68055
ESTIMATING RELATIVE BENEFITS OF DIFFERING
STRATEGIES FOR MANAGEMENT OF WASTEWATER IN
LOWER EGYPT USING QUANTITATIVE MICROBIAL RISK
ANALYSIS (QMRA)
World Bank Water Partnership Program
Final Report
February 2012
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ESTIMATING RELATIVE BENEFITS OF DIFFERING
STRATEGIES FOR MANAGEMENT OF WASTEWATER IN
LOWER EGYPT USING QUANTITATIVE MICROBIAL RISK
ANALYSIS (QMRA)
A report on research carried out by the School of Civil Engineering, University of
Leeds, the World Bank and the Holding Company for Water and Wastewater,
Government of Egypt with support from the National Research Centre, Cairo, Egypt
World Bank Water Partnership Program
Final Report
February 2012
© 2012 International Bank for Reconstruction and Development / International Development Association or
The World Bank
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Washington DC 20433
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Internet: www.worldbank.org
This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and
conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive
Directors or the governments they represent.
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World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.
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Acknowledgements
This study was carried out with financial support from the World Bank Water Partnership Program.
The principal investigator was Barbara Evans, University of Leeds, and the Task Manager was Param
Iyer, World Bank.
It presents a practical example of how to operationalize the 2006 WHO Guidelines on the Safe Use of
Wastewater, Excreta and Greywater and the recent World Bank Policy Research Paper 5412
Improving Wastewater Use in Agriculture; An Emerging Priority.
The Holding Company for Water and Wastewater in Egypt provided staff and access to facilities as
well as providing valuable inputs at the review stage. In particular we would like to thank Engineer
Mamdouh Raslan, Deputy Chairman, and Engineer Mounir Hosny, Director of the Project
Implementation Unit of the Integrated Sanitation and Sewerage Project (ISSIP), for their valuable
guidance and support. Many other staff provided invaluable assistance but in particular we would
like to acknowledge the contribution of colleagues at the Kafr El Sheikh Water Company for their
assistance in conducting field studies at Sidi Salem and El Moufty and providing extremely valuable
additional field data. Particular mention should be made of Anwar Halawa, Eatadal El-Argway and
Atef Fergany.
We would also like to thank colleagues at the National Research Council, in particular Prof Dr Fatima
El-Gohary and Prof.Dr. Mohamed Mohamed Kamel, for their assistance in setting up and carrying
out the field work for this study.
Ms Heba Yaken at the World Bank office in Cairo provided extremely useful inputs and guidance and
Mr. Philippe Reymond of the Swiss Technical Institute at EAWAG/SANDEC and based in Cairo
provided invaluable support and insights and proved the value of collaboration. Mr. Ahmed Atta
acted as the coordinator and made a significant technical contribution.
We would also like to thank our reviewers Ms. Suzanne Scheierling, Ms Caroline van den Berg , Mr
Lee Travers and Ms Soma Ghosh Moulik at the World Bank and Dr Andy Sleigh at the University of
Leeds for their invaluable insights and contributions. However all errors remain our own.
Barbara Evans and Param Iyer
February 2012
The World Bank Water Partnership Program
The Water Partnership Program (WPP) is a multi-donor trust fund established in 2009 and
administered by the World Bank’s Water Unit in the Sustainable Development Network. The WPP
consolidates two previous programs, the Bank-Netherlands Water Program in Supply and Sanitation
(BNWP) and the Bank-Netherlands Water Partnership Program in Water Resource (BNWPP) into an
improved realignment and restructuring of these programs. The Program is funded by the
governments of the Netherlands, the United Kingdom, and Denmark, for a total contribution of
$23.7 million.
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Foreword
The Holding Company for Water and Wastewater through its ACs is responsible for the operation
and maintenance of the existing facilities to deliver safe water supplies and the management of
domestic and industrial wastewater in Egypt. The management of wastewater in particular presents
a growing challenge. The country is highly dependent on the water of the Nile for agricultural
production. The managed re-use of agricultural runoff from the agricultural drainage network is
becoming increasingly important as an input to crop production particularly in the delta region. In
this context, the commitment to deliver modern networked sanitation to all householders in the
region presents particular challenges. Domestic wastewater contains valuable nutrients which
could be useful in crop production but also contains potentially harmful disease-causing pathogens.
It is the task of HCWW to identify, develop and manage appropriate sanitation facilities, including
wastewater collection networks and treatment plants, so as to ensure that domestic wastewater is
treated and disposed of in ways which ensure protection of health. Recognising the potential for
reuse of diluted effluents in agricultural drains HCWW are continually looking for ways to optimise
the planning and design of wastewater management systems. Modern statistical tools enable the
assessment of relative health risks when effluent from treatment plants is discharged into the
agricultural drainage network in locations where reuse could have value in the agricultural system.
Engineer Mamdouh Raslan, Deputy Chairman
Holding Company for Water and Wastewater
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Table of Contents
List of Tables .................................................................................................................................... vi
List of Figures ................................................................................................................................... vi
List of Abbreviations .........................................................................................................................vii
1. INTRODUCTION ......................................................................................................................... 1
2. THE STUDY ................................................................................................................................. 1
Wastewater Reuse and Health....................................................................................................... 1
Aims and Objectives ...................................................................................................................... 2
3. THE CONTEXT ............................................................................................................................ 3
Wastewater Reuse in Egypt ........................................................................................................... 3
Sanitation and Wastewater Treatment .......................................................................................... 3
4. THE APPROACH.......................................................................................................................... 4
Focus on Health Risks .................................................................................................................... 4
Risk Management Strategies ......................................................................................................... 5
5. THE MODEL ............................................................................................................................... 6
Typical Drainage Basin ................................................................................................................... 6
Interventions ................................................................................................................................. 7
Field Test Sites ............................................................................................................................... 7
Calculating Health Risks from Water Quality .................................................................................. 8
6. PARAMETERS FOR USE IN THE MODEL ....................................................................................... 9
Acceptable Additional Risk to Health ............................................................................................. 9
Key Indicator Pathogens ................................................................................................................ 9
On-farm, Post-harvest and In-kitchen Measures to Reduce Health Risks ...................................... 10
Wastewater Treatment Products ................................................................................................. 10
Dilution Options .......................................................................................................................... 10
Cropping Patterns........................................................................................................................ 11
7. RESULTS................................................................................................................................... 11
Downstream Water Quality ......................................................................................................... 11
Effectiveness of Treatment .......................................................................................................... 12
Impact of Sanitation Options on Water Quality ............................................................................ 14
Cost Effectiveness ........................................................................................................................ 16
8. DISCUSSION AND CONCLUSIONS.............................................................................................. 19
Current situation ......................................................................................................................... 19
Effective sanitation options ......................................................................................................... 19
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Water and Wastewater Quality Standards ................................................................................... 21
Conclusions and Further Work ..................................................................................................... 22
References ...................................................................................................................................... 24
APPENDIX 1: QMRA ........................................................................................................................ 27
Introduction ................................................................................................................................ 27
Dose-response relationships .................................................................................................... 27
Disease-infection ratios ........................................................................................................... 27
APPENDIX 2: DATA TABLES ............................................................................................................. 29
List of Tables
Table 1: Intervention Options used in this research ........................................................................... 7
Table 2: Health protection control measures and associated pathogen reductions .......................... 10
Table 3: Incidence of Fecal Coliforms in Drains and Canals .............................................................. 11
Table 4: Model Parameters for Water and Wastewater Quality ....................................................... 13
Table 5: Parameters for treatment options ...................................................................................... 14
Table 6: Downstream water quality in receiving drain assuming chlorination .................................. 14
Table 7: Median Infection risks from consumption of wastewater-irrigated tomatoes estimated by
10,000-trial Monte Carlo Simulation* .............................................................................................. 15
Table 8: Incidence of diarrhea and DALY burden under various scenarios ....................................... 16
Table 9: Overall reduction in icidence of diarrhoeal disease and DALYs by intervention (20 years) ... 16
Table 10: Unit costs for sanitation interventions .............................................................................. 17
Table 11: Selected Water quality parameters in Law 48/1982.......................................................... 21
Table 12: Water quality parameters considered in the development of water quality indices (WQI)22
Table 13: Water Quality Data – El Moufty El Kobra .......................................................................... 29
Table 14: Water Quality Data – Sidi Salem ....................................................................................... 31
Table 15: Hourly Water Quality Data – El Moufty El Kobra ............................................................... 33
Table 16: Hourly Water Quality Data – Sidi Salem ........................................................................... 33
Table 17: Water Quality Data – Trench/Bayaras............................................................................... 35
List of Figures
Figure 1: Balancing context and additional risk .................................................................................. 2
Figure 2: Pathogen flow in the notional drainage basin ...................................................................... 5
Figure 3: Relating incidence of pathogens to health impact in downstream populations ................... 8
Figure 4: Monthly reuse of drainage water in the Nile delta during 2002/2003 (BCM) ..................... 12
Figure 5: Average observed rates of e-coli in study wastewater treatment plants* .......................... 13
Figure 6: 20-year discounted NPV for sanitation options.................................................................. 18
Figure 7: Cost effectiveness of interventions US$ per DALY avoided (log scale) ................................ 18
Figure 8: Cost effectiveness of interventions (excluding household septic tanks) US$ per DALY
avoided ........................................................................................................................................... 19
Figure 9: Cost effectiveness of waste stabilization ponds systems of varying sizes (US$ per DALY
avoided) .......................................................................................................................................... 21
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List of Abbreviations
AS Activated Sludge
BCM Billion cubic meter (m3)
CER Cost-effectiveness Ratio
DALY Disability-adjusted Life Years
HCWW Holding Company for Water and Wastewater
JMP WHO/UNICEF Joint Monitoring Program for Water and Sanitation
MPN Most Probably Number (laboratory method for counting pathogens)
NAWQAM National Water Quality and Area Management Project
NPV Net Present Value
OD Oxidation Ditch
OFT On-farm Treatment
pppy Per person per year
QMRA Quantifiable Microbial Risk Assessment
ST Septic Tank
UNDP United Nations Development Program
UNICEF United Nations Childrens Fund
WHO World Health Organization
WSP Waste Stabilization Pond
WWTP Wastewater Treatment Plant
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1. INTRODUCTION
This report, prepared in collaboration with the World Bank, supported by the Water Partnership
Program, and the University of Leeds, lays out an approach, using modern modeling techniques and
a statistical tool known as Quantifiable Microbial Risk Assessment, by which the relative
effectiveness of different wastewater management strategies can be assessed in terms of optimising
health benefits to downstream populations. The report uses a theoretical model of a typical
drainage basin, but the approach could be applied to many of the drainage basins managed by the
Holding Company for Water and Wastewater in Egypt. The conclusions of the study provide an
indication of how such methods could increasingly be used to enable the selection of cost-effective
and appropriate wastewater management strategies.
