COVID-19 From the Ground Up:
What the Crisis Means for Nigerians1
Findings from the
Nigeria COVID-19 National Longitudinal Phone
Survey (NLPS)
Round 1, April-May 2020
1
The Nigeria COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) 2020 baseline, on which this report
was based, was implemented by Nigeria’s National Bureau of Statistics (NBS) in April-May 2020. For more details
regarding the survey please contact Biyi Fafunmi (biyifafunmi@nigerianstat.gov.ng) and Tunde Adebisi
(tundeadebisi@nigerianstat.gov.ng). This report was prepared by Jonathan Lain, Julie Perng, Tara Vishwanath,
M Abul Kalam Azad, Gbemisola Oseni Siwatu, Amparo Palacios-Lopez, Kevin Robert McGee, Akuffo Amankwah and
Ivette Gonzalez. We are also grateful for very helpful editorial suggestions from Alexander Irwin.
1
OVERVIEW
To monitor the effects of the COVID-19 pandemic on Nigerian people and inform the policy response,
Nigeria’s National Bureau of Statistics (NBS), with support from the World Bank, has launched the
COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS). The first of 12 planned survey rounds
took place between April 20 and May 11, 2020, with a sample of 1,950 households. The following key
messages emerged:
• Nigerians displayed knowledge of the virus, prevention measures, and government action on
COVID-19. The majority of respondents understood the importance of preventive measures like
handwashing and social distancing and were aware of relevant government advisories. Behaviors such
as handwashing and avoiding gatherings were reported by over 90 percent of households.
• A large majority of Nigerians see the pandemic as a threat to their households’ health, and even
more are worried about the impact on their financial future. COVID-19 health concerns are
widespread in the sample, but fears of the pandemic’s economic effects are even more pervasive. A
little over three-quarters of respondents reported being worried about themselves or their family
members becoming seriously ill from the coronavirus, while 92 percent saw the coronavirus as a
threat to their household's finances.
• Since the coronavirus outbreak, most households have suffered economic shocks that far exceed
any faced in recent years. The most widely reported shock was a surge in the prices of major food
items, which was faced by 85 percent of households since the outbreak, compared to only 19 percent
of all households between January 2017 and January 2019.
• The pandemic has disrupted employment and income-generating activities for large numbers of
ordinary Nigerians. These impacts are risky for the majority of working Nigerians who report their
main activities to be in farming or family businesses:
o Forty-two percent of respondents who were working before the outbreak reported that they
had stopped working at the time of the survey.
o The share of respondents that stopped working was higher in urban areas than rural areas.
o The labor-force impact of COVID-19 has been largest in the commerce and service sectors.
o Non-farm enterprises (NFEs) have been particularly impacted by the COVID-19 crisis.
o Seventy-eight percent of households reported a loss in income since mid-March.
• Fifty-one percent of households surveyed reported reducing their food consumption in response to
pandemic-related economic shocks. Due to lack of money or other resources, 75 percent of
households report an adult in the household skipping a meal, while 58 percent report the household
running out of food in April/May 2020.
• The pandemic is making it harder for people to buy staple foods and access health care. Depending
on the item, between 35 percent and 59 percent of households reported difficulties in purchasing
staple foods like yams, rice, and beans in the seven days prior to the interview, mostly due to not
having money to make such purchases. In addition, a little over a quarter of households who needed
medical treatment reported not being able to access it.
• The pandemic has restricted access to education for more than a third of surveyed households with
children; this raises concerns for longer-term human capital losses. Thirty-eight percent of
households with children who attended school prior to COVID-19 school closures reported that their
children did not engage in any learning or education activities during the seven days prior to the
interview. In addition, less than 1 in 5 households reported that they had any contact with children’s
teachers.
2
INTRODUCTION
The COVID-19 pandemic and the concurrent shock to global oil prices have created an urgent need for
timely data to help monitor and mitigate the social and economic impacts of the crisis on Nigerian
households. Nigeria was among the first countries in Sub-Saharan Africa to identify COVID-19 cases and
has since implemented strict measures to contain the spread of the virus. Oil prices have also plummeted
by 60 percent since the start of 2020. Since the oil sector accounts for the bulk of Nigerian government
revenue, this price drop has profound implications for the national economy and ordinary people’s
wellbeing. The federal government must combat an unprecedented public health crisis while working to
restart a weakened economy.
To monitor how the COVID-19 pandemic is affecting the country’s economy and people, and to inform
interventions and policy responses, the National Bureau of Statistics (NBS), with support from the
World Bank, is conducting a high-frequency phone survey. The baseline for this survey – the Nigeria
COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) 2020 – which captures key social and
economic outcomes from households across Nigeria, was collected between April 20 and May 11, 2020.
The survey coincided with the federally-mandated lockdown initiated on March 30.2 The sample of 1,950
households was drawn from the regionally-representative General Household Survey Panel (GHS-Panel)
fielded in 2018-2019.3
The COVID-19 NLPS collects a wide range of information from Nigerian households at monthly intervals.
