to improved water.
•• Poverty headcount ratio at the woreda level has a strong effect on access to improved
water. The higher the poverty headcount ratio the less likely households in the woreda
are to have access to improved water supplies.
•• Agrarian woredas are significantly more likely to have access to improved water than
agropastoralist and pastoralist woredas—by about 10 percentage points.
•• Woredas with medium or easy hydrology or hydrogeology are more likely to have
improved water, but the difference between medium and easy hydrology or hydrogeology
is small.
•• Average annual rainfall and population density of woredas, though significant, has only
very small effect on access to improved water.
•• Access to improved water varies significantly across regions.
While across Ethiopia, woredas targeted by the PSNP have better access to improved water
than non-PSNP woredas, separate simple t-tests reveal that these differences are significant
only across woredas dominated by agrarian cropping livelihoods. Across woredas dominated
by agropastoralist and pastoralist livelihoods the PSNP is not associated with higher access to
improved water supply (figures B.3 and B.4).
140 Maintaining the Momentum while Addressing Service Quality and Equity
Figure B.3: Mean Improved Water Coverage Levels in Agropastoralist and Pastoralist
Areas with and without PSNP in Ethiopia, 2007
. ttest imp_wat , by(noncrp_psnp_dmmy)
Two-sample t test with equal variances
Group Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
0 32 .2139916 .0261187 .1477495 .1607222 .267261
1 75 .2540725 .0186517 .1615286 .2169082 .2912369
combined 107 .2420857 .0152668 .1579207 .2118178 .2723536
diff -.0400809 .0332739 -.1060569 .025895
diff = mean(0) - mean(1) t = -1.2046
Ho: diff = 0 degrees of freedom = 105
Ha: diff < 0 Ha: diff != 0 Ha: diff > 0
Pr(T < t) = 0.1155 Pr(|T| > |t|) = 0.2311 Pr(T > t) = 0.8845
. ttest imp_wat , by(noncrp_psnp_dmmy) unequa l
Two-sample t test with unequal variances
Group Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
0 32 .2139916 .0261187 .1477495 .1607222 .267261
1 75 .2540725 .0186517 .1615286 .2169082 .2912369
combined 107 .2420857 .0152668 .1579207 .2118178 .2723536
diff -.0400809 .0320947 -.1042027 .0240408
diff = mean(0) - mean(1) t = -1.248 8
Ho: diff = 0 Satterthwaite's degrees of freedom = 63.735 7
Ha: diff < 0 Ha: diff != 0 Ha: diff > 0
Pr(T < t) = 0.1081 Pr(|T| > |t|) = 0.2163 Pr(T > t) = 0.8919
Source: Census, 2007.
Note: Top of figure shows simple t-test results for with equal variance, and bottom of figure shows results without equal variance.
Agropastoralist and pastoralist woredas: not targeted by PSNP=0; targeted by PSNP=1. PSNP = Productive Safety Nets Program.
Maintaining the Momentum while Addressing Service Quality and Equity 141
Figure B.4: Mean Improved Water Coverage Levels in Agrarian Cropping Areas with
and without PSNP in Ethiopia, 2007
. ttest imp_wat , by(crp__psnp_dmmy)
Two-sample t test with equal variances
Group Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
0 330 .3402772 .0084816 .1540762 .3235922 .3569622
1 224 .4563948 .01124 .1682242 .4342446 .4785449
combined 554 .3872273 .0072087 .1696722 .3730675 .401387
diff -.1161176 .0138464 -.1433157 -.0889194
diff = mean(0) - mean(1) t = -8.3861
Ho: diff = 0 degrees of freedom = 552
Ha: diff < 0 Ha: diff != 0 Ha: diff > 0
Pr(T < t) = 0.0000 Pr(|T| > |t|) = 0.0000 Pr(T > t) = 1.0000
. ttest imp_wat , by(crp__psnp_dmmy) unequa l
Two-sample t test with unequal variances
Group Obs Mean Std. Err. Std. Dev. [95% Conf. Interval ]
0 330 .3402772 .0084816 .1540762 .3235922 .356962 2
1 224 .4563948 .01124 .1682242 .4342446 .478544 9
combined 554 .3872273 .0072087 .1696722 .3730675 .40138 7
diff -.1161176 .014081 -.1437902 -.088445
diff = mean(0) - mean(1) t = -8.2464
Ho: diff = 0 Satterthwaite's degrees of freedom = 450.301
Ha: diff < 0 Ha: diff != 0 Ha: diff > 0
Pr(T < t) = 0.0000 Pr(|T| > |t|) = 0.0000 Pr(T > t) = 1.0000
Source: Census, 2007.
Note: Top of figure shows simple t-test results for with equal variance, and bottom of figure shows results without equal variance.
Agrarian cropping woredas: not targeted by PSNP=0; targeted by PSNP=1. PSNP = Productive Safety Nets Program.
142 Maintaining the Momentum while Addressing Service Quality and Equity
Appendix C
Hydrogeological Index
The Hydrogeological Index (HI) is based on scores for five factors affecting the ease of groundwater
development for rural water supply, and draws on existing rainfall, geology, water quality, and
topographic data. The variables include the following:
•• Depth to water. Affects drilling costs, pumping costs, and technology options (e.g., hand
pumps compared to motorized pumps).
•• Water quality. Determines whether water is safe to drink. We considered two “natural”
contaminants: salt (salinity) and fluoride.
•• Borehole yield. The volume of water that can be abstracted from a borehole, which
determines the number of people it can serve or the amount of water they can access.
Since yield is a function of storage and permeability, yield also indicates resilience to
climate variability and change.
•• Rainfall and recharge. The amount of rainwater that could potentially be converted into
groundwater recharge, based on some fairly conservative assumptions about conversion.
•• Other factors. Include the presence of wetlands, steep slopes, and flood plains that
might limit groundwater development potential.
Table C.1: Relationship between HI Index and Recommended Development Approach
Required exploration and development
HI Hydrogeological characteristics approaches and technologies
0 Very deep (>250 m) strike depth (depth •• Drilling: deep drilling involving heavy-duty rigs in the cases
to aquifer not necessarily depth to static of deep water strike depth; steel casing and usually 10 ft.
water level); or salinity, fluoride, or other wells required; drilling compressor capacity up to 36 bar
water quality indicators fail to satisfy needed. Highest drilling cost.
local WQ standards/WQ unacceptable •• Study (deep aquifers): integrated and thorough
for the communities; limited recharge hydrogeological survey, airborne geophysics, water
may impose limit on groundwater quality survey, multiple test well drilling, geology, and
availability; groundwater may not receive stratigraphy survey.
present-day recharge (fossil); aquifers •• Study (poor water quality): detailed integrated survey of
with very low yield (unsuitable for any shallow aquifers to identify targeted low salinity or low
type of pump also included under this fluoride areas in otherwise poor water quality zones.
category). •• Capacity: beyond capacity of woredas and the regional
Geology: sedimentary basins or alluvio- government; may be beyond current national capacity.
lacustine sediments with brackish water •• Technologies: water treatment technologies such as
or highly dissected mountainous areas defluoridation plants may be required to remove fluoride,
with limited water storage. or reverse osmosis to remove salinity.
•• Technologies: alternative water sourcing from surface waters
(e.g., dams) or multicommunity RPS schemes through
interworeda water transfer in cases of low yielding aquifers.
table continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 143
Table C.1: Continued
Required exploration and development
HI Hydrogeological characteristics approaches and technologies
1 Low yielding deep aquifers •• Drilling: heavy-duty drilling rigs with >20 bar compressors.
Steel casing and 8 ft to 10 ft hole diameter required.
•• Study: Integrated survey including geology and stratigraphy,
surface geophysics, RS, and test drilling.
Geology: sedimentary basins •• Capacity: beyond capacity of woreda but within capacity
of regional government with support from national federal
enterprises.
•• Technologies: low yields and deeper water levels preclude
use of hand pumps. Solar pumps could be used. Yield too
low for motorized pumps.
•• Technologies: alternative water sources from surface waters
(e.g., dams) or multicommunity RPS schemes through
interworeda water transfer required; or installation of solar
pumps in desperate communities. Hand-dug wells may
produce sufficient water for RWS in some cases.
2 Woreda with moderate water strike •• Drilling: light-duty trailer rigs with low capacity compressors
depth (90–150 m), which can be (12–15 bar) in case of moderate water strike depth. Low
accessed with light duty trailer rigs (with yielding aquifers at that depth do not allow installation of
compressor capacity of 12–15 bar), hand pumps or motorized pumps. Solar pumps may be
but yield too low (0.1 to 0.5 lps) for used in desperate situations. PVC casing may be used
installation of motorized pump, or too safely but steel casing should apply depending on the
deep for hand pumps. nature of geological formation or water temperature.
Woreda with moderate aquifer yield •• Drilling: heavy-duty drilling rigs with larger compressor
(0.5 to 1.0 lps) but unfavorable depth capacity (20 bar or above); trailer rigs generally not
(150–250 m) for light duty track (trailer applicable. Steel casing required.
rigs?) and unfavorable for compressor •• Study: integrated survey: geology, geophysics, RS
capacity mounted on trailer rigs applications, topography with lower requirement for test
(12–15 barr). Also unfavorable for drilling and aquifer scale mapping to identify locally
hand pumps. Solar pumps may be productive zones.
appropriate. •• Capacity: regional government may have capacity to conduct
study in these woredas.
Geology: volcanic rocks (mainly tuffs, •• Technologies: hand pumps unsuitable in most cases; low
volcanic ash and ignimbrites) yields do not allow motorized pumps; solar pumps may
apply in cases of desperate water need.
•• Technologies: alternative water sources could include
spring development for multicommunity RPS in which high
discharge springs from fractures; drilling multiple boreholes
with low capacity and installing solar pumps; interworeda
water transfer through RPS.
table continues next page
144 Maintaining the Momentum while Addressing Service Quality and Equity
Table C.1: Continued
Required exploration and development
HI Hydrogeological characteristics approaches and technologies
3 Woredas underlain by shallow but low •• Drilling: light-duty trailer rigs with compressor capacity of
yielding aquifers (basement rocks 12 bar can be used, PVC casing may be sufficient, 6-in
in general). Aquifers may run dry in drilling sufficient; drilling more than 120 m in such areas
extended dry seasons; groundwater is a sunk cost since productive aquifers not expected
occurs in specific fractured zones deeper than this level; change drilling site in case of drilling
or in overburden regolith; locally difficulty but only consider if second site is high water
higher yields may be encountered probability.
but wildcat drilling could produce dry •• Study: heterogeneous nature of aquifers requires
wells; heterogeneous nature of aquifer integrated hydrogeology study including surface geophysics,
means water may not be encountered remote sensing, topographic survey, and woreda-scale
successfully in most cases regardless hydrogeological mapping.
of the shallow depth of the aquifer. •• Capacity: exists at regional level to conduct hydrogeological
Geology: fractured basement rocks mapping; mapping may be required prior to drilling.
with thin regolith. •• Technologies: hand pumps [Indian Mark II or Afridev].
4 A high yielding aquifer (>5 lps) but •• Drilling: light-duty rigs could be sufficient but local
deep water strike depth may exceed heavy-duty rigs may be required; steel casing required;
capacity of hand pumps. High yield 10-in drilling may be required depending on yield and
means motorized pumps can be used. pump installation; consider on-site solution in case of
Geology: multilayered volcanic and drilling difficulty.
sediments. •• Study: integrated study involving surface geophysics,
remote sensing, regional–woreda scale hydrogeological
mapping, water quality surveys, and pumping tests may be
required.
•• Capacity: regional government capacity may be sufficient
but in some cases support from national institutions is
needed.
•• Technologies: aquifers suitable for RPS; high cost of drilling
means multiple wells per woreda may be expensive so RPS
from productive wells may be more appropriate.
6 Moderate yielding aquifer at shallow •• Drilling: light-duty trailer rigs with up to 12-bar compressor
depth suitable for installation of capacity; PVC casing may be used in most cases, but steel
hand pumps and deployment of truck casing may be needed at some sites. Consider on-site
mounted trailer rigs. solution in case of drilling difficulty but selecting new site
High yielding aquifer with relatively possible if shallow.
deep water strike depth. Depth may •• Study: topographic survey combined with surface
not favor installation of hand pumps geophysics at local level adjacent to the sites to be drilled
but higher yield favors motorized may be sufficient; pumping test may be required in cases
schemes for multicommunity of high yielding aquifers considered for motorized pump
initiatives. installation.