The analysis presented here, which make a realistic assessment of relative health risks using robust
statistical techniques and empirical information, has the potential to increasingly inform the debate
about effluent discharge standards and the management of wastewater and agricultural runoff for
reuse in agriculture.
2. THE STUDY
Wastewater Reuse and Health
Wastewater treatment serves two main purposes; the removal of harmful pathogens from waste
with a view to protecting health and the removal of nutrients (significant amongst which are
Nitrogen and Phosphorous) from waste to protect the environment. Different wastewater
management systems perform these two functions with different degrees of effectiveness and at
different costs. Process selection is often a matter of tradeoff between these two objectives since
few processes are very effective at both. Many modern high-energy processes focus on nutrient
removal and rely on chlorination for pathogen removal. A focus on nutrient removal however
removes or makes significantly more costly the capture of these valuable inputs for downstream
agriculture. Reuse of treated wastewater which is pathogen-free has significant potential to
increase agricultural productivity and reduce reliance on chemical fertilisers.
Decisions about wastewater management strategies are a process of balancing costs and
effectiveness across these two objectives. The removal of pathogens is a priority where
wastewater reuse is common. The transport of pathogens from human excreta back to a human
host is one of the primary routes of transmission of significant disease groups, in particular diarrheal
disease. The core assumption of this research is that the movement of pathogens from
wastewater, via irrigation both directly to farm workers and to consumers of crops, is one of the
primary transmission routes for diarrheal disease. In 2005 the UNDP Human Development Report
for Egypt stated that “[p]oor water quality affects both health and land productivity with damage
costs estimated …. to have reached LE 5.35 billion …. or 1.8% of GPD in 2003�? (UNDP, 2005).
The study makes use of the framework laid down in the WHO Guidelines for the Safe Use of
Wastewater, Excreta and Greywater – Volume 2; Wastewater Use in Agriculture published in 2006,
along with the 2010 update also published by WHO. The value of the 2006 WHO guidelines lies in
the fact that this increased health impact can be calculated in the context of downstream conditions
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including current disease burden and the likely pathways by which people will be exposed to
contaminated wastewater (see for example Figure 1).
A major advantage of the ‘relative risk’ approach taken in the 2006 WHO guidelines is that they
encourage progressive measures to reduce risk of exposure to microbial hazards in contrast to
earlier approaches which were more binomial in nature (either meeting or failing to meet rigid
standards). This approach allows for different strategies to reduce risk exposure to be assessed.
The use of normative tools such as Disability-adjusted Life-Years (DALYs) or disease incidence rates
as a measure of disease burden associated with known levels of risk further allows for a direct
comparison between different risk-reduction strategies.
Figure 1: Balancing context and additional risk
Additional
Context risk
Source: Authors illustration
For example, in Ghana, non-treatment options such as improved irrigation practices at the farm and
post-harvest handling and treatment of crops have been explored alongside more conventional
approaches to improve wastewater treatment to assess the most cost-effective strategies to reduce
diarrheal disease incidence in urban areas (Seidu & Drechsel, 2010). That study compared the
“health gains in terms of diarrheal disease reduction [with the] cost of treatment and non-treatment
interventions associated with wastewater irrigation in Ghana�? (Seidu & Drechsel, 2010)p. 263.
Aims and Objectives
This study set out to assess the relative health impacts of different wastewater management
strategies on health in the Nile delta region using an approach similar to that used in the Ghana case
study mentioned above.
The ultimate objective was to develop a framework for long-term investment planning based on
monitoring of health and productivity impacts of proposed Bank operations which could be included
in Project M&E systems. This would equip Task Teams to assess the risks and opportunities which
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arise due to the proposed shift from on-site to networked sanitation in four governorates where the
Bank has wastewater operations.
A secondary objective was to assess the extent to which existing legislation supports health risk-
based planning.
3. THE CONTEXT
Wastewater Reuse in Egypt
Egypt is highly dependent on reuse of agricultural drainage water for irrigation. In 2002/3 it was
estimated that 4.3 billion m3 (BCM) of drainage water were being used in the delta region and
Fayoum through official reuse projects, and this was set to rise to around 7.6BCM on completion of
further planned drainage projects (Mostafa, El-Gohary, & Shalby, Date Unknown). Unofficial reuse is
generally estimated to be considerably higher.
There are several water quality issues relating to agricultural reuse of drainage water.
Firstly, salinity and concentrations of naturally-occurring pollutants in irrigation water can
rise to unacceptable levels due to the effects of evaporation and consequent concentration
in residual flows.
Secondly, the biochemical characteristics of the drainage water can be adversely affected by
the inflow of unregulated domestic and industrial wastewaters and the effluent from
wastewater treatment plants.
However, from a health perspective, high concentrations of harmful pathogens are of greatest
concern. According to some observers “…the major problem regarding drainage water quality is not
salinity, but chemical and bacteriological pollution…�? (Mostafa, El-Gohary, & Shalby, Date Unknown)
p.98. This report focuses on the health implications of pathogenic contamination of agricultural
drainage water which is reused in agriculture.
Sanitation and Wastewater Treatment
The main sources of pathogenic contamination in the agricultural channels are livestock wastes from
cattle sheds and fields, industrial discharges (tanneries and dairies presenting particular challenges)
and informal discharges of human excreta from onsite sanitation systems.
By presidential decree (Presidential Decree 135/2004), all households in Egypt are guaranteed
individual connections to networked sewerage for their sanitation services. Disposal of wastewater
into irrigation channels is not officially permitted and the discharge of treated domestic wastewater
into such agricultural channels is strictly regulated (Government of Egypt, 1982). In theory
therefore, all sewerage connections should be made to wastewater treatment facilities. A major
objective of The Holding Company for Water and Wastewater (HCWW) is to increase the rate of
connection to sewerage and to develop new wastewater treatment capacity.
Progress towards this objective has been relatively slow. Between 1990 and 2008 rates of access to
improved sanitation (essentially a hygienic toilet) in the rural areas of Egypt rose from 57% to 92%
but rates of sewerage connection were around 18% in 2008 and between 2005 and 2008 progress
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appears to have virtually stagnated (WHO/UNICEF Joint Monitoring Program for Water and
Sanitation, 2010) and (WHO/UNICEF Joint Monitoring Program on Water and Sanitation, 2011).
Many rural households have onsite vaults which are emptied between two to four times per month
due to high water tables (World Bank, 2008). Most of this effluent is either used directly on the
fields or discharged into agricultural drains and canals without treatment. In Gharbeya, Kafr El
Sheikh and Beheira Governorates for example there are some 15 wastewater treatment plants
serving the larger agglomerations, but most are running well below capacity and do not serve the
majority of the population. A survey carried out in Gharbeya, Kafr El Sheikh and Beheira in 2007
reported that while 88% of households had latrines, 48% were connected to septic tanks. Thirty-
nine percent were deemed to be ‘unsanitary’ (implying that the pits or tanks were not providing
adequate storage or protection) and 12% of households had no toilet at all. Of those families with
septic tanks or cess pits, 25% of households in Beheira reported that these were emptied directly
into agricultural drains or canals, while 44% in Kafr El Sheikh reported that they were emptied into
the canal (EcoConServ, 2007).
Informal private operators provide emptying services and dispose of wastes in both irrigation
channels and drainage channels.
Thus the Nile delta has a high prevalence of poorly-managed onsite sanitation facilities, low rates of
connectivity to wastewater treatment facilities and is cris-crossed by a network of agricultural canals
and drains. None of the water companies in Lower Egypt are able to guarantee 100% collection and
treatment of domestic wastewater. Significant volumes of untreated domestic wastewater and
discharges from wastewater treatment facilities that are operating under-capacity are therefore
discharged into the agricultural drainage system and significant volumes of the resultant mixed drain
water are certainly used for irrigation in downstream areas.