The 15-25-minute questionnaire covers such topics as knowledge of COVID-19 and mitigation measures,
access to educational activities during school closures, employment dynamics, household income and
livelihoods, income loss and coping strategies, and assistance received. These same households will be
tracked over 12 months, with selected respondents (typically the household head) completing phone-
based interviews every three to four weeks for 11 more waves. This high-frequency follow-up helps
understand the effects of and household responses to the COVID-19 pandemic in near real time,
supporting new, evidence-based policy responses. Furthermore, the questionnaire implemented each
round will be modular, retaining some key questions to track over time, but also incorporating new
questions targeted to the changing situation on the ground or policymakers’ needs.
This report extends the previous summary presented in COVID-19 Impact Monitoring: Baseline April
2020.4 The report discusses the details of the survey sample, then summarizes findings on a series of
topics: households’ knowledge of COVID-19 and their behavior in response; reported shocks; the
pandemic’s effects on employment and livelihoods; what ordinary people are doing to cope with the
pandemic’s health and economic fallout; and how COVID-19 is affecting children’s education.
2
The first COVID-19 case was recorded by the Nigeria Centre for Disease Control on February 27. On April 20, there
were 732 total confirmed cases, and by May 11, this number had grown to 4,686.
3
Drawing from this recent representative survey allows for adjustment of the sampling weights to correct for non-
response and under-coverage common to phone surveys, in order to ensure that the estimates obtained are
nationally representative.
4
Nigeria National Bureau of Statistics, The World Bank. 2020. COVID-19 impact monitoring, baseline report.
https://microdata.worldbank.org/index.php/catalog/3712/download/48362
3
CAPTURING THE DIVERSITY OF NIGERIAN VOICES: THE NLPS SAMPLE
The NLPS sample is distributed across Nigeria, covering urban and rural areas and households with
different living standards. Around 61 percent of the interviewed sample is rural, with the remainder
coming from urban areas (see Table 1).5 The average household size is 5.5 individuals, and 18 percent of
the households are female headed. The respondents, 82 percent of whom are household heads, have an
average age of a little over 46, and 52 percent have at least some senior secondary education. The bottom
consumption quintile – calculated using the post-harvest wave of the 2018/19 GHS-Panel – comprises
16 percent of the sample, while the top consumption quintile represents 23 percent of the sample.6,7
Table 1. Characteristics of respondents for the NLPS baseline
Standard
Variable Mean Minimum Maximum Sample size
deviation
Age 46.48 14.80 15 99 1949
Male 0.73 0.44 0 1 1950
Household head 0.82 0.38 0 1 1950
Rural 0.61 0.49 0 1 1950
At least some senior secondary/tertiary 0.52 0.50 0 1 1912*
Literate 0.82 0.38 0 1 1912*
Rooms per capita 0.88 0.91 0 14 1950
Note: Sampling weights are not applied to these statistics. *38 respondents who are new household members and who were
not present at the time of GHS-Panel 2018/19.
KNOWING AND DOING: WHAT PEOPLE UNDERSTAND ABOUT COVID-19
AND HOW THEY ARE TRYING TO PROTECT THEMSELVES
This and the following sections summarize key results from the NLPS baseline round.
The vast majority of respondents knew about measures to prevent the spread of COVID-19, although
some measures were better known than others. In terms of personal hygiene measures, 97 percent of
respondents reported knowing that handwashing was a measure to help reduce the risk of contracting
COVID-19, yet only 63 percent of respondents reported knowing that avoiding touching their face is also
a preventative measure (see Table 2). Knowledge of appropriate social distancing measures was high, with
about 9 in 10 respondents reporting that they knew that staying at home and avoiding going out as well
as avoiding crowded places or gatherings could help reduce the risk of contracting COVID-19. As Table 7
in the appendix shows, knowledge of preventative measures differed between urban and rural areas and
across the consumption quintiles: for example, knowledge of hand sanitizer and masks was higher in
urban areas and for richer households.
5
The sample was designed to be representative of urban and rural areas as identified in the GHS-Panel. However,
the sample is not sufficiently powered for a full urban/rural comparison across multiple dimensions. The estimates
presented in this report for urban/rural areas are thus unbiased estimates and therefore informative, but they may
lack the precision traditionally expected for a “representative” sample. The sample may be expanded in future
rounds of the survey to enable more detailed urban/rural comparison across multiple dimensions.
6
As the consumption quintiles are estimated using individual-level sampling weights, the share of households – each
of which may contain different numbers of people – in each quintile is not expected to be the same.
7
More than 98 percent of these respondents were household members in the 2018/19 GHS-Panel.
4
Most respondents reported that they were following safe practices to avoid contracting COVID-19. The
survey asked about four key self-reported behaviors, namely: (1) handwashing; (2) avoidance of
handshakes/physical greetings; (3) avoidance of groups of more than 10 people; and (4) stocking up on
more food. More than 90 percent of respondents reported following the first three behaviors, although
just 47 percent of respondents had stocked up on more food than normal. Table 2 indicates that
knowledge of preventative measures may have been correlated with the analogous behaviors.