Geology: fractured volcanic rocks •• Capacity: zonal level expertise may be sufficient.
and fractured and weathered •• Technology: hand pumps for shallower systems; motorized
basement rocks pumps for deeper aquifers.
table continues next page
Maintaining the Momentum while Addressing Service Quality and Equity 145
Table C.1: Continued
Required exploration and development
HI Hydrogeological characteristics approaches and technologies
8 High yielding aquifer at intermediate •• Drilling: light duty trailer rigs, PVC or steel casing, motorized
depth pumps, or hand pumps. Drill at alternative site in case of
drilling difficulty.
Geology: alluvial valleys; field with •• Study: surface geophysics, topographic survey, and
sediments integrated hydrogeological survey (geological mapping,
water point inventory, and water quality survey).
•• Capacity: zonal- or woreda-level expertise.
•• Technology: motorized pumps and appropriate for RPS.
9 High yielding shallow aquifer •• Drilling: light-duty trailer rigs, PVC casing; drill another
nearby site in case of drilling difficulty.
Geology: fractured volcanic rocks in •• Study: topographic survey or surface geophysics in case of
high rainfall areas complex topography.
•• Capacity: local woreda, zone.
•• Technology: hand pumps.
•• Technology: MUS for productive water use can be
considered if motorized pumps installed; piped systems
also suitable.
12 Very high yielding aquifer at •• Drilling: light-duty trailer rigs, PVC casing. Drill at alternative
shallow depth site in case of drilling difficulty.
Geology: quaternary basalts in •• Study: topographic survey.
the highlands •• Capacity: woreda-level experts and drillers can locate sites.
•• Technology: hand pumps.
•• Technology: MUS for productive water use can be
considered; piped system also possible.
Source: World Bank.
Note: HI = Hydrological Index; MUS = Multi-Use System; WQ = water quality.
146 Maintaining the Momentum while Addressing Service Quality and Equity
Appendix D
Water Quality
The objective of undertaking this water quality survey was to generate new data to improve sector
knowledge on the microbial and chemical water quality of water being used by households across
Ethiopia. Data collection and analysis of water samples from both households and their sources
will be a baseline to monitor the water supply, sanitation, and hygiene (WASH) component of
Growth and Transformation Plan (GTP) II and the Sustainable Development Goals (SDGs).
The collection of the water quality data was linked to the third wave of the Ethiopia Socioeconomic
Survey (ESS) carried out in 2015/16. ESS is an ongoing household panel survey, which means
the same households are revisited over a period of several years. Each wave of data collection
covers a 12-month period during which two visits are conducted to capture seasonal variations
in productivity, particularly related to agriculture. Linking the water quality data collection to the
ESS enabled analysis disaggregated by different socioeconomic groups, residence areas, and
geographic locations. This appendix is a summary of the methods, results, and interpretation.
Full details are reported in the ESS-WQT module (forthcoming).
Methods
Implemented by the Ethiopian Central Statistical Agency (CSA) in collaboration with the World
Bank Living Standards Measurement Study–Integrated Surveys on Agriculture (LSMS-ISA),1
ESS is aligned with the National Strategy for the Development of Statistics (NSDS) covering
2009/10 to 2013/14, and the data are made publicly available.
To ensure representation is at the same level as in ESS, the water quality testing component
(ESS-WQT) was administered to all ESS households. The ESS consists of a probability-based
sample of households representative of the population of all households in rural, small town,
and (as of wave 2) urban areas of Ethiopia. The current sample size of roughly 5,200 households
is also statistically representative at the region level for five regions (Addis Ababa; Amhara;
Oromiya; Southern Nations, Nationalities and People Region [SNNPR]; and Tigray) plus a sixth
“region” that comprises all the other regions.
In the ESS water quality testing (WQT) module, two samples were tested for E. coli: one at the
point of collection, and one directly from a glass used for drinking. A total of 4,533 tests were
conducted at points of collection, which resulted in 4,513 risk classifications (99.6 percent).
The survey was conducted over one data collection period, May–July 2016, and as such does not
address seasonality. Experts note that water quality can have important seasonal variations and
conducting water quality tests during only the dry season could introduce systematic bias (WHO/
UNICEF 2013). Because ESS is an ongoing panel survey, future waves of water quality testing
could provide greater insights on water quality components, across years and during different
seasons, than would normally be possible in a household survey. This would be an important step
toward developing a more complete measure of sustainability, which is sorely lacking at present.
The fieldwork was taken by 18 mobile teams, and each team comprised two testers, a data
collector, and one supervisor and a four-wheel vehicle. The 25 statistical branch offices of the
CSA participated in the survey undertaking, especially in deploying field staff members to their
respective sites of assignment, and administering the financial and logistic aspect of the
survey within the areas of their assignment. To accomplish the data collection operation, all
the data collectors were supplied with the necessary survey equipment at the completion of
Maintaining the Momentum while Addressing Service Quality and Equity 147
the training. To assure data quality, experts from WHO, UNICEF, MAWIE, and the World Bank had
frequent field visits. It took 93 days to complete the water quality survey.
A range of quality assurance and quality control measures were incorporated into the project
at every stage including intensive training, enumerator exams, and field practice. The quality
control measures included the following:
•• Blank tests. Two blank tests were assigned for each EA, particularly for the first four
weeks. The water sample for this test was assumed that they are free from any bacteria.
The intention of performing this test was to check the performance of the field workers
and reminding them to adhering the proper procedure. One blank test was assigned to
a randomly selected household in the household listing that the field workers were
provided. A second blank test questionnaire for EA-level was added to the Survey Solution
template. If water tester 1 was assigned to the selected household for blank test, then
water tester 2 was expected to complete the EA level blank test. For the eight weeks, the
field workers did one blank test per EA at household level.
•• Proportion of filtered water. The field workers were informed that the proportion of filtered
water was expected to imply a given outcome of interest. For example, if water sample
from the fetching point filtered less than 100 percent during the process, the possibility of
high turbidity increases. This means, if the field workers enter a low level turbidity result
for low proportion of filtered water, it indicates a possible wrong practice during the test.
•• Photo analysis. This analysis refers to counting the colonies on the 1 milliliters and
100 milliliters water plates using photos, and analyzing consistency between the
mentioned water plates. The field workers were requested to take pictures of each plate
(1 milliliters and 100 milliliters) after the required incubation period for each bacteria
test using the Survey Solution template. Every day, the number of colonies recorded in
the data was rechecked by the field coordinators. This practice had been serving in two
ways. First, it flagged the possibility of existing contamination during the test process,
which could attribute to the inconsistency between the 1 milliliters and 100 milliliters
water plates. Second, any discrepancy between the number of colonies in 1 milliliters
and 100 milliliters, means that field workers made a mistake in recording results in the
reverse order (the 100 milliliters for 1 milliliters and vice versa); consequently, the field
workers communicated about the issues and requested to record correctly.
•• Test timing. The bacterial test conducted within an hour after the sample was collected.
This procedure was managed through a daily base communication between the team
leader and water testers.
•• Control sample for chemical lab test. This test was done in a central laboratory based in
Addis Ababa. The institute, which conducted the chemical lab test, anonymously had
been provided with control samples along the main source samples. The control samples
have features of the standard measure for each chemical test. At the end of the lab test,
the control sample results from the institute were checked against the original result.
•• Internal consistency checks. Intensive internal consistency had been done on and after
data collection. Based on the data edit specifications, syntaxes were written for checking
data consistencies. If the enumerator recorded wrong values, it flags error messages.
The supervisor reviewed whether the uploaded data were error free and qualified the
stated points. If some errors were recorded on the uploaded data, the supervisor
rejected the data to the respective enumerator by writing comments about the errors.
If the data were error-free, consequently approved by the supervisor.
Testing approaches included microbiological, chemical, and physicochemical analysis. All
household- and source-level samples were tested for E. coli and a subset (1 per EA) were also
tested for enterococci at the household-level. For every water sample measured for E. coli or
148 Maintaining the Momentum while Addressing Service Quality and Equity
enterococci, two CompactDry growth plates (Nissui, Japan) were used. One was inoculated
with 1 milliliter of test water, while the other was used with a portable membrane filter (Millipore
Microfil®), which contained all of the bacteria filtered from a 100 milliliter sample. The
microbiological tests were incubated at 35°C for at least 24 hours using portable MX45 electric
incubators (Lynd, U.K.). After incubation, the number of visible colonies (or colony-forming
units, CFU) were counted. The 100 milliliter test result should therefore be expected to be
approximately 100 times as high as the 1 milliliter test result. When teams found more than
100 colonies on a growth plate the results were reported as “>100.”
During analysis of microbiological data the results from the 1 milliliter sample and the 100 milliliter
sample were combined to produce risk categories. In a minority of cases, test results from the two
volumes were inconsistent and no risk category was assigned. For example, if the 1 milliliter test
showed 10 colonies but the 100 milliliter test shows only five colonies.
In addition to the microbiological tests, assessments for chlorine residual and turbidity were
conducted onsite using photometric methods and samples were collected for subsequent analysis
in a central laboratory in Addis Ababa. Chlorine residual was measured using DPD tablets according
to the manufacturer’s instructions (Hach, USA). A 10 milliliter vial was first rinsed with water and
then filled with 10 milliliter to which a tablet was added and then crushed. Intensity of the color
change was used to assess the level of residual chlorine and the result (milligram per liter). The
results are reported as either <0.2 milligrams per milliliter (low), 0.2–0.5 milligram per milliliter
(moderate) or >0.5 milligram per milliliter (high). Turbidity was measured using a turbiditimeter
(Lovibond, U.K.) with care taken to ensure that vials were cleaned thoroughly and free of marks
such as fingerprints. Results were classified as <0.5 NTU (low), 0.5–1 NTU (moderate), >1 NTU
(high). Chlorine residual and turbidity photometers were calibrated in advance of the fieldwork.
For the laboratory testing, water samples were collected from each unique water source in
a given cluster and a barcode was used to keep track of these samples. No household-
level samples were collected as it was not anticipated that the values would change
substantially from the source. These samples were stored in regional offices and then
transferred to the central laboratory (Waterworks Enterprise, Addis Ababa) and all analyses
were completed within six months of the fieldwork. Parameters tested in the laboratory
were fluoride, hardness, electrical conductivity, and iron. Fluoride concentrations were
assessed using the SPADNS method. Levels of fluoride exceeding the national standard
and WHO guideline value of 1.5 milligram per liter were recorded as “high.” Given the
importance of fluoride from a public health perspective, in addition to the water quality
samples additional “blinded” tests were sent to the central laboratory to complement the
internal quality control procedures.
Results
The most common source for collecting low-risk water was piped on premises (47.2 percent),
while most of the very high risk water was collected from unimproved sources (63.3 percent)
especially unprotected springs (34.5 percent) and surface water (22.5 percent).
Table D.1 shows that 14 percent of the population collected water from low-risk supplies (with
no detectable E. coli), while 36.6 percent collected water from very high-risk supplies. Water
collected from improved sources was of better quality (20.2 percent low risk) than water
collected from unimproved sources (2.2 percent low risk). Water quality was better in large
towns (46.4 percent low risk) and worst in rural areas (8.4 percent low risk). Water quality was
best in Addis Ababa region (84.8 percent low risk), and worst in Southern Nations, Nationalities
and People Region (SNNPR) (7.1 percent low risk).