This undoubtedly exposes agricultural workers downstream to health risks (Abd El Lateef, Hall,
Lawrence, & Negm, 2006).
4. THE APPROACH
Focus on Health Risks
The research examined the relative health risks associated with different wastewater management
strategies in a ‘typical’ drainage basin in the delta region. The study focused on the health risks
associated with the use of untreated and treated wastewater lifted from agricultural drains and
canals downstream of a notional drainage basin. Inflow to the drainage basin was considered to be
wastewater flows from houses, plus the flow in a notional drain.
Health risks in downstream areas are a function of water quality and farming practices. In Egypt,
particularly in the Nile delta region, most wastewater is discharged into agricultural drains either
directly or via the sewerage/ wastewater treatment network. The resultant water quality in
downstream channels therefore depends primarily on the;
Baseline water quality and flow upstream of the sanitation system under consideration
Rate and quality of water discharging via sewerage and wastewater treatment system
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Rate and quality of water discharging outside the sewerage/ wastewater treatment system
(from domestic onsite systems and unregulated commercial discharges).
Figure 2 shows how pathogens flow from households to farm workers and consumers.
Figure 2: Pathogen flow in the notional drainage basin
Production of wastewater at the household (connected and non-connected households)
Sewer connection and Wastewater treatment
Bayara and no treatment
plant
Discharge
With dilution in agricultural drain Direct application
Exposure to contaminated wastewater on the farm
Additional on-farm, post-harvest and in-kitchen
No additional precautions
precautions
Additional burden of disease associated with reuse of wastewater
Source: Authors illustration
On the left is what could be called the “low-risk transmission route�? which involves collection of
household waste in a sewer, its treatment at an appropriate treatment plant, dilution in an
agricultural drain or canal prior to re-use, and the deployment of appropriate on-farm, post harvest
and in-kitchen interventions, all of which minimize the risk of transmission of disease. On the right is
a notional “high-risk transmission route�? where untreated waste is applied directly to the field and
there are no on-farm, post-harvest, or in-kitchen interventions.
The actual situation is a blend of these two extremes along with a number of “medium-risk�?
transmission routes utilizing some but not all of the precautionary measures shown on the left hand
side of Figure 2.
Risk Management Strategies
Reductions in risks associated with reuse of wastewater can broadly be achieved in three ways:
(a) diversion of wastewater flows from low-treatment to high-treatment facilities prior
to discharge;
(b) improved levels of treatment in existing facilities; and
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(c) improved on-farm and post-harvest practices.
The focus of current investment strategies in the Nile Delta region is primarily on:
rehabilitating existing treatment plants;
commissioning new treatment plants; and
construction of new sewer networks.
As long as connectivity rates to the sewer network remain low none of these strategies is likely to
reduce health risks to downstream agricultural workers or consumers. Furthermore little work has
been done to assess the performance of existing treatment processes on removal of the key
pathogens responsible for adverse health impacts.
In reality, there are additional wastewater management options which could be considered and
which might have additional merit in terms of health benefits. These include:
providing alternative (or additional) treatment steps at the household or wastewater
treatment plant level;
creating incentives for higher rates of connectivity to the existing sewer networks;
increasing formal septage collection rates from onsite sanitation systems and
delivery to wastewater treatment facilities thereby reducing discharge of untreated
wastes;
modification of downstream agricultural practices; or
a combination of these strategies.
The study set out to explore the impacts of these strategies by modeling the overall flow of
pathogens through a single drainage basin, using a combination of theoretical and field-based data.
The study explored likely current and future scenarios and examined a range of interventions and
their impact on downstream health outcomes.
5. THE MODEL
Typical Drainage Basin
The study made use of a simple mass-balance model of a ‘typical’ drainage basin or sanitation area.
It explored how the various streams of waste, treated to difference levels, impact on water quality
downstream. To give maximum flexibility the model allowed for a range of scenarios to be explored.
Five categories of households were defined and each household in the notional basin was assigned
to one of these categories:
Category I: Connected via sewer to Wastewater Treatment Plant (WWTP) - Oxidation Ditch
or Activated Sludge process
Category II: Connected via simplified sewer to WWTP - Waste Stabilization Pond
Category III: Not connected to sewer – using improved anaerobic treatment and secondary
polishing),e ach system shared between three households
Category IV: Not connected to sewer – using effective septic tank, one per household
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Category V: Not connected (no facilities or utilizing a bayara or trench to collect household
waste)
At the start the model was set up using a ‘typical scenario’ for the delta region; 88% of households
using poorly-functioning household facilities (known as bayaras or trenches) and the remaining 12%
connected to either a centralized oxidation ditch system or a centralized activated sludge system
which was assumed to be working at 50% capacity.
Interventions
For simplicity, the model considered that wastewater from already-connected households (category
I) would remain with the same treatment option. Only households currently NOT connected to the
network and having no treatment (category VI) were considered as having potential to move.
Various interventions were modeled (Table 1). In each case it was assumed that new sewer
connections would be made to the existing treatment plant to bring it up to full capacity. For the
remaining households one of six possible interventions was considered. The model then calculated
the worst-case scenario for downstream water quality assuming typical upstream values in the
receiving drainage water.
Table 1: Intervention Options used in this research
Intervention Category Comment
shift
1. Convert Bayaras to septic V to IV This option assumes the provision of onsite
tank facilities. It would be enhanced by the
addition of well regulated and properly
financed collection services. Proprietary all-in-
one systems would provide better protection
from groundwater infiltration
2. Improved Bayaras to V to IV This option assumes provision of shared
provide anaerobic facilities (one per three households). It would
treatment and secondary be enhanced by the addition of well regulated
polishing and properly financed collection services.
3. Connect Bayara households V to III Requires construction and operation of
to WSP WWTP sewerage or incentives for septage to be
4. Connect Bayara households VI to II delivered to WWTP. Sewerage may require
to oxidation ditch or pumping so costs will be modeled with and
activated sludge WWTP without pumping. WSPs may be decentralized
or centralized.
5. On-farm and post-harvest - Non-infrastructure intervention with behavior
interventions change
6. Convert Bayaras to septic VI to V
tank or shared anaerobic plus Infrastructure plus behavior change
process with polishing behavior intervention
PLUS on-farm and post- change
harvest interventions
Source: Authors summary of model scenarios
Field Test Sites
To help link the model to conditions on the ground, two locations were selected for detailed field
study. These were Sidi Salem, an oxidation ditch treatment plant with extended aeration in Kafr-El
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Sheikh Governorate, and El-Moufty El-Kobra Waste-stabilization Pond plant in the same area. Water
quality testing was carried out in these two sites over the period between December 2010 and
February 2011. Data from the field-testing was used to calibrate the model.
Calculating Health Risks from Water Quality
Quantifiable microbial risk assessment (QMRA) is a tool which can be used to help operationalize the
2006 WHO guidelines on reuse of wastewater agriculture (World Health Organisation, 2006). It does
this by determining a numerical value of the risk (or probability) of a disease or infection occurring as
a result of an individual being exposed to a specified number of a particular pathogen.
Provided dose-response data are available QMRA can be used to estimate disease and infection risks
which accrue to downstream populations who come into contact with contaminated wastewater in
a range of ways for any pathogen.
Figure 3 shows the logical relationship between incidence of pathogens and health impacts.
In order to calculate health impacts the dose-response equation, disease-infection ratio and the
impact in terms of ill-health and death must be known or estimated. QMRA then allows the
probable health impacts from exposure to certain pathogens to be calculated. Further information
on QMRA techniques is summarized in Appendix 1. Mara (2010) and Mara, Hamilton and Sleigh
(2010) provide full details of QMRA techniques for assessing health risks associated with wastewater
reuse.
Figure 3: Relating incidence of pathogens to health impact in downstream populations
Incidence of
key pathogens
Dose-response equation
Infection risk
Disease-infection ratio
Disease risk
YLL and YDL
Health impact
Source: Authors illustration
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6. PARAMETERS FOR USE IN THE MODEL
Acceptable Additional Risk to Health
A key step in the process was to establish an acceptable level of additional risk to health over
baseline conditions associated with the use in agriculture of wastewater, either directly used or after
mixing in downstream drains and canals. Using Quantifiable Microbial Risk Analysis (QMRA), this
acceptable additional risk of certain disease types, could then be converted into reference standards
for incidence of key pathogens in irrigation water applied at the field level.
Health risk is expressed in terms of DALYs, a measure which combines both mortality and morbidity
to calculate the overall impact of a disease or disease group (see Box 1 ).
In this study a maximum tolerable additional DALY loss of 10-4 per person per year was used
following the publication of the WHO Update to the 2006 Guidelines (World Health Organisation,
2006). This corresponds to an additional disease risk of 10-2. For an individual this is “equivalent to
an additional episode of diarrheal disease every 100 years�? (ibid.) over and above generalized
diarrheal disease incidence which globally is equivalent to two episodes every three years.