Table 2. Knowledge and use of measures to mitigate COVID-19 risk
Knowledge of preventative Reported use of measures
measures taken since mid-March
(percentage of households) (percentage of households)
Handwashing / More frequent handwashing with soap* 97.4 95.8
Use of sanitizer 65.6
No Handshake / physical greetings 81 92.8
Use of mask 73.9
Use of gloves 56.1
Avoid travel 80.3
Staying at home and avoid going out unless necessary 88.8
Avoid crowded places or gatherings with many people /
89.9 93.5
Avoid groups of more than 10 people*
Maintain enough distance of at least 1 meter 81.9
Avoiding touching your face 63.1
None of the above reported 0.6
Stock up more food than normal due to restricted movement 46.9
Note: *Wording in knowledge and behavior sections differ slightly (wording on knowledge is listed on the left).
Knowledge of actions taken by the government was generally high. As Table 3 shows, over 93 percent
of respondents reported knowing about at least one action taken by the government to curb the spread
of coronavirus: the most commonly known were advisories to stay at home (69 percent) and to avoid
gatherings (62 percent). Poorer quintiles and rural respondents were more likely to report knowledge of
government advisories to avoid gatherings, travel restrictions, and closures of schools, universities, and
non-essential businesses.
Table 3. Knowledge of government actions to curb the spread of coronavirus
Share of households (percent)
At least one action to curb the spread of coronavirus 93.1
Advised citizens to stay at home 69.1
Advised to avoid gatherings 61.7
Restricted travel within country/area 32.1
Restricted international travel 10.4
Actions to
Closure of schools and universities 32.6
curb the
Curfew/ lockdown 42.7
spread of
Closure of non-essential businesses 31.5
coronavirus
Sensitization/ Public Awareness 35.1
Established isolation centers 7.1
Disinfection of public places 6.8
Other 7.5
None 4.2
Don't know 2.7
Note: This was an open question; the options were not read.
5
WHAT PEOPLE ARE AFRAID OF AND HOW THEY ASSESS THE GOVERNMENT
RESPONSE
The majority of respondents reported being concerned that COVID-19 could have a negative impact on
their health and financial status. About 78 percent of respondents reported being “very or somewhat
worried” about themselves or an immediate family member becoming seriously ill from coronavirus, while
92 percent reported that coronavirus is a “substantial or moderate” threat to their household's finances.
These concerns were highest for the two poorest quintiles (see Figure 1).
Figure 1. Concerns related to coronavirus
100
Share of respondents (percent)
90
80
70
60
50
40
30
20
10
0
Q1: Poorest Q2: Poorer Q3: Middle Q4: Richer Q5: Richest
Overall Consumption Quintile (2019)
Very/somewhat worried about self or immediate family becoming seriously ill from coronavirus
Coronavirus is a substantial/moderate threat to household's finance
Almost two-thirds of the sample report being satisfied with the government response to the
coronavirus crisis. Among those who are not satisfied, the main reasons are a lack of food assistance
(over 77 percent) and a lack of monetary assistance (64 percent). This seems to correspond with the
concerns about COVID-19: respondents appear to feel more worried and want more assistance related to
the economic impacts of the pandemic, rather than feeling dissatisfaction related to health policy (that is,
they are not dissatisfied with testing or medical materials).
ORDINARY PEOPLE ARE TAKING AN ECONOMIC HIT
Economic shocks have been highly prevalent since the outbreak of COVID-19. In the NLPS, only 7 percent
of households reported that they had not experienced at least one shock. The most commonly reported
shocks were increases in the price of major food items (affecting 85 percent of households) as well as
increases in the price of farming/business inputs (affecting 46 percent of households) (see Figure 2). By
contrast, the highest-reported shock in the GHS-Panel 2018/2019 round – which was also an increase in
the price of major food items consumed – affected just 19 percent of households between 2017 and early
2019.
6
Figure 2. Experience of household shocks since mid-March 2020, comparing urban and rural settings
Other (specify)
Increase in price of major food items consumed
Fall in the price of farming/business output
Increase in price of farming/business inputs
Disruption of farming, livestock, fishing activities
Theft/looting of cash and other property
Nonfarm business closure
Job loss
Illness, injury, or death of income earning HH member
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Share of respondents (percent)
Rural Urban
Households also experienced serious disruptions to economic activity, particularly non-farm business
closure (36 percent) and disruption of farming activities (29 percent). While several of the agricultural
activity shocks were common to both urban and rural areas, they were more pronounced for rural
respondents. There were severe disruptions of farming, livestock, and fishing activities, as well as
increases in the price of inputs and a fall in the prices of farming/business outputs.
THE PANDEMIC IS DESTROYING JOBS AND UNDERMINING LIVELIHOODS
The COVID-19 pandemic threatens labor and non-labor income, given its effects on demand and the
restrictions on movement and assembly: these channels are directly captured by the NLPS. The survey
asked respondents whether they had stopped working following the start of the outbreak, as well as the
reasons behind this. The survey also asked households about their income sources over the last 12 months
and whether the income from a particular source had increased or decreased since COVID-19 broke out.