Water quality was the highest in bottled water (53.4 percent low risk), but less than 1 percent of
the population used this source of drinking water. Piped water on premises, used by 15 percent
Maintaining the Momentum while Addressing Service Quality and Equity 149
Table D.1: E. Coli Risk Levels at Point of Collection by Water Supply Type, Location, and Region in Ethiopia, 2017
Low risk: Moderate High risk: Very high E. coli at
E. coli < risk: E. coli E. coli risk: E. coli source
1 cfu/ 1–10 cfu/ 11–100 cfu/ >100 cfu/ (CFU/ Population
100 mL 100 mL 100 mL 100 mL 100 mL) (millions) Count
Total 14 23.2 26.2 36.6 100 90.2 4,402
Source of drinking water sample
Piped on premises 41.5 33.6 16.3 8.6 100 13.7 1,004
Piped water public tap/ 22.6 40.3 28.1 9.1 100 11.4 475
standpipe
Tube well/borehole 14.9 33.2 20.8 31.1 100 12.6 554
Protected dug well 3.1 16.8 48.1 32 100 4.1 230
Unprotected dug well 0.6 4.8 18.9 75.7 100 2.8 217
Protected spring 7.5 26.2 42.1 24.3 100 13.4 477
Unprotected spring 2.5 7.1 28.7 61.6 100 18.2 641
Rainwater collection 1 13.6 33.3 52.1 100 0.8 36
Piped water kiosk/retailer 27 29.8 19.9 23.4 100 1.6 115
Bottled water 53.4 23.6 17.7 5.3 100 0.4 40
Cart with small tank/drum 3.5 69.4 6.2 20.9 100 1.2 46
Surface water 0.2 0.7 14 85 100 9 481
Other 18.3 34 15.6 32.1 100 1 86
Type of drinking water source
Unimproved 2.2 5.9 23.2 68.7 100 31 1,425
Improved 20.2 32.2 27.7 19.9 100 59.2 2,977
Location type
Rural 8.4 22.2 27.8 41.6 100 72.7 3,019
Urban (small town) 14.1 28.7 29.6 27.7 100 4.8 345
Urban (large town) 46.4 26.8 15.4 11.4 100 12.6 1,038
Urban (all) 37.4 27.3 19.3 15.9 100 17.5 1,383
Region
Addis Ababa 84.8 12.8 1 1.3 100 3.3 195
Amhara 10.9 17.5 26.6 45 100 21.7 905
Oromia 11.4 24.9 26.5 37.2 100 34.9 844
SNNPR 7.2 30.6 30.1 32.1 100 19.3 1,025
Tigray 23.8 19.4 25.7 31.2 100 5.4 542
All other 14.7 18.7 24.2 42.4 100 5.6 891
Source: ESS-WQT 2016.
Note: SNNPR = Southern Nations, Nationalities and People Region.
of the population (table D.1), had relatively good water quality, with 42.4 percent low risk, and
9.8 percent very high risk. Water collected from kiosks or retailers was often of good quality
(33.1 percent low risk). Very high-risk water was most commonly collected from unimproved sources
(69.4 percent), especially surface water (85.8 percent) and unprotected dug wells (72.6 percent).
It is well known that microbiological contamination tends to increase when water is stored in
the household after collection. In some cases, particularly when the quality is poor at the
150 Maintaining the Momentum while Addressing Service Quality and Equity
collection point, or when water is treated at the household level, there can be a decrease in
fecal indicator bacteria between the source and household. Figure D.1 compares the E. coli risk
levels at the collection point to the risk levels at the household level (in a glass of water
provided for drinking). The cells on the diagonal, shaded yellow, represent households in which
the risk class was the same at both testing points. This was the case for 50.1 percent of the
population. In a few cases (10.4 percent, shaded green or dark green) E. coli levels decreased
between collection and the household, but it was more common that E. coli levels would
increase moderately (26 percent) or substantially (13.5 percent).
Unimproved sources, which are more contaminated, were more likely to see a decrease in risk
after collection than improved sources. This is especially true of surface water, which was the
most highly contaminated source. Households that reported treating water at the household
level were more likely to see a decrease in E. coli levels (18.1 percent) than households that
did not report treatment (9.5 percent). However, only 5 percent of the population reported
water treatment. Highlights of the chemical and physicochemical analysis include the following:
•• Fluoride in drinking water at the point of collection: 3.8 percent of samples were above
the Ethiopian national standard for fluoride in drinking water (1.5 milligram per liter),
which is also the WHO Guideline Value.
•• Iron in drinking water at the point of collection: 53.8 percent of samples were above the
Ethiopian national standard for iron in drinking water (0.3 milligram per liter). Of these
5.6 percent of samples were above 1 milligram per liter. There is no health-based WHO
Guideline Value for iron in drinking water.
•• Hardness in drinking water at the point of collection: 11.2 percent of samples were above
the Ethiopian national standard for hardness in drinking water (300 milligram per liter) (as
CaCO3). There is no health-based WHO Guideline Value for hardness in drinking water.
Electrical conductivity in drinking water at the point of collection: 6.4 percent of samples were
above 800 micro-Siemens per centimeter. There is no Ethiopian national standard for
electroconductivity in drinking water, nor is there a WHO Guideline Value for this parameter.
Figure D.1: E. Coli Risk Levels at Collection Point and Household Level in Ethiopia, 2017
E. coli at collection point
<1 1_10 11_100 >100 Total
<1 3.7 0.8 0.5 0.2 5.3
E. coli in the glass
1_10 3.2 4.1 1.7 0.9 9.9
11_100 5.2 12.3 13.3 6.2 37
>100 1.7 6.5 10.5 29 47.8
Total 13.9 23.8 25.9 36.4 100
1.7 Large decrease
8.7 Slight decrease
50.1 No change
26 Slight increase
13.5 Large increase
Maintaining the Momentum while Addressing Service Quality and Equity 151
Availability and Sufficiency of Water
Availability is an important criterion for assessing drinking water service levels.2 In the Ethiopia
Socioeconomic Survey–Water Quality Testing Component (ESS-WQT 2016) water quality
module, two questions were asked about availability and sufficiency of water:
1. In the past two weeks, was the water from this source not available for at least one full day?
2. Has there been any time in the last month when you did not have water in sufficient
quantities?
If the answer to the second question was yes, the respondent was asked the main reason that
he/she did not have water in sufficient quantities.
Table D.2: Availability and Sufficiency of Water, by Technology and Location, 2016
Available Sum Count Sufficient Sum Count
Total 77.5 1406620281 4407 75.4 1371148145 4413
Source of drinking water sample
Piped on premises 38 120728554 1004 48.1 153033817 1005
Piped water public tap/standpipe 66.1 145219167 477 71 156335517 479
Tube well/borehole 92.8 240259843 554 85 220152732 554
Protected dug well 93.4 69520699 230 83.2 61929773 230
Unprotected dug well 88.2 46454028 218 78.7 41747905 219
Protected spring 95.8 247322852 474 94.6 244565055 475
Unprotected spring 93.4 332661389 645 88 313337470 645
Rainwater collection 59.3 9637861 37 50.6 8237452 37
Piped water kiosk/retailer 25.3 9700015 113 35.9 13793835 114
Bottled water 76.9 8500189 40 68.2 7537796 40
Cart with small tank/drum 17.5 3887253 46 7.1 1571749 46
Surface water 94.5 161543236 484 82.3 140780241 484
Other 57.6 11221447 86 41.9 8161055 86
Improved water source
Unimproved 92.2 551588773 1430 84.2 503735344 1431
Improved 70.2 855067761 2978 71.2 867449054 2983
Location type
Rural 87.7 1211338396 3023 83.4 1152437165 3026
Small town (urban) 58.2 61544290 345 52.6 55604246 345
Large town (urban) 40.4 131608576 1038 49.2 160977715 1041
Region
Addis Ababa 34.3 25861173 195 55.1 41519866 195
Amhara 81.4 408487400 911 74.1 371750586 911
Oromia 77.1 504529347 836 77.1 505253405 839
SNNPR 82.8 296386519 1024 80.3 288101852 1026
Tigray 76.9 89904630 545 73.1 85417072 545
All other 74.6 81451211 896 72.2 79105363 897
Source: ESS-WQT 2016.
Note: SNNPR = Southern Nations, Nationalities, and People Region.
152 Maintaining the Momentum while Addressing Service Quality and Equity
Safely Managed Water
The four subindicators of improved, on premises, available (sufficient), and low E. coli risk can
be combined to create the safely managed drinking water services indicator. This combination
can be done at different scales (e.g., national, urban, or rural). If the four subindicators are
combined at the household level, only 3.4 percent of households are considered to be
accessing safely managed drinking water services.
Table D.3: Safely Managed Drinking Water Services in Ethiopia, 2016
On
premises Sufficient Safely Safely
and and Quality and managed managed
Improved improved improved improved (household) (domain)
Total 66 18.2 46.9 13.2 3.4 13.2
Source of drinking water
sample
Piped on premises 100 100 42.3 41.5 21.4 41.5
Piped water public tap/ 100 0 73.5 22.6 0 0
standpipe
Tube well/borehole 100 1.3 84.7 14.9 0 1.3
Protected dug well 100 9.3 84.7 3.1 0 3.1
Protected spring 100 0 94.9 7.5 0 0
Rainwater collection 100 88.3 65.5 1 0 1
Piped water kiosk/retailer 100 0 34 27 0 0
Bottled water 100 100 76.2 53.4 44 53.4
Cart with small tank/drum 100 0 7.7 3.5 0 0
Location type
Rural 58.8 4.7 48.2 7.4 0.1 4.7
Urban (small town) 89.3 49.2 44.9 14 5.3 14
Urban (large town) 95.5 77.6 41 46.4 21.7 41
Urban (all) 93.8 69.8 42.1 37.4 17.1 37.4
Region
Addis Ababa 99.7 93.7 51.3 84.8 45.6 51.3
Amhara 61.4 14.7 45.4 10.6 2 10.6
Oromia 66.1 14.8 45.9 10.4 0.9 10.4
SNNPR 66.4 14.1 50.3 6.7 1.6 6.7
Tigray 71.9 22.8 53.7 23.8 7.1 22.8
All other 56.1 16.5 38.9 11.2 2.7 11.2
Consumption quintiles
Poorest 56.1 3.8 44.7 7.5 0.3 3.8
Poor 67.9 7.6 52.2 8.1 0.8 7.6
Middle 66.8 13.5 50.4 9.6 1.3 9.6
Rich 64.1 21.4 42.3 13.9 3.6 13.9
Richest 80.7 48.2 47.1 31.9 12.7 31.9
Source: ESS-WQT 2016.
Note: SNNPR = Southern Nations, Nationalities and People Region.
Maintaining the Momentum while Addressing Service Quality and Equity 153
However, because these subindicators in some cases will come from different data sources,
and therefore cannot always be combined at the household level, the JMP will estimate the
safely managed indicator by combining subindicators at the scale of the domain for which
estimates are being made. In this case, the safely managed indicator will be taken to be the
lowest of the four subindicator elements at that scale. For example, at the national scale in
Ethiopia, E. coli risk is the subindicator with the lowest value (13.2 percent), so this would be
taken as the estimate of safely managed drinking water services in Ethiopia from the ESS-WQT
survey.
Table D.3 shows the four subindicators, highlighting in red the subindicator that is the lowest
among the four, and therefore determines the overall indicator of safely managed drinking
water services. In most cases the quality subindicator is the limiting factor, but in rural areas
and for some technologies on premises is the limiting factor. In large towns and in the Addis
Ababa region, the availability subindicator is the lowest and drives the safely managed indicator.
Notes
1. The LSMS-ISA is a regional project funded by the Gates Foundation that supports seven
countries in Sub-Saharan Africa to collect multitopic panel household level data with a
special focus on improving agriculture statistics and the link between agriculture and other
sectors in the economy. It aims to build capacity, share knowledge across countries, and
improve survey methodologies and technology. The project in Ethiopia is implemented by
the Central Statistical Agency.
2. The human right to water specifies that water should be “available continuously and in a
sufficient quantity to meet the requirements of drinking and personal hygiene, as well as
of further personal and domestic uses, such as cooking and food preparation, dish and
laundry washing and cleaning. Supply needs to be continuous enough to allow for the
collection of sufficient amounts to satisfy all needs, without compromising the quality of
water.”
Reference
WHO/UNICEF. 2013. Second Meeting of the WHO/UNICEF JMP Task Force on Monitoring
Drinking-water Quality. Geneva: WHO. http://www.wssinfo.org/fileadmin/user_upload
/resources/2013-Water-Quality-Task-Force-Report-Final.pdf.
154 Maintaining the Momentum while Addressing Service Quality and Equity
Appendix E
Logit Regression Model for
Improved Water on Premises
in Urban Areas of Ethiopia
Piped water on premises is associated with economic benefits, especially time saved in
collecting water from stand posts. However, access to piped water on premises is skewed
toward wealthier consumption quintiles. Multivariate regression confirms this inequitable
capture of piped water on premises by higher income households and examined other variables
that may be correlated with this improved access.