Box 1: Disability-adjusted Life Years (DALYs)
DALYs are a measure of the health of a population or burden of disease due to a specific disease or
risk factor. DALYs attempt to measure the time lost because of disability or death from the disease
compared with a long life free of disability in the absence of the disease. DALYs are calculated by
adding the years of life lost due to premature death (YLL) to the years lived with a disability (YLD).
Years of life lost are calculated from age-specific mortality rates and the standard life expectancies
of a given population. YLD are calculated from the number of cases of the disease multiplied by its
average duration and a severity factor ranging from 1 (death) to 0 (perfect health) based on the
disease − for example, watery diarrhea has a severity factor from 0.09 to 0.12, depending on the age
group. DALYs are an important tool for comparing health outcomes because they account for not
only acute health effects but also for delayed and chronic effects − i.e., they include both morbidity
and mortality. When risk is described in DALYs, different health outcomes (e.g., fatal cancers and
non-fatal diarrheal diseases) can be compared and risk management decisions can be prioritized.
Source: (World Health Organisation, 2006)
Key Indicator Pathogens
Diarrheal disease is caused by a wide range of pathogens. The 2006 guidelines propose the
following indicator organisms when considering risks from wastewater reuse in agriculture:
Rotavirus, Campylobacter, e-Coli, Cryptosporidium and Ascaris
In 2010, WHO noted that norovirus is the major viral pathogen causing diarrhea in adults while
rotavirus mainly affects children under 5. Since adults are more likely to face exposure due to
wastewater use than children, norovirus is a better indicator pathogen than rotavirus. However, due
to the lack of appropriate sampling and testing facilities near to the field test sites rotavirus, e-coli
and ascaris were taken as the key indicator organisms in this study.
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On-farm, Post-harvest and In-kitchen Measures to Reduce Health Risks
Since irrigation in Egypt is usually practiced by means of flooding the fields, most of the usual on-
farm precautions are not available (use of drip irrigation, watering cans etc). The only option
considered in the model is the use of pathogen die-off through ensuring a time delay between
irrigation and harvesting. Post-harvest (overnight storage of harvested crops and special
preparation of crops for market) was considered but in-kitchen preparation options were not. A
summary of the relevant post-harvest interventions are shown in Table 2.
Table 2: Health protection control measures and associated pathogen reductions
Control Measure Pathogen reduction Comments
(log units)
On-farm Options
Crop restrictions (no food crops eaten 6-7 Excluded - hard to enforce,
uncooked) depends on crop prices
On-farm treatment
- Three tank system 1-2
- Simple sedimentation 0.5-1 Excluded due to lack of
- Simple filtration 1-3 space
Application methods
- Furrow irrigation 1-2 Excluded due to prevalence
- Low-cost drip irrigation 2-4 of flood irrigation
- Reduction of splashing 1-2
Pathogen die-off 0.5-2 per day Included
Post-harvest options at local markets
Overnight storage in baskets 0.5-1 Included
Produce preparation
- Rinsing salad crops with clean water 1-2
- Washing with running tap water 2-3 Excluded – hard to enforce
- Removing outer leaves of lettuces etc 1-3
In-kitchen preparation methods
- Disinfection 2-3
- Peeling 2 Excluded – behavior
- Cooking 5-6 change hard to enforce
Based on (Mara, Hamilton, Sleigh, & Karavarsamis, 2010)
Wastewater Treatment Products
A review of the literature found limited information relating to the health implications of application
of wastewater sludge from wastewater treatment processes in Egypt. For this reason, the sludge
stream was not included in the analysis and only wastewater effluent from treatment plants was
included. This would tend to have the effect of underestimating health risks associated with all the
wastewater treatment plant options considered. For the onsite options, the quality of the mixed
slurry including liquid and solid fractions was considered.
Dilution Options
The conditions of the channel downstream of the treatment plant or where untreated waste is
discharged are a key determinant of the likely quality of water reused in agriculture. Effluent is
discharged into drains of varying size – from major drainage channels to minor ditches. The quality
of water in the downstream receiving water body is also important in determining how significant
10 | P a g e
any contamination caused by the effluent will be. The model therefore allowed for varying flow and
varying water quality in the receiving drain. Resultant concentrations of pathogens in water for
reuse were calculated using a simple mass-balance calculation. No assumptions for pathogen die-off
were included.
Cropping Patterns
The model has the potential to examine health impacts on a range of cropping outcomes. The
typical Egyptian diet contains a significant element of grains and meat, none of which represent
significant transmission risks for pathogens from wastewater due to the processing involved in their
preparation. The diet does however contain a significant volume of tomatoes (estimated
consumption 99kg/capita/ year) and grapes (17 kg/capita/year) (Arab Republic of Egypt, 2009) .
Since detailed data on tomato preparation are not available, the assumption is made that 50% of the
total consumption of tomatoes and all of the grapes are consumed uncooked. Contamination from
this consumption pattern is assumed to be via consumption of water from the crop surface.
Ingestion of contaminated soil attached to the crop is considered to be marginal.
7. RESULTS
Downstream Water Quality
Data from the field observations and a review of previous studies confirmed that the quality of
water in receiving drains is extremely poor in the Delta region (see Appendix 2). Incidence of Ascaris
and Rotavirus is highly variable (probably reflecting infection rates in the command areas of the
plants under study) and the performance of the plants in removing pathogens was also mixed.
There have been numerous studies that have analyzed and modeled water quality in various drains
and canals in the delta region. Few of these provide detailed information on pathogenic
contamination. Work carried out in preparation for the World Bank’-supported Integrated
Sanitation and Sewerage Infrastructure Project (ISSIP) however noted very “high pollution loads as a
result mainly of sewage and industrial wastewater discharges�? (EcoConServ, 2007). This finding
confirmed earlier extensive monitoring of the Nile system (DAI and IRG, June 2003) which noted that
“total coliform bacteria reach 106 MPN/11ml …in many drains in the delta which is considerably
higher than the Egyptian standard of 5000 MPN/100ml.�? A selection of data from Gharbeya and Kafr
El Sheikh are shown below.
Table 3: Incidence of Fecal Coliforms in Drains and Canals
Location Observed Value
Mit Yazid Canal >10,000 MPN/100ml
Mit Yazid Command >60,000 MPN/100ml
Area Drains
Mahmoudia Canal >100,000 MPN/100ml
System Drains
Source: (EcoConServ, 2007)
Most observers comment that the highest concentrations of most water quality parameters occur
during the winter time (El Sayad & Abdel Gawad, September 2001). This finding was confirmed by a
study of the incidence of parasite eggs in drain water where incidence appeared to be higher in the
11 | P a g e
autumn and winter months (August-January) than in spring and summer (Stott, Jenkins, Shabana, &
May, 1997).
This higher concentration of pathogens in the winter coincides with the period of minimum flow.
Seasonal variation in reuse for example is high with peak reuse flows in the period from June to
September coinciding with the peak summer season (Figure 4) and the lowest rates in January and
February.
Figure 4: Monthly reuse of drainage water in the Nile delta during 2002/2003 (BCM)
0.8
0.7
0.6
0.5
Western delta
0.4
Middle delta
0.3 Eastern delta
0.2
0.1
0
Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul
Source: (Mostafa, El-Gohary, & Shalby, Date Unknown)
Overall the literature confirmed that there are high levels of pathogenic contamination in the canal
and drain network. Likely sources include both domestic waste discharged directly from household
septic tanks and cess pits, discharge of partially treated wastes from treatment plants and industrial
effluent discharges.
Information on the quality of wastewater and the incidence of our key indicator pathogens is drawn
from the field testing carried out as part of this project and cross checked with data from earlier field
studies ( (Stott, Jenkins, Shabana, & May, 1997), (El Gohary, El-Hawarry, Badr, & Rashed, 1996)
(Sherief, El-S Easa, El-Samra, & Mancy, 1996). A summary of the data used for the model is shown in
Table 4.
Effectiveness of Treatment
The waste stabilization pond at El Moufty El Kobra appeared to be functioning well below its design
capability during the period of this study. This was confirmed by field observations to be caused by
contamination of the sewer network from a dairy operation within the community. Visual
observations confirmed heavy algal growth in all the ponds and possibly overloading which may
have been exacerbated due to high levels of animal excreta in the influent. At Sidi Salem, as would
be expected, the removal of pathogens upstream of the chlorination system was relatively poor, and
even below the chlorinator some pathogens remained suggesting some inefficiencies in the process.
12 | P a g e
Table 4: Model Parameters for Water and Wastewater Quality
Model Parameter
Raw Wastewater (Bayara)
e-Coli 2.00E+07 (/100ml)
Rotavirus 1.00E+05 (/100ml)
Ascaris 3 nr/liter
Raw Sewage
e-Coli 1.00E+07(/100ml)
Rotavirus 1.00E+04(/100ml)
Ascaris 3 nr/liter
Receiving Drain Water
e-Coli 4.00E+02(/100ml)
Rotavirus 1.00E+01(/100ml)
Ascaris 0 nr/liter
Source: Authors summary estimates
Figure 5: Average observed rates of e-coli in study wastewater treatment plants*
e-coli
1.00E+08
1.00E+07
1.00E+06
1.00E+05
1.00E+04
1.00E+03
1.00E+02
1.00E+01
1.00E+00
5ENC
3FP1
3FP2
1WW
1WW
2AB1
2AB2
4MP1
4MP2
9CDD
6EC
9CDD
8CM
8CM
9CD
7CU
7CU
Ave Ave
El-Mofti El-Kobra Sidi Salem
Source: Field study data
*See Appendix 2 for a detailed breakdown. WW= wastewater influent, AB=Anaerobic Basin, FP=Facultative
Pond, MP= Maturation Pond, CU=Drain upstream of WWTP discharge point, CM = drain at mixing point, CDD =
drain downstream of mixing point, ENC= effluent upstream of chlorination, EC = effluent downstream of
chlorination
The baseline scenario is thus very poor. A high percentage of wastewater is reaching drains
untreated, drains are in poor condition generally to begin with, and pathogen removal at the existing
treatment plants is not particularly effective.