Main income-generating activities in the sample
Farm and non-farm enterprises (or family businesses) are the most important income-generating
activities of Nigerian workers. In the COVID-19 NLPS, the most common main activity reported was
farming, comprising 42 percent of all workers, followed by NFEs (40 percent of workers), private-sector
wage work (12 percent of workers), and government-sector wage work (5 percent of workers). This
7
distribution of activities is similar to the one reported in the 2018/2019 GHS-Panel.8 In the 2018/19
GHS-Panel, the most common main activity reported – that is, the job in which the most hours were
worked – was farming (43 percent of all workers), followed by non-farm enterprises (38 percent of
workers), private-sector wage work (8 percent of workers), and government-sector wage work
(6 percent of workers).
The share of Nigerians who are working has almost halved since the start of the pandemic. Around
42 percent of respondents reported that they had worked prior to mid-March, but had not worked in the
last seven days; these respondents are defined as having “stopped working” (see Figure 3). A majority
(90 percent) of those who stopped working reported that the work stoppage was potentially related to
COVID-19.
Job losses are worst in cities
Urban dwellers are more likely to have stopped work due to the pandemic. Around 48 percent of urban
respondents reported stopping working for reasons potentially related to COVID-19 compared with
33 percent of rural respondents. Additionally, respondents from the poorest households (those in the
lowest consumption quintile as per the 2018/19 GHS-Panel) were most likely to stop working due to the
pandemic (45 percent), though this share was also relatively high for the wealthiest households
(39 percent).
Figure 3. Working situation of respondents by urban-rural and consumption quintiles
100
15 15 16 10 13 15 15
Share of respondents (percent)
90 19
80
70 37
33 39
60 43 47 46 43
45
50 3 9
40 4
5 9
30
20 48 45 42
38 33 33 39
32
10
0
All Rural Urban Q1: Poorest Q2: Poorer Q3: Middle Q4: Richer Q5: Richest
Stopped working (related to COVID-19) Stopped working (unrelated to COVID-19)
Currently Working Not working before outbreak
Main activities in the sample
Agriculture, buying and selling, and other services were the most prevalent activities in the NLPS
sample. As Table 4 shows, about 36 percent of those who currently work or who worked prior to mid-
March reported their main job to be in agriculture, hunting, and fishing, while 27 percent reported
being in services, and 24 percent reported being in commerce (buying, selling goods, repaid
8
Note that the determination of the main activity was calculated differently between the two surveys. In the GHS-
Panel, the team determined the main activity based on hours reported for each activity. In the NLPS, this was
calculated based on what respondents self-reported as their “main work.”
8
goods/hotels/restaurants). Industry and public administration were far less common, comprising
8 percent and 5 percent of working respondents, respectively.
Table 4. Main activity for main jobs and family businesses
Share with main job in that Share with family business
sector (percent) in that sector (percent)
Agriculture Agriculture, hunting, fishing 36 1
Mining, manufacturing 1 1
Industry Electricity, gas, water supply 1 1
Construction 6 3
Buying, selling goods, repair
Commerce 24 64
goods/hotels/restaurants
Transport, driving, post, travel agencies 7 7
Services Professional activities 2 2
Personal services 18 20
Other Public administration 5
Note: Statistics on main job focusses on those who were working at the time of the survey or prior to mid-March (1677
respondents). Statistics on family businesses focus on those with family businesses at the time of the survey or prior to mid-
March (1076 respondents).
The sectors in which NLPS respondents work differ substantially between urban and rural
respondents, as well as across different quintiles (Figure 4). Urban respondents are significantly less
likely to work in agriculture as their main activity than rural respondents (21 percent versus 43 percent)
and are more likely to work in commerce (29 percent versus 21 percent) and services (36 percent
versus 23 percent). Turning to the consumption quintiles (taken from the 2018/19 GHS-Panel),
respondents in the poorest quintile are focused more heavily in agriculture (47 percent), while
respondents in the highest quintile work mainly in services (34 percent).
Figure 4. Sector of work for respondents' main jobs (across sub-groups) in April-May 2020
100% 5% 4% 4% 2% 4%
7% 7%
Share of working respondents (percent)
90% 19%
80% 23% 19% 28% 26%
36% 34%
70%
21% 25% 29%
60% 17% 25%
50% 8% 4% 23%
29% 9% 10%
40% 9%
30% 8%
9% 47%
20% 43% 41% 40% 36%
29%
10% 21%
0%
Rural Urban Q1: Poorest Q2: Poorer Q3: Middle Q4: Richer Q5: Richest
Rural/Urban GHS Consumption Quintiles
Agriculture Industry Commerce Services Other
Non-farm enterprises are common and are concentrated in commerce and in services. A little over
half of the households (53 percent) have a family business. For these businesses, an overwhelming
share (64 percent) is concentrated in commerce while the second-highest activity for businesses is
personal services (20 percent) (see Table 4).