The regression results show that independent of household income levels, piped water on
premises is siginificantly correlated with education level and the size of town. However,
improved access is not correlated with gender of head of household or the tenure status of
households.
Households in Addis were three times more likely to have access to piped water on premises
than medium or large towns. In turn, households in medium and large towns, other than Addis,
were over twice as likely to have access to piped water on premises than small towns. This
points to the need to channel more capital investment to smaller towns to help them catch up
with larger towns. In addition, given that piped water supply on premises is principally provided
by utilities and that these utilities benefit from both capital and recurrent subsidies, greater
effort needs to be made to hook up poorer households regardless of town size.
Method and Data Sources
To examine the possible determinants of improved water supply on premises in urban areas of
Ethiopia a logit regression model was estimated using data from the Ethiopia Socioeconomic
Survey (ESS) 2015–16, a nationally representative survey of just under 5,000 households.
The dependent variable was household access to piped water on premises (HH without=0;
HH without=1).
Piped water supply on premises includes piped water into the dwelling or in the yard or plot that
the dwelling is in. It does not include any nonpiped water sources such as boreholes, wells, or
springs. The regression includes the following independent variables:
•• Urban consumption quintiles (dummy variables for each quintile based on consumption
quintiles built for urban areas)
•• Town strata (dummy variables for: small towns1 =0; medium and large size towns other
than Addis Ababa=1; Addis Ababa=2)
•• Level of education (dummy variable: not completed primary=0; completed primary=1;
secondary=2; tertiary=3)
Maintaining the Momentum while Addressing Service Quality and Equity 155
•• Gender of household head (dummy variable: female=0; male=1)
•• Tenure status of household (dummy variable: rents house=0; owns house=1)
•• Household size (continuous variable)
Results
Improved piped water on premesis was significatly correlated with (a) urban consumption
quintiles; (b) education level; (c) town stratum; and (d) household size.
Relative to the lowest urban consumption quintile the highest consumption quintile was five
times more likely to have access to piped water on premesis (see figure E.1). The likelihood of
accessing piped water on premises improves with increasing town size. Households in Addis
were six times as likely to have access to piped water on premises than small towns.
Households in medium and large towns, other than Addis, were over twice as likely to have
access to piped water on premises than small towns.
Access to improved water on premises is correlated with level of education. Though completion
of primary education was not significantly correlated with improved access, the odds ratio was
Figure E.1: Odds Ratio Results for Improved Water on Premises in Ethiopia, 2017
. xi: logistic water_premis i.con_quturb i.towndummy i.educ i.sexhead hh_size i.hhownwer[pw=factor_pop] ,c
> luster(psu)
i.con_quturb _Icon_qutur_1-5 (naturally coded; _Icon_qutur_1 omitted )
i.towndummy _Itowndummy_0-2 (naturally coded; _Itowndummy_0 omitted )
i.educ _Ieduc_0-3 (naturally coded; _Ieduc_0 omitted)
i.sexhead _Isexhead_0-1 (naturally coded; _Isexhead_0 omitted)
i.hhownwer _Ihhownwer_0-1 (naturally coded; _Ihhownwer_0 omitted )
Logistic regression Number of obs = 1,62 3
Wald chi2(12) = 125.6 9
Prob > chi2 = 0.0000
Log pseudolikelihood = -10686245 Pseudo R2 = 0.180 2
(Std. Err. adjusted for 143 clusters in psu)
Robust
water_premis Odds Ratio Std. Err. z P>|z| [95% Conf. Interval ]
_Icon_qutur_2 2.807555 .7263403 3.99 0.000 1.690887 4.66167 4
_Icon_qutur_3 3.250561 1.06162 3.61 0.000 1.713797 6.16534 2
_Icon_qutur_4 4.513481 1.642123 4.14 0.000 2.212189 9.20875 8
_Icon_qutur_5 5.034557 1.925202 4.23 0.000 2.37938 10.6526 7
_Itowndummy_1 2.234137 .6698225 2.68 0.007 1.241392 4.02078 4
_Itowndummy_2 6.925044 2.279119 5.88 0.000 3.633134 13.1996 9
_Ieduc_1 1.193993 .2575607 0.82 0.411 .7823223 1.8222 9
_Ieduc_2 2.569214 .6336868 3.83 0.000 1.584363 4.16625 6
_Ieduc_3 2.952135 .8265819 3.87 0.000 1.705314 5.11055 5
_Isexhead_1 .884194 .1701049 -0.64 0.522 .6064428 1.28915 5
hh_size 1.192363 .0715682 2.93 0.003 1.060029 1.34121 8
_Ihhownwer_1 1.016193 .2227904 0.07 0.942 .6612387 1.56168 6
_cons .0933795 .0387694 -5.71 0.000 .0413855 .210695 1
Source: World Bank.
156 Maintaining the Momentum while Addressing Service Quality and Equity
above one. Households in which a member had completed secondary or tertiary education
were two to three times more likely to have access to piped water on premises, as compared
to the reference group of households in which no member had completed primary school.
Neither the gender of head of household nor the tenure status of the household were
associated with improved access to piped water on premises. Increasing household size was
correlated with increased access to piped water on premises. Further analysis is requred to
understand this relationship.
Note
1. CSA defines small towns based on population estimates from the 2007 Population
Census; a town with the population of less than 10,000 is a small town (Ethiopia
Socioeconomic Survey Wave Three (2015/2016) Basic Information Document, 13).
Maintaining the Momentum while Addressing Service Quality and Equity 157
Appendix F
Logit Regression Model for
Shared Sanitation in Urban
Areas of Ethiopia
This regression analysis examines variables that may be correlated with increasing or
decreasing the likelihood that households share toilet facilities. The results indicate that
households were more likely to share toilet facilities in larger towns than in small towns.
Households were significantly less likely to share toilet facilities where they owned rather than
rented the house they lived in.
Households in the highest urban consumption quintile were less likely than other households
to share toilet facilities. However, for other consumption quintiles there was not a significant
correlation with shared use of toilet facilities. The variables for education level, gender of
household head, and even use of an improved toilet facility were not significantly correlated
with shared use of toilet facilities. As towns get larger, households tend to increase the sharing
of toilet facilities. The results of this regression suggest that it would be worth investing further
the relations between tenure status of household and the sharing of toilet facilities.
Method and Data Sources
To examine the possible determinants of shared use of toilet facilities in urban areas of
Ethiopia a logit regression model was estimated using data from the Ethiopia Socioeconomic
Survey (ESS) 2015–2016, a nationally representative survey of just under 5,000 households.
The dependent variable was household sharing of toilet facilities (toilet facility not shared=0;
shared=1).
Households that reported resorting to open defecation were omitted from the observations
since they had no shared facility. All other households were included whether they had a basic
unimproved or an improved facility. The regression model included the following independent
variables:
•• Urban consumption quintiles (dummy variables for each quintile based on consumption
quintiles built for urban areas)
•• Town strata (dummy variables for: small towns=0; medium size towns=1; Addis Ababa=2)
•• Level of education (dummy variable: not completed primary=0; completed primary=1;
secondary=2; tertiary=3)
•• Gender of household head (dummy variable: male=0; female=1)
•• Household size (continuous variable)
•• Type of toilet facility used (dummy variable: not improved=0; improved=1)
•• Tenure status of household (dummy variable: rents house=0; owns house=1)
Maintaining the Momentum while Addressing Service Quality and Equity 159
Results
The only variables that had a significant corelation with shared use of toilet facilities were
(a) town stratum; (b) tenure status of household; (c) the highest consumption quintile; and
(d) household size. Households living in regional capitals and Addis were almost three times
more likely to share toilet facilities than households in smaller towns. People who owned the
house they lived in were almost three times less likely to share toilet facilities with other
households than people who rent the house they live.
Households in the highest urban consumption quintile were less likely to share toilet facilities
with other households, though for lower consumption quintiles no significant correlation was
found. Households with greater numbers of household members were also less likely to
share toilet facilities with other households. The squared function of household size was
examined in a separate model but was not found to be significant. This last result requires
further investigation to understand the relation between household size and sharing of
toilet facilities.
Figure F.1: Odds Ratio Results for Sharing of Toilet Facilities in Ethiopia
. xi: logistic sharelatr i.con_quturb i.towndummy i.educ i.sexhead hh_size i.hhownwer i.imp_lat[pw=facto
> r_pop], cluster(psu)
i.con_quturb _Icon_qutur_1-5 (naturally coded; _Icon_qutur_1 omitted )
i.towndummy _Itowndummy_0-2 (naturally coded; _Itowndummy_0 omitted )
i.educ _Ieduc_0-3 (naturally coded; _Ieduc_0 omitted )
i.sexhead _Isexhead_0-1 (naturally coded; _Isexhead_0 omitted)
i.hhownwer _Ihhownwer_0-1 (naturally coded; _Ihhownwer_0 omitted )
i.imp_lat _Iimp_lat_0-1 (naturally coded; _Iimp_lat_0 omitted)
Logistic regression Number of obs = 1,50 9
Wald chi2(13) = 122.5 9
Prob > chi2 = 0.0000
Log pseudolikelihood = -11132626 Pseudo R2 = 0.135 0
(Std. Err. adjusted for 142 clusters in psu)
Robust
sharelatr Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
_Icon_qutur_2 1.05111 .27208 0.19 0.847 .6328704 1.74575
_Icon_qutur_3 .9732969 .2616244 -0.10 0.920 .5746989 1.648353
_Icon_qutur_4 .9751355 .275745 -0.09 0.929 .5602288 1.697323
_Icon_qutur_5 .5868164 .1629297 -1.92 0.055 .3405383 1.011203
_Itowndummy_1 2.797032 .7642045 3.76 0.000 1.637315 4.77818
_Itowndummy_2 2.742771 .9078314 3.05 0.002 1.433672 5.24722
_Ieduc_1 1.156627 .2494829 0.67 0.500 .7578622 1.76521
_Ieduc_2 1.240276 .2542981 1.05 0.294 .829838 1.853715
_Ieduc_3 1.34664 .3641433 1.10 0.271 .7926453 2.287831
_Isexhead_1 .8724282 .1484826 -0.80 0.423 .6249709 1.217866
hh_size .7830279 .0409694 -4.67 0.000 .7067094 .8675882
_Ihhownwer_1 .3871289 .0639282 -5.75 0.000 .2800872 .5350791
_Iimp_lat_1 .9463606 .205139 -0.25 0.799 .6187923 1.447333
_cons 2.679607 1.079112 2.45 0.014 1.216975 5.900119
Source: World Bank data.
160 Maintaining the Momentum while Addressing Service Quality and Equity
Appendix G
Supply- and Demand-Side
Barriers Households Face in
Hooking Up to Utilities
Household survey samples are based on geographic clusters that at least for urban areas are
physically small, amounting to no more than a few city blocks. It is therefore possible at least
in urban areas to study the extent to which people lacking access to infrastructure live in
clusters where infrastructure is available (indicated by the fact that some immediate neighbors
are hooked up to the service). The resulting analysis gives us a sense of the degree to which
low access to services is driven by supply-side issues (infrastructure networks not reaching the
areas where people live) or by demand-side issues (people not connecting to available
infrastructure networks).
The basic concepts used to analyze this issue are defined in box G.1. The main novelty is that
we decompose the traditional measure of household coverage into two components (as per
Foster and Araujo 2004; Komives et al. 2006). The first, which we call access, gives the
percentage of the population that lives in a cluster where at least one household has service
coverage, indicating that the infrastructure is physically proximate and that there could be an
opportunity to connect. The second, which we call hook up, gives the percentage of the
population living in clusters where the service is available that actually make a connection, and
hence take up that opportunity. Using these two concepts it is possible to estimate the
percentage of the unserved population that constitutes a supply-side deficit (meaning that they
are too far from the network to make a connection until further rollout takes place) compared
to a demand-side deficit (meaning that something other than distance from the network is
preventing them from taking up the service).
The policy conclusions in each case are very different, and hence the interest in making this
distinction. The solution to a supply-side deficit is to make further investments to rollout the
geographic reach of infrastructure networks. The solution to a demand-side deficit is to make
policy changes that help to address potential barriers to service take-up, such as high
connection charges or illegal tenure.