Using both the field observations and literature, typical treatment efficiencies for the options under
consideration were used in the model assuming that treatment processes were working to their full
potential for Egyptian conditions (see Table 5).
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Table 5: Parameters for treatment options
Effectiveness of Treatment
Log reduction rates
Activated Waste Anaerobic Septic tank
Sludge/ stabilization treatment
oxidation pond and polishing
ditch
Upstream of chlorination
e-Coli 0.44 3 3 2
Rotavirus 0 2 2 2
Ascaris 0 2 2 2
At Chlorination
e-Coli 3 n/a n/a n/a
Rotavirus 3 n/a n/a n/a
Ascaris 2 n/a n/a n/a
Source: Authors summary estimates
Impact of Sanitation Options on Water Quality
The project model reconfirmed the observed results for the Baseline scenario in the context of the
model drainage basin. Downstream water quality was then calculated under the study scenarios
and the results are shown in Table 6 which indicates the worst quality water that would result under
each intervention.
Table 6: Downstream water quality in receiving drain assuming chlorination
Intervention Baseline 1 2 3 4 5 6
Mixed drain
water
total fecal unit/100ml 1.E+08 1.E+06 1.E+05 3.E+04 3.E+04 4.E+04 1.E+06
coliforms
e-coli unit/100ml 2.E+07 1.E+05 1.E+04 3.E+03 3.E+03 4.E+03 2.E+05
Rotavirus unit/100ml 1.E+05 1.E+02 1.E+02 8.E+01 9.E+01 1.E+02 1.E+03
Ascaris unit/100ml 3.E+00 8.E-01 8.E-01 8.E-01 9.E-01 1.E+00 3.E-02
Sludge
total kg/day 9.E+02 9.E+02 1.E+03 5.E+03 6.E+03 1.E+04 9.E+02
volume
total fecal MPN/day 9.E+11 9.E+11 1.E+12 9.E+11 2.E+12 1.E+13 9.E+09
coliforms
Source: Study results
Incidence of Ascaris is low (and this is reinforced by findings in the literature) (Stott, Jenkins,
Shabana, & May, 1997) but it has been included in the analysis because of its relative importance
with respect to onsite sanitation systems. The main health impacts however are associated with
Rotavirus infection which remains a significant health risk in Egypt (Khoury, Ogilvie, El Khoury, Duan,
& Goetghebeur, 2001).
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Table 7 shows the results for QMRA simulations of health risks associated with exposure to rotavirus
as a function of exposure to all fecal coliforms (for a longer discussion on this method see (Mara,
Sleigh, Blumenthal, & Carr, 2007)).
Table 7: Median Infection risks from consumption of wastewater-irrigated tomatoes estimated by
10,000-trial Monte Carlo Simulation*
Wastewater Quality (e- Median Infection risks
coli per 100ml) associated with
rotavirus pppy
107 - 108 1
106 - 107 1
105- 106 0.96
104 - 105 0.28
103 - 104 3.2E-02
102 - 103 3.1E-03
10 – 102 3.2E-04
1 – 10 3.34E-05
Source: Results of simulations using (Mara & Sleigh, QMRA: A Beginners
Guide - Monte carlo simulation programmes, 2008)
*375g of raw tomato eaten per person per 2 days; 3.5–4ml wastewater remaining on 375g tomato after
irrigation; 0.1–1 rotavirus per 105 e. coli; 1022–1023 rotavirus die-off between harvest and consumption; ID50 ¼
6.7 ^ 25% and a ¼ 0.253 ^ 25% for rotavirus.
The acceptable marginal health risk is 10-2 (See above and also (Mara, Sleigh, Blumenthal, & Carr,
2007) gives a target wastewater quality at the farm gate (for irrigation workers) or at market (for
consumers of crops) of the order of 103 total FC per 100ml. Based on the median wastewater quality
experienced in the downstream drains under baseline conditions a total reduction in pathogens of
the order of 106 is required to achieve this acceptable level of risk.
Using the QMRA to assess the impact on downstream health of exposure to irrigated crops Table 8
indicates the annual incidence of disease in the affected population. It is worth noting here the very
conservative assumption which is that only the population in the command sanitation basin under
consideration consumes crops irrigated there. In reality crops are likely to be exported to urban
areas and the affected population is likely to be greater than that shown here.
Table 8 shows that some of the proposed interventions could have a significant positive impact on
health. Improved on-farm and post-harvest management of food crops could reduce diarrheal
incidence by more than 90%, preventing more than 2.5 million diarrhea cases in the area over 20
years (for a population of around 225,000 people) when combined with improvements to the design
and operation of onsite sanitation systems. Networked sewerage with treatment also has a
significant impact on health but in the case of activated sludge and oxidation ditches this is highly
dependent on effective and continuous chlorination. The overall health impact, expressed in
diarrheal disease incidence in the total population is summarized in Table 9.
15 | P a g e
Table 8: Incidence of diarrhea and DALY burden under various scenarios
Scenario Baseline 1 2&3 4 5 6
Disease Risk pppy
Rotavirus 1.00E+00 9.90E-01 2.40E-01 2.75E-01 9.90E-01 9.00E-02
Cryptosporidium 1.80E-01 1.70E-02 1.45E-03 1.65E-03 1.70E-02 2.00E-04
Ascaris 3.00E-04 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00
Disease incidence (cases per year)
Rotavirus 225,000 222,750 54,000 61,875 222,750 20,250
cryptosporidium 40,500 3,825 326 371 3,825 45
Ascaris 68 0 0 0 0 0
Total 265,568 226,575 54,326 62,246 226,575 20,295
REDUCTION 0% 15% 80% 77% 15% 92%
DALYs (cases per year)
rotavirus* 5,850 5,792 1,404 1,609 5,792 527
cryptosporidium 61 6 0 1 6 0
Ascaris 1 0 0 0 0 0
Total 5,911 5,797 1,404 1,609 5,797 527
REDUCTION 0% 2% 76% 73% 2% 91%
*/1 DALY loss per case of disease Rotavirus: 2.6E-2; Cryptosporidium 1.5E-3; (Mara & Bos, Risk Analysis and Epidemiology;
The WHO 2006 Guidelines for Safe Use of Wastewtater in Agriculture, 2010) Ascaris 8.25E-3 ( (Mara D. D., Hamilton,
Sleigh, Karavarsamis, & Seidu, 2010)
*/2assume children under 2 not consuming irrigated crops
Source: Model results
Table 9: Overall reduction in icidence of diarrhoeal disease and DALYs by intervention (20 years)
Scenario ddi DALY
Annual Total Annual Total
reduction reduction reduction reduction
1 38,993 779,850 114 2,281
2&3 211,241 4,224,825 4,507 90,136
4 203,321 4,066,425 4,302 86,040
5 38,993 779,850 114 2,281
6 245,273 4,905,450 5,385 107,695
Source: Model results
Cost Effectiveness
Cost data for the various options was assembled from project reports and cross checked with data
included in the Egyptian Guidelines on Rural Sanitation (Chemonics Egypt, Ahmed Gaber and
Associates, 2006). Unit costs were assessed for typical systems of a reference size since the unit
costs of sewerage networks and wastewater treatment systems do vary with the size and
distribution of the population served. Typical values were selected for this analysis, but more
16 | P a g e
detailed comparisons could be made for particular cases on the ground. The cost data are
summarized in Table 10.
These unit costs were converted to 20-year lifecycle costs assuming discount rate of 8%. Net present
values were then calculated for each option (Figure 6).
Using these data, costs of the notional interventions could be compared to the 20-year health
impacts computed from the data in Table 8.
Cost-effectiveness ratios for each option are shown in Figure 7 against a logarithmic scale. Figure 7
shows that replacing septic tanks with no additional treatment improvements is significantly less
cost-effective than other ‘engineered’ solutions. Figure 8 therefore shows only the engineered
solutions against a linear scale.