9
All sectors are affected, but commerce and services are suffering most
While workers in all sectors were affected by the pandemic, commerce and services were hit the
hardest (Figure 5). Of the 24 percent of working (pre-mid-March) respondents that were engaged in
commerce, 62 percent had stopped working by the time of the survey. Meanwhile, of the 27 percent
working in services, 56 percent had stopped working. By contrast, of the 36 percent of respondents in
agriculture, just 34 percent had stopped working. Note that, while 76 percent of those in other sectors
had stopped working after mid-March, the sample size is small (only 5 percent of the respondents worked
mainly in this sector).
Across all sectors except agriculture, all respondents who had stopped working reported that COVID-
19-related economic impacts were the primary cause. In agriculture, however, 24 percent of those who
had stopped working reported potentially unrelated causes for stopping work.
Figure 5. Who is still working, and who has stopped? Distribution across sectors
40
Share of respondents that are working or stopped
35
9
30
25
work (percent)
20 14
14
15
24
10
5 4 12
9
3
4
0 1
Agriculture Industry Commerce Services Other
Stopped working (for a reason potentially related to COVID-19)
Stopped working (for a reason potentially unrelated to COVID-19)
Working
These inter-sector differences in job losses are supported by further econometric analysis: job losses
appear to be more likely in commerce and services even after controlling for other respondent
characteristics. In other words, a respondent would be more likely to stop working if they are in
commerce, compared to another respondent with similar individual characteristics – such as location,
gender, and position in the consumption distribution – but who works in agriculture. Figure 6 shows the
predicted probabilities that the respondent stopped work after having worked prior to mid-March. These
results emanate from a linear regression of whether or not the respondent stopped working which
includes not only the respondents’ sector of work but also their location, gender, and consumption
quintile as control variables. Full details of this regression approach can be found in the appendix.
10
Figure 6. Predicted probability of stopping work, by activity
80
Predicted probability of job loss
70
60
50
(percent)
40
30 60 64 59
20 38
10
0
Agriculture Industry Commerce Services
Note: The graph displays the predicted probability for each sector emanating from a regression for whether a respondent
stopped working on gender, rural/urban status, sector of work, state, and quintile. Full details of this regression approach can
be found in the appendix.
Non-farm enterprises have been particularly impacted by the COVID-19 crisis. The COVID-19 NLPS
investigates impacts on family businesses by asking about how the revenue from sales in late March/April
2020 compares to the revenue in February 2020. Over 81 percent of those households with a family
business reported that their revenues are zero (23 percent) or that they were lower when compared to
revenues in February 2020 (58 percent).9 This is consistent with the evidence presented above on sectoral
differences in job losses, since almost two-thirds of the households that have a non-farm enterprise run
an enterprise engaged in commerce. When asked about the reason for these lower revenues, over
91 percent of enterprise-owning households listed reasons that were related to COVID-19.
Even though agriculture has been more insulated in terms of job losses, farming activities have clearly
been disrupted by COVID-19. Of the 68 percent of households that reported having a member who
worked on a household farm growing crops, raising livestock, or fishing since the beginning of 2020,
almost one-third reported having their activities disrupted such that they were unable to perform normal
farm tasks, since mid-March 2020. The main reason given for disruption of farm work was the advisory to
stay at home (55 percent) followed by restrictions on movement and travel (39 percent) (see Table 5).10
9
This means about 43 percent of all households had an enterprise in which revenue was either zero or lower than
in February 2020.
10
Rural respondents were significantly more likely to state that it was due to reduced availability of hired labor
(6 percent, versus 1 percent for urban), and significantly less likely to state that it was due to restrictions on
movement or travel (33 percent, versus 60 percent for urban).
11
Table 5. Main reasons for not being able to perform normal farm activities
National Urban Rural
Main reason p-value
(percent) (percent) (percent)
Advised to stay at home 54.78 49.26 56.41 0.39
Reduced availability of hired labor 4.94 1.06 6.08 0.02
Restrictions on movement/ travel 38.68 59.66 32.52 0.00
Unable to acquire/ transport inputs 2.19 1.68 2.34 0.70
Unable to sell/ transport outputs 1.36 1.47 1.33 0.90
Ill or need to care for ill family member 3.22 0.00 4.16 0.03
Other 20.64 19.56 20.96 0.83
Note: The p-value shows whether there is a statistically significant difference between the share for urban areas and the share
for rural areas.
While labor income sources were the most important income sources prior to the COVID-19 outbreak,
many households received non-labor income that is also at risk. In terms of labor income, farming was
the most prevalent income source, especially for poorer households in rural areas: 79 percent of
households reported receiving farm income, with significantly higher shares in rural versus urban
households, and in lower consumption quintiles (see Figure 7 and Table 8 in the appendix). This was
followed by NFEs (63 percent of all households), which were more concentrated among urban dwellers,
and wage-employment (30 percent of all households), which was more prevalent among richer
households. Turning to non-labor income sources, more than 1 in 5 households received remittances from
family members within the country, with the share being significantly higher for urban dwellers in richer
households. Additionally, around 14 percent of household received income from properties, investments
and savings.