For various reasons, it could be questioned whether absolutely everyone in a geographic cluster
with some coverage really has the opportunity to connect. First, although the geographic
clusters are relatively small in urban areas, the distances may still be such as to prohibit
connection. Second, even though the infrastructure is present, it may not have the carrying
capacity required to service all residents in a particular geographic cluster without further
investment and upgrade. Third, even if a household is physically close to a network with
adequate carrying capacity, the household may choose not to connect simply because there is
an acceptable alternative (such as a borehole) rather than due to any demand-side barriers
with the service.
Maintaining the Momentum while Addressing Service Quality and Equity 161
Box G.1: Coverage, Access, and Hook-Up Rates: Relationships and Definitions
Coverage rate = number of households using the service / total number of households
Access rate = number of households living in communities or clusters where service is
available / total number of households
Hook-up rate = number of households using the service / number of households living in
communities where service is available
Coverage = access rate × hook-up rate
Unserved population = 100 − coverage rate
Pure demand-side gap = access rate − coverage rate
Supply-side gap = unserved population − pure demand-side gap
Pure supply-side gap = supply side gap × hook-up rate
Mixed demand and supply side gap = supply side gap × (100 − hook-up rate)
Proportion of deficit attributable to demand-side factors only = pure demand side gap /
unserved population
Proportion of deficit attributable to supply-side factors only = pure supply side gap / unserved
population
Proportion of deficit attributable to both demand and supply side factors only = mixed demand-
and supply-side gap / unserved population
Wodon et al. (2009) use a statistical approach to try and correct for these problems.
They simulate the maximum connection rate obtainable in any primary sampling unit (PSU)
based on that of the richest households in that PSU. If less than 100 percent of the richest
households are connected, it suggests that something other than demand-side barriers is at
work. Results for the demand-side deficit are presented both with and without this statistical
adjustment. The methodology is less applicable to rural areas because the PSUs tend to be
larger in size and population densities much lower.
References
Wodon, Quentin, Sudeshna Banerjee, Amadou Bassirou Diallo, and Vivien Foster. 2009. “Is
Low Coverage of Modern Infrastructure Services in African Cities due to Lack of Demand
or Lack of Supply?” Policy Research Working Paper 4881. World Bank, Washington, DC.
Foster, Vivien, and Maria Caridad Araujo. 2004. “Does Infrastructure Reform Work for the Poor?
A Case Study from Guatemala.” Policy Research Working Paper 3185. World Bank,
Washington, DC. https://openknowledge.worldbank.org/handle/10986/13877.
Komives, Kristin, Jonathan Halpern, Vivien Foster, Quentin T. Wodon, and Roohi Abdullah. 2006.
“The Distributional Incidence of Residential Water and Electricity Subsidies.” World Bank
Policy Research Working Paper 3878. World Bank, Washington, DC. https://ssrn .-com
/abstract=936032.
162 Maintaining the Momentum while Addressing Service Quality and Equity
Appendix H
One WASH National Program:
Institutional and Implementation
Arrangements
The WASH Implementation Framework (WIF) set out that planning, implementation, monitoring,
and evaluation would be coordinated through establishment of water supply, sanitation, and
hygiene (WASH coordination) structures at national, regional, zonal, woreda, and kebele levels.
The coordination structure is guided by the steering committees and technical teams formed
by the WASH sector ministries and corresponding regional sector bureaus, as illustrated in
figure H.1. The four sector ministries have committed themselves to assign an appropriate
official to the National WASH Technical Team (NWTT), to establish a project management unit
(PMU) and to assign a WASH focal person to liaise between the PMU and the National WASH
Coordination Office (NWCO) and to implement decisions of the ministries and the National
WASH Steering Committee (NWSC). While there remains mandatory vertical communication
within each WASH sector ministry and bureau, there also aims to be horizontal communication
and linkage between different WASH sector ministries’ and bureaus’ PMUs, and between
corresponding WASH coordination offices and PMUs based on signed memorandums of
understanding (MoUs) between the sectors.
Despite significant and encouraging activities of the NWSC, some of the constraints affecting
the execution of the decisions according to the guidelines include (a) delay of budget release
and “no objection” from donors; (b) delay of major procurements and long processes; (c) and
lack of regular and frequent meetings to deliberate on emerging issues. The NWCO has a
critical role in ensuring policies, strategy plans, and decisions of the NWSC and NWTT are
effectively communicated at all levels. While some progress has been made in establishing
and operationalizing the One WASH National Programme (OWNP) coordination structure as set
out in the WIF, there are also significant gaps in that need to be strengthened to fully
operationalize the proposed structures and fully implement their envisaged role.
Regions have the authority and the responsibility to establish institutional arrangements at the
regional and zonal levels that are best suited to their particular needs and circumstances.
However, regional arrangements were expected to correspond with those at the federal level to
ensure effective linkages. However, at regional authorities lack a uniform understanding of
OWNP concepts on the different implementation modalities and guidelines among members of
steering committees, technical teams, and PMUs. There are also mixed perceptions concerning
the management and financing of the OWNP , as well as the relationship between the OWNP and
the Consolidated WASH Account (CWA). CWA-funded activities are typically referred to in the
regions as OWNP activities. The OWNP covers all national WASH activities regardless of the
source of finance, but there is a need for wider awareness raising to build a proper understanding
for the CWA and OWNP .
It has taken a significant amount of time to establish regional WASH coordination offices
(RWCOs), and many regions still don’t have fully functioning mechanisms. RWCOs have
been slow to be established due to lack of clear understanding on the specific roles of the
RWCO, limited guidance on the required number and professional mix of the staff, and
sources of budget. Most of the regional steering committees have delegated the water
Maintaining the Momentum while Addressing Service Quality and Equity 163
Figure H.1: Schematic of the OWNP Institutional and Implementation Arrangement
Nat. Water Nat. MOFEC
National WASH National PMU PMU National WASH
steering WASH coordination
committee technical team Nat. Health office
Nat. Ed. PMU
PMU
Reg. Water Reg. MOFEC
PMU Regional WASH
Regional WASH PMU
Regional WASH coordination
steering office
technical team Reg. Health
committee Reg. Ed. PMU
PMU
Zonal WASH
management team
Woreda WASH Town/City WASH
WASHCO Woredas WASH
steering committee steering committee
coordination office
(woreda cabinet) (town/city cabinet)
Note: MOFEC = Ministry of Finance and Economic Cooperation; OWNP = ONE WASH National Programme; PMU = project
management unit; WASHCO = water supply, sanitation, and hygiene committee.
sector PMUs to take the responsibilities of the program coordination, on top of their regular
duties and responsibilities.
The lack of regional OWNP strategic plans and absence of effective coordination and systems
of accountability continue to be a hindrance to alignment. This is further compounded by the
continuation of multiple (unaligned) steering and technical committees for each of WASH
programs financed through different channels.
With regard to linkages and harmonization of WASH activities, woreda- and kebele-level program
planning and implementation is mainly concentrated on the rural water supply development
with little attention for institutional WASH and harmonization of household and community
WASH activities. While WASHCOs play major role in expansion of water supply and provision of
quality services, health extension workers (HEWs) are active in expansion of household level
sanitation and hygiene activities. However, the availability of water supply is not integrated with
the promotion of sanitation and hygiene services. Therefore, in general, integration and
harmonization at woreda and kebele levels is grossly inadequate.
In towns, WIF structures have not been established with exception of PMUs in few World Bank–
supported towns. The coordination structures do not exist and were a major factor for
challenges in the implementation of urban sanitation projects.
Furthermore, participation of the community and the private sectors (for repair and maintenance
as well as spare parts) is lacking. Community participation in most regions, woredas, and
schemes is limited to planning and collection of contribution for repair and maintenance in
times of needs. Communities also participate in setting affordable user charges, bylaws to
alienate free riders, and support to the vulnerable groups. However, general assemblies,
general meetings and discussions with the WASHCOs to deliberate on problems, the financial
status of the schemes, implementation efficiency, and management effectiveness are very
limited in almost all schemes.
164 Maintaining the Momentum while Addressing Service Quality and Equity
Appendix I
Woreda-Level Financing
Block grants received by woredas are allocated by the woreda councils between sectors based
on the priorities of the woreda, consistent with federal and regional priorities. Allocation of
limited public resources among key sectors mainly depend on the magnitude of the problem;
cost of achieving the targets in each sector; and federal, regional, and woreda priorities. Water
supply, sanitation, and hygiene (WASH) is often not prioritized. Unlike policies toward roads,
power, and education, WASH is not considered a productive investment that stimulates
economic growth—which is a wrong approach. In addition, interventions in the water supply are
dependent on the availability of water source, which is sometimes complex, costly, and beyond
the capacity of local governments. Sanitation and hygiene activities, especially in rural areas,
are mainly focused on education and behavioral change, which are not tangible compared to
investment in physical assets.
Despite this, WASH was among the priority sectors classified as pro-poor in the Government of
Ethopia’s (GoE’s) economic and social development plans (Sustainable Development and
Poverty Reduction [SDPRP], A Plan for Accelerated and Sustained Development to End Poverty
[PASDEP], and Growth and Transformation Plan [GTP]). As a result, the amount of public
resource allocated for WASH has increased steadily over the last two decades. The findings of
the World Bank’s public expenditure review on WASH revealed that between 2008/09 and
2011/12 sector expenditure increased from 0.4 percent to 0.7 percent of GDP . The sector
share of total expenditure increased from 2 percent to 3.5 percent and has been stable at
about US$2 per capita for the periods 2008/09 to 2011/12.
Table I.1 reveals that per capita public expenditure (obtained from the BOOST data for 720
woredas) is relatively higher in regions where access to improved water supply was lower in
2007. Both the per capita expenditure and the change in access to improved water supply in
2011 (NWI) compared to 2007 are higher in Benishangul, Gambella, Amhara, and Afar regions.
However, the average size of the per capita expenditure is very small. When reviewing the per
Table I.1: Average Per Capita Expenditure by Region in Ethiopia and Change in Access to Improved
Water Supply
Average per capita Access to Access to
Woredas capital expenditure, Improved water Improved water
Region (no.) 2010–12 supply, 2007 (%) supply, 2011 (%)a Change (%)
Benishangul-Gumuz 20 33.49 15.9 59.7 43.8
Gambella 13 79.66 30.5 64.7 34.2
Amhara 138 11.47 24.9 51.6 26.7
Oromia 276 8.70 24.2 49.8 25.5
SNNPR 145 2.73 25.9 42 16.1
Afar 30 15.67 20.2 34.8 14.6
Tigray 45 5.06 51.8 52.7 1
Total 720 9.42 25.1 48.5 23.4
Source: World Bank based on BOOST data.
Note: SNNPR = Southern Nations, Nationalities, and People Region.
a. Findings of the National WASH Inventory conducted in 2011.
Maintaining the Momentum while Addressing Service Quality and Equity 165
Table I.2: Ethiopian Woredas with Reported Capital Expenditure, 2010–12
Capex only Capex only Capex in
Regions Capex (no.) in 1 year in 2 years all 3 years Total
Afar 1 8 10 11 30
Amhara 15 8 29 86 138
Benishangul-Gumuz 4 6 8 2 20
Gambella 12 1 13
Oromia 30 5 30 211 276
SNNPR 41 38 29 37 145
Somali 52 1 53
Tigray 19 8 10 8 45
Total 174 74 116 356 720
Source: World Bank based on BOOST data.
Note: CAPEX = capital expenditure; SNNPR = Southern Nations, Nationalities, and People Region. Empty cells represented data that was not available.
capita figures it should be noted that there are significant variations in unit costs of providing
the services depending on their specific situations, including remoteness, source of water,
population density, availability and cost of labor, and construction materials. Reliability of
data could also be a challenge since data are based on administrative reports rather than
national surveys.
As shown in table I.2, out of 720 woredas with expenditure information, 174 did not allocate
any capital budget for the three years (2010–12), 74 allocated in one of the three years,
116 in two of the three years, and 356 for all three years. However, the amount of the public
expenditure allocated was very small, even in the 356 woredas that did consistently allocate
budget during the period.
Having no capital expenditure allocated to water supply and sanitation services at the woreda
level does not mean that there was no investment on improving coverage in these woredas.