Table 10: Unit costs for sanitation interventions
Unit Capital costs Annual Operational
costs (per unit)
Connections Design EGP US$ EGP US$
population
Household/ cluster options
Network 0 0 0 0 0
Septic tank 1 5 600 101 150 25
Anaerobic
Treatment plus 3 15 750 126 200 34
Polish
Decentralized options
Network 1,000 5,000 4,000,000 670,017 60,000 10,050
Waste stabilization
1,000 5,000 500,000 83,752 25,000 4,188
pond (WSP)
Centralized options
Network 10,000 50,000 40,000,000 6,700,168 600,000 100,503
Network with
10,000 50,000 40,000,000 6,700,168 4,000,000 670,017
pumping
Waste stabilization
10,000 50,000 2,500,000 418,760 250,000 41,876
pond (WSP)
Activated sludge/
10,000 50,000 12,500,000 2,093,802 2,500,000 418,760
oxidation ditch
On farm practices (36 months)
3,000,000 502,513 120,000 20,101
Source: Authors estimates based on ISSIP project documents and cross checked with (Chemonics Egypt, Ahmed Gaber and Associates,
2006)
17 | P a g e
Figure 6: 20-year discounted NPV for sanitation options
OFT plus ST
OFT
AS/OD with pumping
AS/OD
Centralised WSP with pumping
Centralised WSP
Decentralised WSP
Anaerobic treatment plus polishing
Improved septic tanks
$- $50 $100 $150 $200 $250 $300
Source: Model results
OFT – On-farm treatment; AS/OD = Activated Sludge or Oxidation Ditch; WSP = Waste Stabilization Pond
Figure 7: Cost effectiveness of interventions US$ per DALY avoided (log scale)
Improved septic tanks +OFT
OFT
AS/OD with pumping
AS/OD
Centralised WSP with pumping
Centralised WSP
Decentralised WSP
Anaerobic treatment plus polishing
Improved septic tanks
$1 $10 $100 $1,000 $10,000
Source: Model results
OFT – On-farm treatment; AS/OD = Activated Sludge or Oxidation Ditch; WSP = Waste Stabilization Pond
18 | P a g e
Figure 8: Cost effectiveness of interventions (excluding household septic tanks) US$ per DALY
avoided
Improved septic tanks +OFT
OFT
AS/OD with pumping
AS/OD
Centralised WSP with pumping
Centralised WSP
Decentralised WSP
Anaerobic treatment plus polishing
$0 $100 $200 $300 $400 $500 $600 $700
OFT – On-farm treatment; AS/OD = Activated Sludge or Oxidation Ditch; WSP = Waste Stabilization Pond
8. DISCUSSION AND CONCLUSIONS
Current situation
The data and model all confirm that the most significant health risk is posed by the un-regulated
dumping of waste from poorly-performing household cess pits and septic tanks. It is worth noting
here that discharges from industrial units have not been included in this analysis, but this could be
incorporated relatively easily. In the drainage basins observed during this study however visual
observation suggests that dumping of the contents of domestic systems is a significant contributory
factor in polluting the drains. Furthermore, some domestic waste may be being dumped into
secondary and tertiary drainage/ irrigation channels and recycled for irrigation without dilution.
Effective sanitation options
Currently the focus of much HCWW investment is on the construction of additional treatment
capacity. However the mass –balance modeling carried out here along with an analysis of potential
water treatment options suggests that other, lower cost, alternatives may have equal importance
and more potential in the short term to reduce health risks to downstream irrigators.
The most effective treatment intervention was the replacement of faulty household septic tanks/
cess pits, with effective primary and secondary treatment. This could be provided through
neighborhood anaerobic systems with polishing or proprietary household septic tanks which are
properly constructed and managed.
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Even where centralized systems are preferred in the long run improvements to onsite sanitation
represent an important and cost-effective short-term intervention that could have significant
health implications. Furthermore household facilities could take advantage of more flexible
approaches to finance, with households bearing a greater share of the upfront costs; willingness to
pay to reduce the inconvenience of the current system of bayaras which need to be emptied
frequently. Improved management of onsite systems could be a very useful focus of wastewater
management strategies in the delta.
Waste stabilization ponds also provide good health protection and are not reliant on the operation
of chlorinators for pathogen removal.
Surprisingly, the available field data and data from the literature along with the modeling did not
suggest that the Extended Aeration Oxidation ditches and Activated Sludge plants have a
significant impact in terms of achieving required health targets unless effective chlorination could
be guaranteed; field observations suggest this is not the case at present. Furthermore the analysis
presented here excludes the health implications of managing sludge products from these plants –
the cost and risks associated with sludge handling make these options even less attractive than is
suggested by our analysis.
More significantly, almost all infrastructure interventions were bettered by changes in on-farm
and post-harvest behaviors in terms of cost-effective health protection. This is an intervention
which should not be ignored.
The costs of aerated systems are extremely high when compared to ponds because of the high
operational costs of the former when energy prices are properly calculated. Ponds are considered
to be expensive due to their higher land take, but at flow rates up to around 20,000m3 per day, the
Rural Sanitation Guidelines suggest that they are better value for money over their operational
lifetime (Chemonics Egypt, Ahmed Gaber and Associates, 2006).
The relative cost-effectiveness of all the treatment processes is highly dependent on their scale. Like
most networks with treatment processes, centralization has a positive effect on unit costs up to a
point. Decentralized waste stabilization ponds for example are more costly than centralized
systems using the same treatment (Figure 9) if we assume that per capita operational costs for the
sewer network remain equal.
If however community management of at least some part of the operation of the system is viable
and advantageous for other reasons, then decentralized options become more financially
attractive. Furthermore the use of smaller systems could obviate the need for pumping which is the
single most effective way of bringing down unit costs and reducing the long term financial burden on
the water companies.
20 | P a g e
Figure 9: Cost effectiveness of waste stabilization ponds systems of varying sizes (US$ per DALY
avoided)
DC 10000
DC8000
DC6000
DC4000
DC2000
DC1000
DC500
DC100
$130 $135 $140 $145 $150 $155 $160 $165 $170 $175
Source: Model results
Note: Y axis values indicate the number of connections per system under consideration.
Water and Wastewater Quality Standards
Until recently, legislation relating to reuse of agricultural drainage water was extremely restrictive. It
is based on Egyptian Water Protection Law 48/1982 Articles 65 and 68 respectively.
Table 11: Selected Water quality parameters in Law 48/1982
Parameter Standard
TDS 2000 mg/l
DO >4mg/l
Temperature <35°C
Ph 6-9
TDS 2000mg/l
TSS 50mg/l
BOD 60mg/l
NO2 1mg/l
NO3 45mg/l
Phosphate 1mg/l
The National Water Quality and Availability Management Program (NAWQAM) developed two
composite indicators for water quality based on the standards. Table 12 shows the parameters
considered in the development of these indices.
21 | P a g e
Table 12: Water quality parameters considered in the development of water quality indices (WQI)
Parameter WQI-65 WQI-68
TDS Yes Yes
DO Yes Yes
Fecal Coliform Yes Yes
Temperature Yes Yes
pH Yes Yes
Turbidity Yes Yes
BOD Yes No
NO3 Yes No
Phosphate Yes No
Source: (NAQWAM, 2001)
NAWQAM went on to carry out extremely valuable monitoring and analysis of water quality in
selected drains and to assess the impact of WWTPs on water quality. However, Table 12 shows the
very high number of parameters that must be considered when assessing drain water quality
irrespective of the downstream context in which drainage water will be reused. The conclusion of
the study on the Hados drain was that ‘most WWTPs operating within the study area violate the
Egyptian law 48/1982’. The study further went on to conclude that ‘the most appropriate treatment
technique in the Delta of Egypt is the activated sludge process. Trickling filters and oxidation ponds
may also be used’ (NAQWAM, 2001). This final conclusion suggests that the use of composite
parameters may place a much stronger emphasis on nutrient removal than on the removal of
pathogens that are harmful to human health since the activated sludge process tends to be more
effective at the former than the latter (Jimenez, Mara, Carr, & Brissaud, 2010).
Some observers have noted that the new National Code for wastewater reuse issued in 2000 is “less
restricted�? than previous legislation (notably Decree 44). The National Code allows for a
consideration of standards and levels of treatment alongside monitoring and analysis of cropping
patterns, irrigation methods and health protection measures. This approach is more in line with the
latest guidelines for WHO on safe use of wastewater, excreta and greywater (World Health
Organisation, 2006) which take a risk-minimization approach rather than the earlier approach of
setting absolute targets for a range of water quality parameters. Use of this more flexible approach
opens up the opportunity for a more nuanced analysis of investment strategies – with more
emphasis on achieving optimum outcomes in terms of both health protection and nutrient re-use
when considering agricultural applications of treated, partially treated and untreated wastewater.
Such an approach might result in rather different conclusions than those reached by the NAQWAM
team.
Conclusions and Further Work
The study explored the likely health impacts of wastewater management and sanitation investments
in the Delta region of Egypt. Overall the study found that conventional approaches to sanitation
management, and in particular the preference for centralized wastewater treatment processes with
extended aeration many not always offer the most cost-effective solution in terms of health
protection. While these options will remain an important part of the solution, health considerations
as well as the need to keep operational costs as low as possible suggest that other more modern
approaches may offer a better solution. These might include a blend of onsite sanitation
22 | P a g e
improvements, including the use of proprietary prefabricated septic tanks, better management and
financial arrangements for emptying of septic tanks and pits and some decentralized and centralized
wastewater treatment.
The study developed a modeling approach which combines simple assessments of impacts on
downstream water quality with QMRA to assess broad health impacts. The approach, while
relatively simple and easy to carry out, would be improved with more detailed location-specific data
and in particular more information on downstream irrigation and harvesting practices for key crops.