Figure 7. Household income sources in the last 12 months
Share of households (percent)
0 10 20 30 40 50 60 70 80 90 100
Household farming, livestock or fishing
Non-farm family business
Wage employment of household members
Remittances from abroad
Remittances from family within the country
Assistance from other non-family individuals
Income from properties, investments, savings
All households Urban Rural
Note: The following income sources were included in the NLPS but are not reported here: “Pension”; “Assistance from
government”; “Assistance from NGOs/charitable organizations”; and “Other”.
Both labor and non-labor income sources have suffered dramatically since the outbreak of COVID-19,
yet income from wage-employment and income from properties, investments and savings fared slightly
better than other income sources. Overall, income losses have been widespread, with 78 percent of
12
households reporting a loss in income since mid-March. Income from NFEs appears to have been affected
the most, with 85 percent of those households that relied on NFE income reporting that NFE income
declined (see Figure 8 and Table 9 in the appendix). Around two-thirds of those households receiving
income from properties, investments, and savings suggested that such income sources had declined.
Figure 8. Household income changes since mid-March 2020, by different sources of income
Share of households (percent)
0 10 20 30 40 50 60 70 80 90 100
Household farming, livestock or fishing
Non-farm family business
Wage employment of household members
Remittances from abroad
Remittances from family within the country
Assistance from other non-family individuals
Income from properties, investments, savings
More Same Less
Some of the loss in income among wage workers may be due to underemployment. Given that wage
work is far rarer than work in farm or non-farm businesses, a little under 4 percent of all respondents
reported not being able to work as normal in their wage job, yet almost 21 percent of households had a
member (not necessarily the respondent) who was not able to work as normal in their wage job.
Underemployment resulted in impacts on pay for a portion of the respondents. While 46 percent of
respondents who worked less in their wage job (for COVID-related reasons) received full pay, 16 percent
received partial pay, and 37 percent received no pay.
Overall household income losses were similar across quintiles and between rural and urban
respondents, but some specific income sources were more affected for poorer, rural households. As
Table 9 in the appendix shows, rural households and those in the poorest quintiles were more affected by
income losses from farming, livestock, or fishing. By contrast, urban households and those in the richest
quintiles were more affected by income losses from wage-employment and remittances
PEOPLE ARE USING DANGEROUS COPING STRATEGIES—MANY ARE EATING
LESS FOOD
Households are turning to coping mechanisms that may have negative impacts in the medium and long
run, especially in terms of nutrition and food consumption. Indeed, around 51 percent of all households
reduced their food consumption as a coping mechanism (see Figure 9). As well as reducing their food
consumption, many households (29 percent) also appear to be drawing down their savings in response to
the crisis.
13
Figure 9. Coping mechanisms for shocks since mid-March 2020
Relied on savings
Reduced non-food consumption
Reduced food consumption
Sold harvest in advance
Credited purchases
Borrowed from friends/family
Received assistance from friends/family
Engaged in additional income-generating activity
Sale of (agric/non-agric) assets
0 10 20 30 40 50
Share of households (percent)
Not only has there been a marked change in food insecurity since the crisis, but different sub-groups of
Nigerians may be more impacted than others. In particular, all the indicators shown in Figure 10 suggest
that food insecurity is significantly higher (in both years) in urban areas. There are also differences
between richer and poorer households. For example, for the indicator capturing whether an adult in the
household went without eating for a whole day because of a lack of money or other resources, there is a
statistically significant difference across the quintiles: 35 percent of households in the first quintile
reported someone not eating for a day, versus 16 percent in the fifth quintile.
Figure 10. Food insecurity experience over time and across sub-groups
0.9
Share of households that are food insecure
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Overall: Overall: Urban Rural Q1: Poorest Q2: Poorer Q3: Middle Q4: Richer Q5: Richest
18/19 2020
Overall food security rates: 2020
Adult in HH had to skip a meal because not enough money or resources
HH ran out of food because of lack of money or other resources
Adult in HH went without eating for a whole day because of a lack of money or other resources
14
THE PANDEMIC IS COMPLICATING ACCESS TO BASIC GOODS AND
SERVICES—INCLUDING THE SUPPLIES PEOPLE NEED TO PROTECT THEIR
HEALTH
Soap, rice, and cleaning supplies were reported by households to be the most commonly needed items,
but these items were not always accessible. Specifically: of the 78 percent of households needing soap,
11 percent were not able to purchase any (in the seven days prior to the interview); of the 62 percent of
households needing rice, 50 percent were not able to purchase any; and of the 59 percent of households
needing cleaning supplies, 19 percent were unable to purchase any. Additionally, a high share of
households (34-59 percent of those that needed them, depending on the item) reported not being able
to obtain staple foods like yams, cassava, and beans when needed.
For the most part, this lack of access was due to economic concerns; households lack the income to buy
the goods they need. When asked the reasons why these basic goods could not be obtained, 78-
90 percent of those households who could not buy them said that it was because they had no money to
do so (see Table 6).11 Other less cited reasons were the local market being closed, restrictions on going
outside, and prices being too high.