While the provision of water supply and sanitation services is decentralized to the woreda
level, in practice the task is still largely performed by regional and zonal offices. Currently,
most schemes are constructed by zones or regions (except small schemes such as hand-dug
wells and on spot springs), with their budget proclaimed at the regional level. There is no
relationship between per capita spending on water supply by the woredas and access to
improved water supply.
While the shortage of resources to cover the huge service gap is a major constraint in the
sector, the efficient allocation of resources to ensure sustainability of the existing service is an
area that also needs to be explored. The non-functionality rate in rural water supply schemes
are as high as 25 percent, and nonrevenue water (NRW) in the urban water supply system is
about 40 percent.1
The findings of the public expenditure review on water supply has revealed that between
2008/09 and 2011/12, only 55 percent of the total government budget was allocated to
capital budget, while in the WASH sector this proportion is significantly higher (81 percent). The
proportion of capital budget for the WASH sector is relatively lower (80 percent) at local than
at the federal levels, where it is 89 percent.
166 Maintaining the Momentum while Addressing Service Quality and Equity
Note
1. Recently conducted WASH Facility Survey covering 54 woredas and 50 towns in all the
regions and Dire Dawa City Administration reveals that about 44.2 percent of the rural
water supply schemes work for less than four hours per day, and 64.1 percent of rural
water supply schemes failed at least once or more times in the last 12 months for an
average of 51 days with frequency of four. The same survey indicates that about
44.6 percent of households consume less than 10 liters per capita, and almost a quarter
of the samples consume between 10–15 liters. The average consumption of households
benefiting from schemes with a downtime of less than five days is 1.2 times higher than
schemes with a downtime of more 20 days. The average downtime contributes to variation
in supply and consumption levels. The average consumption of households benefiting from
schemes with downtime of less than five days is 1.2 times higher than schemes with
downtime of more 20 days.
Maintaining the Momentum while Addressing Service Quality and Equity 167
Appendix J
WASH and Health: Defining
Exposure Risk Factors and
Model for Analysis
To better understand the relationship between water supply, sanitation, and hygiene (WASH),
nutrition, and health, this analysis has applied a WASH poverty risk model (WASH PRM)
(figure J.1) to assess patterns of disease risk across economic and geographic subpopulations
by combining rigorous estimates of the effects of exposure and susceptibility factors on
disease with country-specific data on the distribution of these risk factors. The primary purpose
of this model is to describe how diverse and interrelated risk factors may contribute to h
ow the national diarrheal disease burden is distributed between sub-population groups. The
association or causality between WASH and these outcomes is not possible as the data is
cross-sectional and prone to many biases, and is therefore not estimated.
The PRM model combines key susceptibility factors and exposure factors that are most relevant
to the health outcome of interest: diarrhea. The conceptual framework for the WASH PRM is
explained in figure J.1; “exposure factors” section includes WASH-related elements that
influence the risk of diarrheal disease. Relative risks are developed from the literature for
levels of these WASH services. Relative risks for individual exposure risk factors are combined
into a single exposure index. The “susceptibility factors” section of the conceptual framework
addresses individual risk factors that have been identified through rigorous evaluations and
meta-analyses. Quantitative risk estimates for each factor are combined into a single
susceptibility index. As described in figure J.1, we consider water supply and sanitation as
“exposure” factors, that is, as independent variables that influence our dependent outcomes
of interest (diarrheal disease, diarrheal mortality, and stunting).
Figure J.1: WASH Poverty Risk Model Conceptual Framework
Susceptibility factors
Underweight Vitamin A ORT
Water
WASH/Exposure factors
HH
Geography sanitation
Diarrhea Mortality
Poverty Sanitation
coverage Stunting
Hygiene Health outcomes
Note: WASH/exposure factors in light blue are not included in the exposure index. HH = household; ORT = oral rehydration
treatment; WASH = water supply, sanitation, and hygiene.
Maintaining the Momentum while Addressing Service Quality and Equity 169
Under the Millennium Development Goal (MDG) target for water supply and sanitation, access
to these two services was classified as improved or unimproved, with progress on improved
services contributing to progress in meeting the MDG target. This binary classification of water
supply and sanitation masks a gradient of ascending service levels that bring differing levels
of health and other benefits. More recently, the WASH sector has moved to a service ladder
approach that better describes water supply and sanitation access as a continuum of ascending
levels assumed to bring ascending benefits. The new Sustainable Development Goal (SDG) to
“ensure access to water supply and sanitation for all” by 2030 goes beyond unimproved or
improved designations to call for safely managed water supply and sanitation services.
To describe the risk posed by inadequate water supply and sanitation access to different groups,
it is important to consider multiple service level or exposure scenarios that distinguish between,
for example, improved sanitation and a sewer connection, and allow for different relative risks
of a given health outcome for each exposure level. Many systematic reviews pool different water,
sanitation, and hygiene interventions to arrive at a single relative risk estimate for all interventions
within a given category (water, sanitation, and hygiene), against a single counterfactual of no
intervention, failing to account for differences in service level and the control.
Two previous efforts to assign relative risk (RR) to various WASH exposure scenarios applied
literature-based estimates to an ascending level of single and then multiple WASH services,
but distinguished only between one or two levels of water supply and sanitation service. For
the WASH PRM, we will adopt the exposure scenarios and accompanying RR estimates
proposed in a recent burden of disease analysis led by the World Health Organization (WHO).
These RRs are determined using a meta-analysis based on a systematic review of various
WASH interventions corresponding to exposure scenarios, or service levels.
We assign exposure scenarios based on the coverage of water supply and sanitation service
levels using data from 2012 DHS (see figure J.1 for survey sites). We define service levels with
a desire to align where possible with the World Bank Access Plus framework. We use three
service levels for both water supply and sanitation that can be combined to describe exposure
scenarios with varying degrees of diarrheal disease risk.
Water
We exclude point of use water treatment scenarios due to the challenges of estimating adequate
compliance and the questionable reliability of the RR estimates (36). We use three exposure
scenarios from the DHS to estimate water source coverage: (a) unimproved water; (b) off-plot or
community-improved water source; and (c) on-plot improved (including piped) water source. Water
sources were grouped into scenarios using DHS household-level data and JMP MDG water ladder
definitions. Water source coverage was then estimated at the cluster (community) level using all
households, then combined with the child-level data and used to calculate the exposure index.
Sanitation
We use all three exposure scenarios for sanitation proposed by Wolf et al. unimproved
sanitation (including open defecation), improved no sewer (on-site), and sewer connection
(reticulated, off-site). We define each scenario using the classification of toilet type and
reported household sharing from DHS household-level data. Household sanitation access for
each child was combined with child-level data to calculate the exposure index.
We derived sanitation definitions that adhere to the JMP MDG sanitation ladder. Category A
includes open defecation and unimproved; any shared improved toilet or latrine; and pour or
flush toilets that flush to “somewhere else.” Category B includes unshared improved toilets or
latrines and pour or flush toilets that flush to “don’t know where.” Category C includes unshared
pour or flush toilets connected to a piped sewer.
170 Maintaining the Momentum while Addressing Service Quality and Equity
Table J.1: Exposure Risk Model Parameters
7.1 Input Value Description Reference
Water access relative risk 2011 DHS Household File 2011 DHS ET
A. Unimproved 1.00 “Dug well: unprotected well,” “water from spring: HV201
unprotected spring,” “tanker truck,” “cart with small
tank,” “surface water (river, dam, lake, pond, stream,
canal, irrigation channel),” “bottled water”
B. Off-plot improved 0.89 “Piped water to neighbor,” “public tap/standpipe,” “tube HV201
well or borehole” “dug well: protected well,” “water from
spring: protected spring” and “rainwater”
C. On-plot improved 0.77 “Piped into dwelling” or “piped to yard/plot,” and “on HV201,
premises” improved water source HV235
Sanitation access relative risk 2011 DHS Household File 2011 DHS ET
A. No, unimproved and 1.00 “flush or pour flush toilet: flush to somewhere else,” “pit HV205
shared latrine: without slab/open pit,” “bucket toilet,” “hanging
toilet/hanging latrine,” “no facility/bush/field”
B. Improved and unshared 0.84 “Flush or pour flush toilet: flush to septic tank/pit HV205
(excluding sewered house latrine,” “flush or pour flush: don’t know where,” “pit
connection) latrine: VIP/with slab,” “composting toilet”
C. Sewered house 0.31 “Flush or pour flush toilet flush to piped sewer system” HV205,
connection HV225
Note: Reference refers to a variable in the DHS table (e.g., HV201).
Exposure Index
We calculated scores for the exposure index individually for each child based on the
combined relative risks of each water supply and sanitation access scenario (equation J.1;
table J.2), and then these values are averaged by cluster using survey weights included in
DHS datasets. The value for each child is based on the household’s access to water supply
and sanitation facilities. After calculating the exposure index, we rescaled it, then adjusted
it to the excess exposure risk due to inadequate WASH by subtracting 1.00 from the relative
risk value.
(J.1) Exposure index:
ExpIndexi = SanRR·WatRR
Other Exposure Risk Factors
We present DHS data to characterize disparities in other hygiene factors related to diarrheal
disease (table J.3). Our exposure index does not include these other exposure-related hygiene
factors because while these are important for exposure, their contribution to exposure risk has
not been characterized through rigorous studies. However, this does not undermine how
important they are for limiting child exposure to diarrheal disease.
Improved hand washing and safe water treatment are defined using household-level DHS
data (table J.3). A household has improved hand washing facilities if it meets three criteria
present in the household-level data in the DHS: (a) having a designated place for hand
Maintaining the Momentum while Addressing Service Quality and Equity 171
Table J.2: Exposure Scenarios and Assigned Relative Risk from Literature Estimates
Combined
Scenario Water Relative risk Sanitation Relative risk relative risks
1 No improved water access, no A 1.00 A 1.00 1.00
improved sanitation access
2 Improved off-plot water access, B 0.89 A 1.00 0.89
no improved sanitation access
3 No improved water access, A 1.00 B 0.84 0.84
improved sanitation access
4 Improved off-plot water access, B 0.89 B 0.84 0.75
improved sanitation access
5 Improved on premises, improved C 0.77 B 0.84 0.65
sanitation access
6 Improved on premises, sewered C 0.77 C 0.31 0.24
sanitation
Notes: Relative risk figures from Wolf et al., 24.
Table J.3: Definitions of Other Exposure Risk Factors
Input Description Reference
Hand washing 2011 DHS Household File 2011 DHS ET
Improved Designated place for hand washing, water with soap, mud, or ash HV230a-b, HV232a-b
present
Unimproved Absence of either place, water, or soap/ash/mud HV230a-b, HV232a-b
Water treatment 2011 DHS Household File 2011 DHS ET
Safe “Boil,” “bleach/chlorine,” “solar disinfectant,” “water filter” HV237a-b, d-e
Unsafe “Strain through cloth,” “let it stand,” “other,” “don’t know” HV237c, f, x, z
Child stool disposal 2011 DHS Child File 2011 DHS ET
Improved Safe disposal into improved toilet or latrine (category B or C) V465 and V116
Safe “Child used latrine/toilet” or “put/rinsed in latrine or toilet” V465
Unsafe “Put/rinsed into drain or ditch,” “thrown in garbage,” “buried,” V465
“left in the open,” “other”
Population density GPW 2015 population / sq. kilometer adjusted with UN World GPW
Population Prospects
Population density DHS cluster improved sanitation coverage (category B or C) and HV205 and GPW
without sanitation GPW 2015 estimates
172 Maintaining the Momentum while Addressing Service Quality and Equity
washing that is stocked with (b) water and (c) soap, mud, or ash. Improved or safe water
treatment is defined by treating household water with an effective method for decontaminating
drinking water. Safe or improved child stool disposal is defined using the child-level DHS
data. Improved child stool disposal is when the respondent reports that the child either
directly uses an improved toilet facility or child stool is rinsed or disposed of into an improved
toilet facility (table J.3).
Population density estimates from the Gridded Population of the World (GPW) (37) were
used to assess the effects of community-level sanitation. These provide 1 square kilometer
resolution estimates of population density. We use GPW estimates that have been adjusted
using UN World Population Prospects. We overlaid DHS cluster locations on GPW population
density raster maps and extracted density estimates for each cluster. We also calculated
“population density without sanitation” as a proxy measure for the relative amount of
human waste potentially being released into the environment. We used the product of
improved sanitation coverage and population density as a measure of community-level
contamination. To calculate this variable, we combined population density cluster estimates
with cluster improved sanitation (categories B and C, table J.1) coverage to describe the
co-distribution of individual child and community sanitation risk (table J.3).