Further work would enhance the value and accuracy of the model used as real cost data from
operational systems could progressively be included to provide a more accurate assessment
particularly of operational costs. Field testing of key indicator pathogens could usefully be scaled up
as there is limited data currently available with which the efficacy of existing treatment processes in
terms of health protection can be assessed.
23 | P a g e
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Gastroenteritis in the Middle Eastern and North African Pediatric Population. BMC Infectious
Disesases , 11:9.
Mara, D. D. (2010). Quantiative Microbial Risk Analysis: the 2006 WHO Guidelines and Beyond - An
Introduction. Washington DC: World Bank.
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of Wastewtater in Agriculture. In P. Drechsel, C. Scott, L. Raschid-Sally, M. Redwood, & A. Bahri,
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Mara, D. D., & Sleigh, P. A. (2008). QMRA: A Beginners Guide - Monte carlo simulation programmes.
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Bahri, Wastewater Irrigation and Health: Assessing and Mitigating Risk in Low Income Countries.
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APPENDIX 1: QMRA
Introduction
Quantifiable microbial risk assessment (QMRA) is a tool which can be used to help operationalize the
2006 WHO guidelines on reuse of wastewater agriculture (World Health Organisation, 2006). It does
this by determining a numerical value of the risk (or probability) of a disease or infection occurring as
a result of an individual being exposed to a specified number of a particular pathogen.
Provided dose-response data are available QMRA can be used to estimate disease and infection risks
which accrue to downstream populations who come into contact with contaminated wastewater in
a range of ways for any pathogen. Figure 3: Relating incidence of pathogens to health impact in
downstream populations in the main text shows the logical relationship between incidence of
pathogens and health impacts.
In order to calculate health impacts the dose-response equation, disease-infection ratio and the
impact in terms of ill-health and death must be known or estimated.
Dose-response relationships
Infection risk from a single exposure to a particular pathogen is computed using a dose-response
equation. Mara gives the following approach to estimating disease and infection risk using one of
the following two QMRA dose-response equations (Mara, 2010):
Exponential dose-response equation (commonly used for protozoan pathogens):
PI(d) = 1 − e−rd (1)
(b) Beta-Poisson dose-response equation (commonly used for viral and bacterial pathogens):
(2)
where PI(d) is the risk of infection in an individual from a single exposure to (here, the ingestion of) a
single pathogen dose d; N50 is the median infective dose (i.e., the value of d that causes infection in
50% of the exposed population); and α and r are pathogen ‘infectivity constants’.
The annual risk of infection is given by:
PI(A)(d) = 1 – [1 – PI(d)]n (3)
where PI(A) (d) is the annual risk of infection in an individual from n exposures per year to the single
pathogen dose d.
Disease-infection ratios
Not all infections however result in disease. The risk of disease, as opposed to the risk of infection, is
given by:
PD(d) = aPI(d) (4)
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where PD(d) is the risk of disease in an individual from a single exposure to the single pathogen dose
d; and a is the disease/infection ratio (i.e., the proportion of the infected population that becomes
clinically ill (thus the value of a is in the range 0−1).
Mara goes on to discuss how these values of risk (probability) expressed per person per exposure
event can be translated into an annual infection risk – i.e. the percentage chance an individual has of
becoming infected as a result of n exposures per year. Since the values of N50 and α are subject to
some uncertainty Monte Carlo (MC) risk simulation is used to provide a more robust solution to
QMRA calculations (for further information on MC simulation see for example Mara, 2010).
QMRA can thus be used to compute risk of disease.
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APPENDIX 2: DATA TABLES
Table 13: Water Quality Data – El Moufty El Kobra
Total
Coliforms e-Coli
Site Date Location (NRC) (NRC) Rotavirus Helminths
El-Moufty El-Kobra 26/12/2010 1WW 2.00E+08 7.00E+07 0 0.00E+00
El-Moufty El-Kobra 09/01/2011 1WW 4.80E+08 2.60E+07 0 2.00E+00
El-Moufty El-Kobra 27/01/2011 1WW 4.80E+08 1.80E+07 1.00E+05 1.00E+00
El-Moufty El-Kobra 21/02/2011 1WW 1.10E+08 1.10E+07 1.00E+04 3.00E+00
El-Moufty El-Kobra Ave 1WW 3.18E+08 3.13E+07 0 0
El-Moufty El-Kobra 26/12/2010 2AB1 2.40E+07 3.10E+06 0 0.00E+00
El-Moufty El-Kobra 09/01/2011 2AB1 1.50E+07 1.60E+06 0 0.00E+00
El-Moufty El-Kobra 27/01/2011 2AB1 1.10E+07 2.10E+05 1.00E+04 1.00E+00
El-Moufty El-Kobra 21/02/2011 2AB1 1.60E+07 1.30E+05 1.00E+04 1.00E+00
El-Moufty El-Kobra Ave 2AB1 1.65E+07 1.26E+06 0 0
El-Moufty El-Kobra 26/12/2010 2AB2 2.80E+07 2.30E+06 0 0.00E+00
El-Moufty El-Kobra 09/01/2011 2AB2 1.10E+07 1.10E+06 0 0.00E+00
El-Moufty El-Kobra 27/01/2011 2AB2 3.10E+06 4.60E+06 1.00E+05 0.00E+00
El-Moufty El-Kobra 21/02/2011 2AB2 2.80E+06 2.60E+05 1.00E+04 0.00E+00
El-Moufty El-Kobra Ave 2AB2 1.12E+07 2.07E+06 0 0
El-Moufty El-Kobra 26/12/2010 3FP1 2.10E+06 1.50E+05 0 0.00E+00
El-Moufty El-Kobra 09/01/2011 3FP1 6.80E+05 1.40E+05 0 0.00E+00
El-Moufty El-Kobra 27/01/2011 3FP1 4.10E+05 1.00E+05 1.00E+04 0.00E+00
El-Moufty El-Kobra 21/02/2011 3FP1 3.10E+05 4.80E+04 1.00E+03 0.00E+00
El-Moufty El-Kobra Ave 3FP1 8.75E+05 1.10E+05 0 0
El-Moufty El-Kobra 26/12/2010 3FP2 9.30E+06 7.00E+05 0 0.00E+00
El-Moufty El-Kobra 09/01/2011 3FP2 4.10E+06 2.80E+05 0 0.00E+00
El-Moufty El-Kobra 27/01/2011 3FP2 4.80E+05 4.60E+04 1.00E+04 0.00E+00
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Total
Coliforms e-Coli
Site Date Location (NRC) (NRC) Rotavirus Helminths
El-Moufty El-Kobra 21/02/2011 3FP2 1.60E+05 6.80E+04 1.00E+03 0.00E+00
El-Moufty El-Kobra Ave 3FP2 3.51E+06 2.74E+05 0 0
El-Moufty El-Kobra 26/12/2010 4MP1 7.00E+05 1.20E+04 0 0.00E+00
El-Moufty El-Kobra 09/01/2011 4MP1 1.50E+05 1.30E+04 0 0.00E+00
El-Moufty El-Kobra 27/01/2011 4MP1 7.40E+04 1.30E+04 1.00E+04 0.00E+00
El-Moufty El-Kobra 21/02/2011 4MP1 4.20E+04 4.10E+03 1.00E+02 0.00E+00
El-Moufty El-Kobra Ave 4MP1 2.42E+05 1.05E+04 0 0