Table 6. Reasons that basic goods were not available
Share of households that could not access each item reporting a particular
Reasons given that basic goods were reason (percent)
not available Cleaning
Medicine Soap Rice Beans Cassava Yams Sorghum
supplies
Out of stock 5.16 3.84 3.49 3.50 1.02 4.31 9.25 1.89
Local market closed/ not operating 9.71 16.29 13.10 9.72 9.19 11.84 8.34 9.49
Limited/no transportation 3.63 3.11 3.56 1.67 3.09 0.59 3.32 1.64
Restriction to go outside 15.20 13.58 12.13 6.22 8.12 11.05 7.31 6.72
Price too high 0.44 6.81 2.90 16.98 5.66 7.32 17.50 3.60
No money to buy 80.71 77.61 79.31 88.71 89.81 83.54 84.14 85.08
A little over a quarter of households who needed medical treatment reported not being able to access
it. A majority (over 55 percent) who could not access the treatment stated that it was due to lack of
money, and nearly a quarter (24 percent) stated that this lack of access was due to movement
restrictions.12
SAFETY NETS ARE REACHING ONLY A SMALL NUMBER OF THOSE IN NEED
As access to basic goods may continue to be limited, safety nets will be important for the welfare of
Nigerian households throughout the COVID-19 crisis. Around 14 percent of respondents in the NLPS had
11
Additionally, for all of the items, except for sorghum, the richest were the least constrained while the lowest
quintile were the most constrained in terms of purchases.
12
The NLPS also asked respondents about access to financial institutions (including automated teller machines,
banks, and money agents). A little under 40 percent of all households needed access to a financial institution in the
seven days prior to the interview; of these, more than 15 percent were unable to access a financial institution. Access
to financial institutions was lower in rural areas.
15
received assistance from an institution such as the government, international organizations, and religious
bodies in the form of food (12 percent), direct cash transfers (2 percent), and other in-kind transfers
(1 percent). The largest source of assistance was the state government, comprising around one-third of
the assistance programs, followed by religious bodies, which comprised around one-quarter of the
assistance programs.
ONE OF THE PANDEMIC’S VICTIMS IS EDUCATION
School closure prompted by the pandemic is reducing children’s opportunity to learn. Following the
outbreak of the pandemic, all schools in Nigeria were closed. More than 80 percent of all households have
children aged 5-20, and 93 percent of such households had children enrolled in school before these
closures (see Figure 11).
Figure 11. Coronavirus restrictions: effects on education in the past seven days
90
attended school before the outbreak of
Share of households with chuldren that
80
70
COVID-19 (percent)
60
50
40
30
20
10
0
Q1: Poorest Q2: Poorer Q3: Middle Q4: Richer Q5: Richest
Overall Consumption Quintile (2019)
Did not engage in any learning/education activities Did not have contact with teachers
A little under 40 percent of households with children who attended school prior to school closures
reported that their children were not engaging in any learning or education activities. Disengagement
from learning activities appears to have been spread more widely in poorer households than in richer
households. The main learning activities, for those who engaged, included studying or reading on their
own (67 percent), being taught by parents or other household members (56 percent), and listening to
educational radio programs (21 percent). Finally, only a little over 19 percent of households reported that
they had any contact with children’s teachers in the seven days prior to the interview. For these
households, the primary means of contact were telephone (60 percent) and household visits by the
teacher (38 percent).
16
KEY TAKE-AWAYS FOR POLICY
• The pandemic’s employment impacts have been large, affecting non-farm enterprises and those
working in the commerce and service sectors the most. As many as 42 percent of respondents
who were working before the outbreak reported that they were not working at the time of the
survey.
• Compromised livelihoods and especially reduced food consumption in many households call for
urgent action. Safety nets and other economic and health policies are needed to address these
shortfalls. Currently, only 14 percent of survey respondents are receiving support from social
safety net programs.
• Risks to human capital development are further compromised due to school closures. Many
young people are either self-learning or being homeschooled, and over one-third currently have
no educational activities at all. As the country transitions to the next phases of pandemic response
and recovery, these interruptions to learning will need to be addressed with policies to mitigate
the harmful medium- and long-run impacts.
• Knowledge of the pandemic is correlated with behavior change. The COVID-19 NLPS analysis can
inform future public-health communications campaigns. Recognizing gaps in current
understanding of the pandemic will help define outreach priorities and target information to the
groups that need it most.
• The second round of the NLPS was completed in June 2020 and is expected to provide further
insights. Forthcoming Round 2 results will provide more information on the impacts of COVID-19
on employment and livelihoods, food security and access to basic goods, human development,
and many other issues.