Defining Susceptibility Factors
The model includes risk factors related to susceptibility of diarrheal disease and mortality. These
include susceptibility-related micronutrients (vitamin A) to effective treatment (e.g., oral rehydration
treatment [ORT]) and undernutrition assessed by child weight-for-age (WFA) (table J.4).
Undernutrition. For undernutrition, we use relative risks (RRs) from Caulfield et al. (2003) in
which they estimate the RR of cause-specific mortality (including diarrhea) for different
levels of stunting (low height-for-age), wasting (low weight-for-height) and underweight (WFA).
We estimate RRs based on WFA z-scores recorded for under-five children in the child-level
Table J.4: Model Parameters for the Susceptibility Index
Input Relative risk Description Reference
Child underweight
Normal — WFA z-score > −1 standard deviations (SD) from the mean (38)
Mild risk 2.32 WFA z-score −1 to −2 SD from the mean (38)
Moderate risk 5.39 WFA z-score −2 to −3 SD from the mean (38)
High risk 12.50 WFA z-score < −3 SD from the mean (38)
Oral rehydration treatment (ORT)
Does not receive ORT (39)
Receives ORT 0.07 Protective, reduces risk of mortality by 93% (39)
Vitamin A dose
Received vitamin A — (40)
dose
Diarrheal mortality 0.72 Protective, reduces risk of mortality by 28% (40)
risk reduction from
receiving ORT
Note: ORT = oral rehydration therapy; WFA = weight-for-age.
Maintaining the Momentum while Addressing Service Quality and Equity 173
DHS data (table J.4). RRs are assigned to different levels of WFA based on standard
deviations (SDs) below the global mean of the z-score distribution (−1 to −2 SD, −2 to −3 SD,
and less than −3 SD) compared to normal (greater than −1 SD) Caulfield et al. For the
diarrheal risk model, we use the estimates for low WFA on diarrheal mortality as a likely
measure of long- and short-term undernutrition effects. We use reported RRs for each level
to estimate a piece-wise linear risk function that provides a continuous estimate of excess
risk as WFA z-scores decline.
ORT. There is substantial evidence of the effect of ORT on the severity and duration of
diarrhea. Based on 157 studies, Munos et al. (2010) estimates a 93 percent reduction in
diarrhea mortality with ORT use (prepackaged or home remedy). We combine this estimate
with an estimated probability of receiving ORT, calculated from child-level DHS data (table J.4).
ORT data are available only for children who have had a diarrheal episode in the previous two
weeks. However, if analyses were restricted to these observations, the coverage would be
very sparse and likely bias or underestimate the occurrence of diarrhea. Rather than including
whether a child received ORT for a recent diarrheal episode (during the last two weeks), we
estimate the propensity for receiving ORT given household wealth quintile, maternal
education, region, setting, and child’s age. Values for children without a recent episode are
imputed using a logistic regression model built on data from children who did have an
episode. Imputing values for all children results in a more widespread estimate of the
likelihood of receiving ORT.
Vitamin A. Imdad et al. (2011) examine the effect of vitamin A supplementation
on diarrhea mortality, as well as outcomes related to pneumonia and measles. Based
on 12 studies with data on diarrhea specific mortality, they estimate a pooled effect of
~30 percent reduction due to vitamin A supplementation (RR=0.70; CI: 0.58–0.86)
among children 6–59 months of age (40). We incorporate this estimate in the
susceptibility estimates using child-level DHS data on whether or not the child received
a vitamin A dose.
Susceptibility Index
We calculate the scores for the susceptibility index individually for each child based on the
combined relative risks of each of the three susceptibility factors (table J.5). The susceptibility
index (SusIndexi) is designed to be proportional to the excess risk associated with all of the
factors (J.1).
(J.1) Susceptibility index:
SSusIndexi = ∏ ∑ RR
k
j ,k RiskFactori, j ,k
i, j
Where RRj,k is the relative risk associated with the j th level of risk factor k. RiskFactori,j,k is the
level of that risk factor for individual i. For vitamin A supplementation, there are only two levels
(yes or no) and RiskFactori,j,k serves as a dummy variable. For the other risk factors, the levels
are continuous. Susceptibility values are estimated for each child subpopulation using
appropriate survey weights included in DHS datasets.
Combined Risk Index
Susceptibility (SusIndexi)and exposure risk (ExpIndexi) are combined into the overall risk index
(RiskIndexi), which is simply the product of the two indexes (equation J.3). We calculated risk
index scores individually for each child under five years of age and then aggregated into
subpopulation estimates.
174 Maintaining the Momentum while Addressing Service Quality and Equity
Table J.5: Summary of Susceptibility Index Calculation
7.2 Risk factor Relative risk description Data source Calculation
Underweight Having a low WFA significantly WFA is collected and Relative risk for different
increases a child’s risk of dying reported in the DHS. categories are linearized to
from diarrheal disease. WFA is create an individual value for
assessed on how far a child is the child (from 1 to 12.5).
above or below the international
standard. The more standard
deviations below the average, the
greater the risk.
Oral rehydration Receiving timely rehydration can DHS has information on Based on the probability of
greatly reduce the mortality from whether children receive getting ORT and the relative
diarrheal disease (by 93%). The ORT (PrORT) following risk, ranging from 0.07 to 1.0.
relative risk of diarrheal mortality diarrhea for some 1 - (PrORT x (1 - RR_ORT)).
for ORT is 0.07 (RR_ORT). children. We estimate the
probability of receiving
ORT for all children using
data from those that have
it (adjusting for age, sex,
wealth and region).
Vitamin A Receiving vitamin A DHS has information Based on whether they
supplementation has been shown on whether children received vitamin A and its
to reduce the risk of diarrheal have received vitamin A protective effect. 1 - (vit_A x
mortality in children. The relative supplementation (vit_A). (1 - RR_vitA)).
risk is 0.72 (a 28% reduction)
(RR_vitA).
Note: ORT = oral rehydration therapy; WFA = weight-for-age.
(J.2) Risk index:
RiskIndexi = ExpIndexi·SusIndexi
Data Analyses
Data on the distribution of diarrheal susceptibility and exposure risk factors come from
available DHS surveys.1 Demographic and health surveys are implemented countrywide in
middle- to low-income countries and survey a wide range of health and socioeconomic
characteristics. Surveys are released with data on geographic locations, and include both
household- and individual-level datasets. Households are selected using stratified sampling
methods that require accounting for complex survey design.
Density plots. These graphs show the distributions of variables of interest using probability
densities. The area under each curve is equal to one, and represents the relative density of
probability that a member of the wealth quintile has the corresponding value along the x-axis.
Concentration curves. These graphs show the distributions of outcomes across a ranked
cumulative fraction of the population—in this study, socioeconomic status. The x-axis shows
the cumulative wealth fraction from the poorest percentiles on the left, to the entire population
Maintaining the Momentum while Addressing Service Quality and Equity 175
on right and shows the fraction of a given outcome (y-axis) associated with the population up
to each cumulative wealth level. This is plotted against a 45-degree line of equity, in which the
poorest 40 percent have 40 percent of outcomes, extending all the way up the wealth
continuum. While they do not show actual coverage values for risk factors, they do highlight
where disparities in risk factor coverage are most prominent.
Scatterplot matrixes. The lower half of these figures show a series of pairwise x-y scatter
plots showing the co-distribution of different WASH risk factors, population density, and
indexes for both urban and rural children. The upper half shows two-dimensional contour
plots of the pairwise co-distributions of variables and indexes from the WASH PRM. Many
of the individual risk factors are categorical and therefore not easily represented. In these
cases, scatters show the cluster-level proportions and means, rather than individual
values.
Poverty and economic status. Asset-based wealth and consumption metrics both reflect
urban and rural poverty differently. The differences in both lifestyle and access to assets
between urban and rural populations can be masked when wealth quintiles are calculated
at a national level. Asset-based wealth metrics rely on individual goods (e.g., bicycles) or
construction materials (e.g., thatch roofs), which have very different meaning and value in
rural compared to urban settings. National quintiles can obscure the condition of the urban
poor population, which is grouped into the third or fourth national quintiles. While their
assets may group them into higher wealth quintiles, when compared to rural populations,
they may not experience a higher standard of living equal to their higher ranking. Asset-
based indexes (as are used in DHS to determine household wealth) result in rural
households being grouped into the middle and lower national quintiles, while urban
households are grouped into the middle and upper quintiles. Failing to account for urban
and rural differences can obscure important underlying patterns between wealth and
health. We computed national, urban, and rural wealth quintiles, and ranked urban and
rural households separately by wealth quintiles. The categorization of quintiles for urban
and rural populations is based on the distribution of the asset scores within the urban and
rural populations, respectively, rather than the national distribution, thus they must not be
interpreted as equivalent.
Geospatial analyses. One of the key objectives of the WASH PRM is to show the geographic
distribution and co-distribution of risk factors and impact. This includes mapping individual risk
factors and cumulative measures (e.g., exposure, susceptibility, and risk indexes). Our maps
identify regions that experience high levels of exposure, susceptibility, diarrheal risk, and other
important outcomes. We show these outcomes at national and regional scales, and for
different economic levels (bottom 40 percent [B40] and top 60 percent [T60]). Regional- and
cluster-level average values are calculated using the appropriate DHS survey weights.
We interpolated exposure, susceptibility, and risk indexes for the national-level maps, as well as
for the B40 and T60. We calculated cluster-level averages of the three indexes. Using ARCGIS
10.2.2, we utilized empirical Bayesian kriging to interpolate a high resolution (5 square kilometer)
risk surface. Standard kriging approaches use a regression-type linear model to predict values
at unmeasured locations on a surface using an average of values near the point in question.
Empirical Bayesian kriging uses the underlying sample distribution to inform the model’s priors
and covariance functions, whereas most other kriging measures assume underlying Gaussian
distribution, which is often not the case in datasets. These high-resolution maps provide an
initial rapid assessment of important trends in diarrheal disease-related factors.
DALY burden of inadequate WASH. The WASH PRM estimates the distribution of child diarrhea
and enteric infections due to inadequate WASH. The estimates also account for variability in
child susceptibility through undernutrition or lack of medical care. These have been expressed
as measures of the risk index. However, in this section these estimates are translated into the
more commonly used measures of disability-adjusted life years (DALYs), developed and used
by the Global Burden of Disease project (GBD).
176 Maintaining the Momentum while Addressing Service Quality and Equity
DALYs are a common health metric that combines both the years of life lost (YLL) due to a
particular cause or risk factor as well as the years lived with disability. For diarrhea and enteric
disease among children under five years of age, the vast majority (approximately 90 percent)
of the DALY burden is due YLL due to premature mortality. A single DALY can be considered as
one year of healthy life lost. As a summary measure that can be calculated across diverse
causes or risk factors, including those that might cause death (such as road traffic accidents)
or those that do not cause death but may cause chronic disability (e.g., back pain or trichiasis).
As such, DALYs permit comparison between diverse health conditions and provide a useful
summary statistic of disease burden for a given population.
Here, we use DALYs to provide a summary estimate for the distribution of the enteric disease
burden attributable to inadequate WASH by subpopulation groups. For this exercise, we use
DALY estimates from the 2013 GBD, which are available online.
Health burden causes are broken down in the GBD into different categories of communicable
and noncommunicable diseases. Here we use the estimates for diarrheal disease (category
A.2.1 from the GBD data portal website; and intestinal infectious diseases (category A.2.2
from GBD data portal website). It is important to point out that this captures the burden of
short-term morbidity and mortality, but does not account for any potential of enteric infections
on undernutrition or long-term consequences.
We start by translating the WASH PRM risk index into a DALY burden rate (DALYs per 100,000).
The WASH risk index represents the relative excess risk associated with inadequate WASH, and
the first step is to convert it into a measure of overall risk of diarrhea and enteric infections
(and not just the excess due to poor WASH). This involves recalculating an overall exposure
index that is not adjusted for the excess risk. This is done by using the original RR numbers
from the literature and not subtracting 1 from the RR to create an excess RR. This has the
effect of turning the exposure index (risk index) into a measure of the overall enteric disease
risk, rather than just the portion attributable to inadequate WASH.