El-Moufty El-Kobra 26/12/2010 4MP2 2.80E+05 1.60E+04 0 0.00E+00
El-Moufty El-Kobra 09/01/2011 4MP2 2.60E+05 1.80E+04 0 0.00E+00
El-Moufty El-Kobra 27/01/2011 4MP2 4.60E+04 6.90E+03 1.00E+03 0.00E+00
El-Moufty El-Kobra 21/02/2011 4MP2 3.80E+04 6.10E+03 1.00E+03 0.00E+00
El-Moufty El-Kobra Ave 4MP2 1.56E+05 1.18E+04 0 0
El-Moufty El-Kobra 26/12/2010 7CU 1.20E+02 1.30E+01 0 0.00E+00
El-Moufty El-Kobra 09/01/2011 7CU 1.10E+02 4.20E+01 0 1.00E+00
El-Moufty El-Kobra 27/01/2011 7CU 1.00E+02 5.10E+01 1.00E+01 0.00E+00
El-Moufty El-Kobra 21/02/2011 7CU 1.30E+02 3.40E+01 0.00E+00 0.00E+00
El-Moufty El-Kobra Ave 7CU 1.15E+02 3.50E+01 0 0
El-Moufty El-Kobra 26/12/2010 8CM 7.00E+04 4.60E+03 0 0.00E+00
El-Moufty El-Kobra 09/01/2011 8CM 1.30E+04 1.10E+03 0 0.00E+00
El-Moufty El-Kobra 27/01/2011 8CM 6.80E+03 1.80E+03 1.00E+03 0.00E+00
El-Moufty El-Kobra 21/02/2011 8CM 4.60E+03 4.60E+02 1.00E+02 0.00E+00
El-Moufty El-Kobra Ave 8CM 2.36E+04 1.99E+03 0 0
El-Moufty El-Kobra 26/12/2010 9CDD 2.30E+02 1.80E+02 0 0.00E+00
El-Moufty El-Kobra 09/01/2011 9CDD 2.10E+02 1.00E+02 0 0.00E+00
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Total
Coliforms e-Coli
Site Date Location (NRC) (NRC) Rotavirus Helminths
El-Moufty El-Kobra 27/01/2011 9CDD 2.40E+02 1.20E+02 1.00E+02 0.00E+00
El-Moufty El-Kobra 21/02/2011 9CDD 1.80E+02 1.00E+02 0.00E+00 0.00E+00
El-Moufty El-Kobra Ave 9CDD 2.15E+02 1.25E+02 0 0
Table 14: Water Quality Data – Sidi Salem
Total
Coliforms e-Coli
Site Date Location (NRC) (NRC) Rotavirus Helminths
Sidi Salem 26/12/2010 1WW 1.20E+08 7.00E+07 0 1.00E+00
Sidi Salem 09/01/2011 1WW 3.10E+08 4.60E+07 0 0.00E+00
Sidi Salem 27/01/2011 1WW 1.50E+08 2.70E+07 0.00E+00 0.00E+00
Sidi Salem 21/02/2011 1WW 1.10E+07 1.80E+06 0.00E+00 4.00E+00
Sidi Salem Ave 1WW 1.48E+08 3.62E+07 0 0
Sidi Salem 26/12/2010 5ENC 2.30E+06 6.40E+05 0 1.00E+00
Sidi Salem 09/01/2011 5ENC 4.10E+05 6.40E+04 0 0.00E+00
Sidi Salem 27/01/2011 5ENC 6.10E+05 4.60E+04 0.00E+00 1.00E+00
Sidi Salem 21/02/2011 5ENC 3.80E+05 2.80E+04 0.00E+00 2.00E+00
Sidi Salem Ave 5ENC 9.25E+05 1.95E+05 0 0
Sidi Salem 26/12/2010 6EC 7.00E+04 7.20E+03 0 1.00E+00
Sidi Salem 09/01/2011 6EC 6.20E+03 7.10E+02 0 0.00E+00
Sidi Salem 27/01/2011 6EC 4.30E+03 3.80E+02 0.00E+00 0.00E+00
Sidi Salem 21/02/2011 6EC 2.30E+03 1.30E+02 0.00E+00 0.00E+00
Sidi Salem Ave 6EC 2.07E+04 2.11E+03 0 0
Sidi Salem 26/12/2010 7CU 3.00E+02 1.20E+02 0 0.00E+00
Sidi Salem 09/01/2011 7CU 1.60E+03 1.60E+02 0 0.00E+00
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Total
Coliforms e-Coli
Site Date Location (NRC) (NRC) Rotavirus Helminths
Sidi Salem 27/01/2011 7CU 4.80E+02 1.40E+02 0.00E+00 0.00E+00
Sidi Salem 21/02/2011 7CU 2.60E+02 9.00E+01 0.00E+00 0.00E+00
Sidi Salem Ave 7CU 6.60E+02 1.28E+02 0 0
Sidi Salem 26/12/2010 8CM 4.60E+03 1.10E+03 0 0.00E+00
Sidi Salem 09/01/2011 8CM 1.10E+03 3.10E+02 0 0.00E+00
Sidi Salem 27/01/2011 8CM 1.10E+03 2.10E+02 0.00E+00 0.00E+00
Sidi Salem 21/02/2011 8CM 4.80E+02 2.00E+02 0.00E+00 0.00E+00
Sidi Salem Ave 8CM 1.82E+03 4.55E+02 0 0
Sidi Salem 26/12/2010 9CD 1.80E+03 4.10E+02 0 0.00E+00
Sidi Salem 09/01/2011 9CD 4.10E+02 1.60E+02 0 0.00E+00
Sidi Salem 27/01/2011 9CD 3.20E+03 1.10E+02 0.00E+00 0.00E+00
Sidi Salem 21/02/2011 9CD 2.10E+02 1.10E+02 0.00E+00 0.00E+00
Sidi Salem Ave 9CD 1.41E+03 1.98E+02 0 0
Sidi Salem 26/12/2010 9CDD 3.70E+02 1.60E+02 0 0.00E+00
Sidi Salem 09/01/2011 9CDD 2.10E+02 1.20E+02 0 0.00E+00
Sidi Salem 27/01/2011 9CDD 1.00E+02 3.10E+02 0.00E+00 0.00E+00
Sidi Salem 21/02/2011 9CDD 1.10E+02 1.00E+02 0.00E+00 0.00E+00
Sidi Salem Ave 9CDD 1.98E+02 1.73E+02 0 0
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Table 15: Hourly Water Quality Data – El Moufty El Kobra
Total Coliforms e-Coli
Site Location Time (NRC) (NRC)
El-Moufty El-Kobra 1WW 1415 3.10E+08 4.10E+07
El-Moufty El-Kobra 1AP2 1415 4.60E+05 6.30E+04
El-Moufty El-Kobra 1WW 1515 2.60E+08 1.60E+07
El-Moufty El-Kobra 1AP2 1515 2.30E+05 4.10E+04
El-Moufty El-Kobra 1WW 1615 2.10E+08 1.80E+07
El-Moufty El-Kobra 1AP2 1615 4.10E+04 1.20E+04
El-Moufty El-Kobra 1WW 1715 6.70E+07 7.20E+06
El-Moufty El-Kobra 1AP2 1715 1.10E+04 3.20E+03
El-Moufty El-Kobra 1WW 1815 3.50E+07 2.40E+06
El-Moufty El-Kobra 1AP2 1815 2.10E+04 2.60E+03
Table 16: Hourly Water Quality Data – Sidi Salem
Total Coliforms e-Coli
Site Location Time (NRC) (NRC)
Sidi Salem 1WW 700 2.60E+08 2.10E+07
Sidi Salem 5ENC 700 1.20E+06 3.10E+04
Sidi Salem 6EC 700 1.10E+03 4.10E+02
Sidi Salem 1WW 800 4.10E+08 6.80E+07
Sidi Salem 5ENC 800 3.10E+05 1.10E+04
Sidi Salem 6EC 800 1.20E+03 1.00E+02
Sidi Salem 1WW 900 3.40E+08 4.10E+07
Sidi Salem 5ENC 900 9.80E+05 6.70E+04
Sidi Salem 6EC 900 4.40E+03 4.70E+02
Sidi Salem 1WW 1000 2.80E+07 1.10E+07
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Total Coliforms e-Coli
Site Location Time (NRC) (NRC)
Sidi Salem 5ENC 1000 1.10E+05 2.10E+04
Sidi Salem 6EC 1000 1.00E+03 1.10E+02
Sidi Salem 1WW 1100 4.10E+08 1.30E+06
Sidi Salem 5ENC 1100 2.10E+06 2.60E+04
Sidi Salem 6EC 1100 3.10E+03 4.10E+02
Sidi Salem 1WW 1200 2.10E+07 4.30E+06
Sidi Salem 5ENC 1200 1.20E+04 6.40E+03
Sidi Salem 6EC 1200 2.60E+02 1.00E+02
Sidi Salem 1WW 1300 1.10E+08 4.10E+07
Sidi Salem 5ENC 1300 7.50E+06 2.10E+05
Sidi Salem 6EC 1300 6.90E+03 3.20E+02
Sidi Salem 1WW 1400 2.60E+07 1.70E+06
Sidi Salem 5ENC 1400 1.80E+05 1.14E+02
Sidi Salem 6EC 1400 6.40E+03 1.70E+02
Sidi Salem 1WW 1500 1.80E+08 2.80E+06
Sidi Salem 5ENC 1500 2.60E+04 2.30E+03
Sidi Salem 6EC 1500 1.00E+02 9.00E+01
Sidi Salem 1WW 1600 2.30E+07 4.60E+06
Sidi Salem 5ENC 1600 4.50E+04 1.20E+04
Sidi Salem 6EC 1600 2.30E+02 1.00E+02
Sidi Salem 1WW 1700 1.60E+08 2.30E+06
Sidi Salem 5ENC 1700 3.40E+04 1.80E+03
Sidi Salem 6EC 1700 1.40E+02 9.00E+01
Sidi Salem 1WW 1800 4.20E+07 2.60E+05
Sidi Salem 5ENC 1800 3.70E+04 1.70E+03
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Total Coliforms e-Coli
Site Location Time (NRC) (NRC)
Sidi Salem 6EC 1800 1.30E+02 8.00E+01
Table 17: Water Quality Data – Trench/Bayaras
Total Coliforms e-Coli
Command Area (NRC) (NRC)
Sidi Salem 4.10E+09 1.20E+08
Sidi Salem 2.60E+08 3.10E+06
Sidi Salem 3.20E+08 4.10E+07
Sidi Salem 1.70E+08 2.10E+07
Sidi Salem 6.10E+08 1.60E+07
Sidi Salem 4.20E+07 2.10E+06
Sidi Salem 3.90E+07 2.30E+06
El-Moufty El-Kobra 4.30E+08 1.20E+00
El-Moufty El-Kobra 6.10E+08 3.10E+07
El-Moufty El-Kobra 2.80E+07 1.10E+06
El-Moufty El-Kobra 2.10E+08 4.30E+06
El-Moufty El-Kobra 6.30E+07 2.80E+06
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