17
APPENDIX
Supplementary tables
Table 7. Knowledge of measures to mitigate COVID-19 risk, by sub-groups
Share of households with knowledge of each measure (percent)
Mitigation measures
Overall Urban Rural Q1 Q2 Q3 Q4 Q5
Handwashing 97.4 98.1 97.0 97.1 98.4 97.1 97.8 96.9
Use of sanitizer 65.6 76.5 60.5 49.3 68.8 57.1 66.1 74.0
No Handshake / physical greetings 81.0 80.1 81.5 79.1 85.1 83.4 84.3 76.4
Use of mask 73.9 79.4 71.4 62.0 77.4 71.6 75.3 76.8
Use of gloves 56.1 60.7 54.0 45.2 59.5 55.4 55.7 59.2
Avoid travel 80.3 78.7 81.0 82.4 85.1 78.4 84.0 75.9
Staying at home and avoid going out unless necessary 88.8 89.0 88.8 94.5 90.5 87.8 93.8 83.3
Avoid crowded places or gatherings with many people 89.9 87.6 90.9 93.0 90.4 92.5 89.9 87.2
Maintain enough distance of at least 1 meter 81.9 86.0 80.1 73.9 80.6 81.6 85.2 83.3
Avoiding touching your face 63.1 60.6 64.2 66.5 69.3 61.3 61.5 61.3
None of the above reported 0.6 0.8 0.6 0.9 1.2 1.8 0.1 0.1
Table 8. Household income sources in the last 12 months, by sub-groups
Share of households with each income source (percent)
Income sources
Overall Urban Rural Q1 Q2 Q3 Q4 Q5
Household farming, livestock or fishing 78.5 55.5 89.2 89.7 94.4 89.6 72.4 66.1
Non-farm family business 63.0 67.9 60.7 68.5 60.9 65.2 62.9 60.9
Wage employment of household members 29.8 33.1 28.2 21.4 23.7 25.5 29.1 38.0
Remittances from abroad 3.4 5.6 2.4 0.1 1.2 2.4 1.6 7.3
Remittances from family within the country 21.8 28.0 18.9 12.2 19.1 20.7 21.4 27.2
Assistance from other non-family individuals 21.6 23.2 20.9 20.2 28.1 21.3 19.5 21.0
Income from properties, investments, savings 14.4 13.0 15.0 7.3 20.1 16.7 10.1 16.2
Pension 4.1 7.2 2.7 0.8 1.4 2.6 2.8 8.2
Assistance from the Government 3.3 1.7 4.0 3.4 3.2 5.7 4.3 1.3
Assistance from NGOs / charitable orgs 2.8 2.9 2.8 2.1 7.4 2.3 1.8 2.1
Other 0.6 1.1 0.3 0.0 0.5 0.8 0.9 0.4
18
Table 9. Household income losses since mid-March, by sub-groups
Share of households that had each income source experiencing a loss
Income sources in that income source (percent)
Overall Urban Rural Q1 Q2 Q3 Q4 Q5
Household farming, livestock or fishing 72.6 70.7 73.1 72.6 71.8 81.6 74.3 65.2
Non-farm family business 84.6 85.1 84.3 76.2 86 87.5 86.3 84.4
Wage employment of household members 57.9 55.9 59 50.5 60.3 68.6 64.2 51.6
Remittances from abroad 60.0 54.4 66.2 100 22.5 36.6 78.3 63.8
Remittances from family within the country 71.7 72.6 71.1 60.5 74.8 67.9 74.3 72.7
Assistance from other non-family individuals 78.0 81.2 76.3 87.1 75.9 86.9 71.1 75.7
Income from properties, investments, savings 65.5 45.6 73.5 39 71.9 71.1 71.5 60.6
Pension 15.1 4.5 28.3 0 13.2 63.4 14 7.8
Assistance from the Government 56.7 68.3 54.5 71.6 49.5 62.8 40.8 72.8
Assistance from NGOs / charitable orgs 67.3 56.3 72.6
Other 81.1 88.9 68.4
Overall income 78.4 78.3 78.4 76.2 79.7 81.7 79.8 75.9
19
Regression model for the drivers of stopping work
In order to calculate the likelihood that workers in each sector stopped working, a simple linear regression
was estimated, in which the dependent variable was a dummy variable for whether those respondents
who had been working prior to the COVID-19 outbreak had stopped working at the time of the survey
(see Table 10). Since the dependent variable is binary, this is a linear probability model: the coefficients
can be read directly as marginal effects and, by clustering at the enumeration area level, the standard
errors have been corrected for heteroskedasticity. As well as the sector of work in which in the individual
engaged, the regression also controls for the gender, location, and consumption quintile of each
respondent, as well as state fixed effects.
Table 10. Linear regression results showing the drivers of stopping work
Dependent variable: dummy variable for whether
respondent stopped working
Male 5.47
(4.17)
Rural -15.03***
(3.88)
Q1: Poorest 12.76**
(6.14)
Q2: Poorer -1.33
(7.80)
Q3: Middle 4.62
(4.75)
Q4: Richer -3.51
(4.48)
Industry 12.54*
(6.88)
Commerce 20.89***
(5.14)
Services 15.07***
(4.57)
Constant 34.06***
(7.27)
Observations 1,581
R-squared 0.135
Note: Standard errors, clustered at the enumeration area level, in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Sample
restricted to those respondents who were working prior to the COVID19 outbreak. Regression includes state fixed effects, but
these are not reported. Quintile 5 is the omitted category for the quintile variable. Agriculture is the omitted category for the
sector variable. An alternative specification, in which dummy variables for the 9 employment sectors were included, produces
qualitatively similar results.
20