The second step is to convert this revised enteric risk index into a DALY equivalent. We make
the assumption that the relative distribution of the risk index is an appropriate estimate of the
distribution of the DALY burden. Using the GBD estimate as our national burden envelope, we
create a risk-burden multiplier using equation (J.4):
(J.3) Risk-burden multiplier:
NatEnterDALY
RBMult =
EntRiskIndi
This establishes a ratio between risk index and DALY burden that maintains the national GBD
burden estimate. We then use the multiplier to estimate an individual-level expected DALY
burden for each child. These values can then the aggregated by geographic and economic
subpopulations. See equations (J.5) and (J.6).
(J.4) Total enteric DALY burden:
EntDALYi = RBMult·EntRiskIndexi
(J.6) Inadequate WASH-attributable enteric DALY burden:
WASHDALYi = RBMult·WASHRiskIndi
EntDALYi represents the burden for individual i from diarrheal and enteric infections based on
the individual exposure and susceptibility variables. The sum of ENTDALYi over the population
is the same as the GBD diarrheal and enteric infection burden. WASHDALYi represents the
Maintaining the Momentum while Addressing Service Quality and Equity 177
portion of this burden associated with inadequate WASH service levels. As with the GBD
burden, these individual estimates are rates expressed as DALYs per 100,000 children.
These burden estimates for individual children are then aggregated to subpopulation levels
(e.g., region, urban or rural residence, and wealth quintile) using survey statistics as above.
The appropriately weighted means for the subpopulations represent the expected DALYs per
100,000 children per year. For these measures, we focus on the distribution of the total enteric
burden and burden associated with inadequate WASH.
Note
1. All statistical estimates presented and imputations were calculated and combined into
the WASH PRM using complex survey design in STATA 14 (StatCorp LP , College Station,
TX). All data representations in plots were made in R statistical software using the
ggplot2 package, authored by Hadley Wickham, and associated extensions (41). All maps
were rendered in ArcGIS 10.22 (ESRI, Redlands, CA) using model outputs.
References
Caulfield, L. E., M. de Onis, M. Blössner, and R. E. Black. 2003. “Undernutrition as an Underlying
Cause of Child Deaths Associated with Diarrhea, Pneumonia, Malaria, and Measles.”
American Journal of Clinical Nutrition 80 (1): 193–8.
Imdad, A., M. Y. Yakoob, C. Sudfeld, B. A. Haider, R. E. Black, and Z. A. Bhutta. 2011. “Impact
of Vitamin A Supplementation on Infant and Childhood Mortality.” BMC Public Health
11 (3): S20.
Munos, M. K., C. L. F. Walker, and R. E. Black. 2010. “The Effect of Oral Rehydration Solution
and Recommended Home Fluids on Diarrhoea Mortality.” International Journal of
Epidemiology 39 (1): i75–i87.
178 Maintaining the Momentum while Addressing Service Quality and Equity
Appendix K
WASH and Health: Distribution
of Exposure and Susceptibility
In urban and rural settings, exposure variables related to water supply, sanitation and hygiene
(WASH) are strongly associated with economic status with a large disparity between the urban
rich and poor. The richest households in Ethiopia have up to twice the access to improved
water sources than the poorest, and are up to 20 percent more likely to report safe water
treatment. The poorest 40 percent of households have an inequitable cumulative share
(20 percent or less) of improved child stool disposal, improved sanitation, and safe water. In
urban and rural settings, WASH-related exposure variables are strongly associated with
economic status with a larger disparity between the urban rich and poor populations.
Panels a–c of map K.1 show a scale spatial resolution map (at 5 square kilometers) of the
exposure index value distribution across children under five nationally and by economic groups.
Southern and central Ethiopia have the highest exposure indices across all three maps (>2.90).
Central Ethiopia has the lowest exposure risk, which ranges from less than 2.70 among the
T60 to between 2.70 and 2.90 among the poorest 40 percent of households. While panels a–c
of map K.1 are based on the variables included in the exposure index, there are substantial
disparities in other exposure-related variables not included in the index (e.g., hand washing,
water treatment, and safe disposal of child fecal matter). Including these variables would result
in greater disparities and heterogeneity.
WASH exposure variables are associated with wealth and with each other. That is, poor
households are more likely to have multiple WASH conditions that increase their exposures to
enteric pathogens. Since poor households are often within poor communities, they are also
more likely to be surrounded by poor sanitation conditions. For some risk factors, patterns
differ greatly between urban and rural settings. In Ethiopia, higher proportions of urban
households have access to improved water supply and sanitation than rural households; as a
result, children in urban communities have a lower susceptibility than children from rural
communities.
Panels a–c of map K.2 are susceptibility index maps that have common features with the agro-
ecological belts of Ethiopia. The country’s agro-ecological belts differ in rainfall, growing season,
Map K.1: Exposure Index Values in Ethiopia for Populations of Children under
Five, 2011
a. Overall b. B40 c. T60
Exposure index
< 2.70
2.70–2.80
2.80–2.90
2.90–3.00
> 3.00
Source: DHS 2011.
Note: Maps are at 5 km2 resolution. B40 = below 40 percent of wealth index; T60 = above 60 percent of wealth index.
Maintaining the Momentum while Addressing Service Quality and Equity 179
Map K.2: Susceptibility Index Values in Ethiopia for Populations of Children under
Five, 2011
a. Overall b. B40 c. T60
Susceptibility
index
< 1.3
1.30–1.80
1.80–2.30
2.30–2.80
2.80–3.30
> 3.30
Source: DHS 2011.
Note: Maps are at 5 km2 resolution. B40 = below 40 percent of wealth index; T60 = above 60 percent of wealth index.
soils, and elevation. These factors may affect food availability, economic status, livelihood, and
other factors. Areas with the highest child susceptibility index values are concentrated in
the southeast and northeast, while the children with the lowest susceptibility index values are
concentrated in the west in the overall map (panel a) and the T60 population (panel c). For the
B40 children population, there are larger areas of the higher susceptibility index values (>2.30)
in the north and south, and to a lesser extent in the center. In the T60 children, there is a large
area with relatively higher (2.30–2.80) susceptibility index values in southeastern Ethiopia,
and on the northeastern edge.
Child susceptibility variables are associated with wealth and each other. That is, children in
poor households are more likely to be underweight and have a lower probability of receiving
ORT. In both urban and rural settings, children in poorer households are more vulnerable to the
risks posed by poor WASH due to low nutrition and access to key health interventions (ORT and
vitamin A). The urban rich have the lowest concentration of underweight children, in comparison
to the urban poor and the rural rich and poor. Children in poor households are up to 2.7 times
more likely to be underweight and five times more likely to be severely underweight. The B40
has more than 45 percent of the cumulative share of being underweight in comparison to richer
children. However, the upper wealth quintiles also have an inequitably higher share of
underweight children.
Children in the bottom 20 percent (B20) rural households are 1.3 times more likely to be
underweight and 1.9 times more likely to be severely underweight than their B20 urban
counterparts. Children in urban households have two to three times the probability of receiving
ORT, as compared to rural children. There was not a large disparity in regards to preventative
(vitamin A) services, but there was for curative (ORT treatment) services between urban and
rural populations. Children in urban households have two to three times the probability of
receiving ORT treatment, as compared to rural children.
In general, susceptibility is negatively associated with wealth; the poorest and most vulnerable
households are also more likely to live in communities with higher exposure risk, as set out in
figure K.2, panels a–c. Children in poor households have higher exposure and susceptibility
than children in rich households, with the B40 having approximately 50 percent of the
cumulative share of the susceptibility and risk. Nationally, poorer children (B20 and B40) have
approximately 1.5 to 3.6 times the risk than richer children (T20 and T40), and this pattern
emerges at the community level. In general, children in rural populations have a higher risk
than those in urban populations; poor rural children (B20 and B40) have 1.6 to 1.7 higher risk
index values than poor (B20 and B40) urban children. The overall risk is concentrated among
the riskiest children, even when setting is controlled for. There are likely other previously
uncovered factors contributing to this pattern.
180 Maintaining the Momentum while Addressing Service Quality and Equity
Figure K.1: Distribution of Susceptibility Factors by Economic Level for Children under Five in Ethiopia, 2011
a. Mod. & sev. underweight b. Severe underweight c. Probability of ORT d. Vitamin A coverage
60
40
National
Percent
20
0
60
40
Percent
Rural
20
0
60
40
Percent
Urban
20
0
Po t
M r
e
Ri r
t
Po t
M r
e
Ri r
t
Po t
M r
e
Ri r
t
Po t
M r
e
Ri r
t
es
es
es
es
es
es
es
es
e
e
e
e
e
e
e
e
dl
dl
dl
dl
or
ch
or
ch
or
ch
or
ch
or
ch
or
ch
or
ch
or
ch
id
id
id
id
Ri
Ri
Ri
Ri
Po
Po
Po
Po
Wealth quintile Wealth quintile Wealth quintile Wealth quintile
Source: DHS 2011.
Note: Children who are >2 standard deviations less than the global mean weight-for-age (WFA) for their age are considered underweight. Children who
are >3 standard deviations less than the average WFA are considered severely underweight. ORT = oral rehydration therapy.
DALY Burden of Inadequate WASH in Ethiopia
In Ethiopia, the national enteric burden associated with inadequate WASH is 11,135 DALYs /
100,000 children per year, which is approximately 75 percent of the Global Burden of Disease
(GBD) enteric burden estimated for the country. Panels a–c of figure K.2 show the calculated
total enteric burden rate divided into the fraction associated with having inadequate WASH and
burden rates unrelated to WASH by wealth quintile for national, rural, and urban populations of
children under five. It is important to clarify aspects of what is meant by associated and unrelated
to inadequate WASH. First, some enteric infections are not preventable with improved WASH.
Maintaining the Momentum while Addressing Service Quality and Equity 181
Figure K.2: WASH-Related DALY Enteric Burden for Children under Five in
Ethiopia, 2011
a. National b. Rural c. Urban
20,000
DALYs / 100,000 children
15,000
10,000
5,000
0
e
e
e
er
er
er
t
er
t
er
t
t
er
t
t
es
es
es
es
es
es
dl
dl
dl
ch
ch
or
or
or
ch
id
id
id
or
or
or
ch
ch
ch
Po
Po
Po
Ri
Ri
Ri
M
M
M
Po
Po
Po
Ri
Ri
Ri
Wealth quintile Wealth quintile Wealth quintile
Total enteric burden Inadequate WASH Unrelated to WASH
Source: DHS 2011.
Note: DALY = disability-adjusted life year; WASH = water supply, sanitation, and hygiene.
For example, almost all children under five experience rotavirus infection, but improvements in
WASH do not prevent the infection. These are unrelated to inadequate WASH in that they would
not be prevented with improvements. Second, the DALY burden associated with inadequate
WASH here accounts for both the level exposure due to inadequate WASH and children
susceptibility due to other factors. That is, the DALY burden associated with inadequate in a
particular subpopulation reflects both exposure and susceptibility in that subpopulation. Child
susceptibility (e.g., undernutrition and likelihood of ORT) affects both the WASH associated and
the unrelated burden.
The health burden of inadequate WASH is disproportionately borne by poorer children and
those in vulnerable geographic areas. Nationally, the WASH enteric burden for the poorest
quintile is about three times greater than the enteric burden for the richest quintile. WASH-
related enteric burden is lower within urban than in rural populations, but the disparities in both
are equivalent. Burden for the poorest rural communities is 1.8 as high as the burden for the
richest, and in urban communities the burden is 5.4 times higher for the richest than the
poorest. The highest burden associated with inadequate WASH among the poor households is
due to a conjuncture of vulnerabilities. They are less likely to have good WASH services, and
those who do not are also more likely to be undernourished and without access to care. Child
health vulnerabilities magnify the effects of inadequate WASH among poor populations.
It should be noted that this analysis, like the underlying GBD estimates, accounts for the
impact of inadequate WASH on acute morbidity and mortality from enteric infections. It does
not account for the effect these infections may have on undernutrition and its chronic sequelae.
The findings in this report on the relative quality of WASH service in Ethiopia suggest that the
estimates of disease burden are the lower bound and actual WASH-related disease burden is
likely to be higher.
182 Maintaining the Momentum while Addressing Service Quality and Equity
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