STRATEGY SUPPORT PROGRAM | WORKING PAPER 148 JULY 2020

Food and nutrition security in Addis

Ababa, Ethiopia during COVID-19
pandemic
July 2020 report

Alan de Brauw, Kalle Hirvonen, and Gashaw T. Abate

CONTENTS
Abstract ..........................................................................................................................................iv
1. Introduction ............................................................................................................................... 5
2. Context ..................................................................................................................................... 6
2.1. Addis Ababa ...................................................................................................................... 6
2.2. COVID-19 policy measures in Ethiopia.............................................................................. 6
3. Data .......................................................................................................................................... 7
3.1. February 2020 survey ....................................................................................................... 7
3.2. Phone survey in early May 2020 ....................................................................................... 7
3.3. Phone survey of early June 2020 ...................................................................................... 8
3.4. Phone survey of early July 2020........................................................................................ 8
4. Knowledge and behaviorial responses to COVID-19 ................................................................. 8
5. Income sources and changes.................................................................................................. 12
5.1. Income sources before the COVID-19 crisis .................................................................... 12
5.2. Income sources and changes in employment status during the COVID-19 pandemic ..... 12
5.3. Changes in income levels and coping during the COVID-19 pandemic ........................... 13
6. Food and nutrition security ...................................................................................................... 15
7. Conclusions ............................................................................................................................ 20
References ................................................................................................................................... 21
Appendices ................................................................................................................................... 24
Appendix A: Sampling approach ............................................................................................. 24
Appendix B: Comparing characteristics of survey households from the January and February
2020 survey sample that were and were not included in the May 2020 phone survey ....... 25
Appendix C: Disaggregation of July 2020 survey results by household wealth quintile ............ 26

TABLES
Table 1. Use of public transportation, face masks, and protective gloves, and attendance at
religious gatherings in the past seven days, percent of respondents ......................................... 9
Table 2. Households responding positively to Food Insecurity Experience Scale questions, by
household wealth quintile, percent .......................................................................................... 17
Table 3. Households consuming from each Household Dietary Diversity Score food group, by
survey round, percent.............................................................................................................. 18
Table 4. Mean number of days households consume from the Food Consumption Score food
groups, by survey round .......................................................................................................... 19
Table A1. Basic household characteristics, January and February 2020 survey ........................... 24
Table A2. Comparing pre-pandemic household characteristics between households from the
January and February 2020 survey sample that were and were not included in the May 2020
phone survey .......................................................................................................................... 25
Table A3. Coping mechanisms used by the households in the past 30 days, by wealth quintile,
percent .................................................................................................................................... 26
Table A4. Households consuming from each Household Dietary Diversity Score food group over
the past seven days, by wealth quintile, percent...................................................................... 26
Table A5. Mean number of days over the past seven that households reported consuming from the
Food Consumption Score food groups, by household wealth quintile ...................................... 26

ii
FIGURES
Figure 1. Percent of respondents who did not leave their home in the previous seven days, by
asset quintile and survey round ................................................................................................. 9
Figure 2. Foods that respondents are avoiding because of COVID-19 risk ................................... 10
Figure 3. Aspect of COVID-19 crisis that respondents reported as having the greatest impact on
their household, by survey round ............................................................................................ 10
Figure 4. Self-reported stress level, by survey round .................................................................... 11
Figure 5. Self-reported stress level, by household wealth and survey round ................................. 11
Figure 6. Household income sources in the past 12 months, by sex of household head and sex of
person responsible for the income generating activity ............................................................. 12
Figure 7. Contrasting household income sources in 2019 and in June 2020 ................................. 13
Figure 8. Surveyed households receiving cash or in-kind support in the past four weeks, by source
................................................................................................................................................ 13
Figure 9. Change in income levels in this month compared to usual incomes ............................... 14
Figure 10. Change in income levels in this month compared to usual incomes, by household wealth
quintile .................................................................................................................................... 14
Figure 11. Coping mechanisms used by the households in the past 30 days ................................ 15
Figure 12. Duration of how long household estimate they can meet their foods needs with current
savings .................................................................................................................................... 16
Figure 13. Do you think that the income your household will receive in the next 30 days will be
enough to cover the household’s food needs over the next 30 days?...................................... 16
Figure 14. Household food security status, by survey round ......................................................... 17
Figure 15. Household wealth and Household Dietary Diversity Score ........................................... 19
Figure 16. Household wealth and Food Consumption Score ......................................................... 20

iii
ABSTRACT
In early July 2020, we called by telephone a representative sample of nearly 600 households in
Addis Ababa, Ethiopia to assess income changes and household food and nutrition security status
during the COVID-19 pandemic (recall period covering June). This was the third administration of a
COVID-19 related survey to these households, following surveys in early May 2020 and early
June. About 64 percent of the households indicated in the third survey that their incomes were
lower than expected (down from 67 percent reporting lower incomes than expected in previous
month) and 42 percent reported that they are extremely stressed about the situation (down from
45 percent in previous month). Using a pre-pandemic wealth index, we find that less-wealthy
households were considerably more likely to report income losses and high stress levels than were
wealthier households. Compared to the period just before the pandemic (January and February
2020), indicators measuring food security have significantly worsened but during the pandemic
they have remained relatively stable. Households now are less frequently consuming relatively
more expensive but nutritionally richer foods, such as fruit and dairy products. However, overall
food security status in Addis Ababa is not yet alarming and we see small signs of improvements in
this July phone survey relative to previous months. However, many households have drawn down
their savings over past months to buffer their food consumption. As the daily COVID-19 infection
rates are still rising in Ethiopia, the food security situation in Addis Ababa may deteriorate over
coming months, especially as the savings levels among the poorest households are now low. This
calls for a further scale-up and strengthening of existing support programs.

JEL-codes: O12; O15; I12; I18.

Keywords: COVID-19; Ethiopia; Africa; Food security; Nutrition

iv
1. INTRODUCTION
In December 2019, the world was alerted to a sudden pneumonia outbreak in the city of Wuhan in
China (Lu, Stratton, & Tang 2020). This outbreak was later attributed to a severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) that causes the Coronavirus disease 2019, or COVID-19.
COVID-19 is a highly infectious disease that can lead to a severe, and sometimes fatal, respiratory
disease (Chen et al. 2020). The COVID-19 outbreak in Wuhan caused more than 3,800 deaths
(BBC 2020). Between January and March 2020, the virus spread internationally, which led the
World Health Organization (WHO) to declare the COVID-19 outbreak as a pandemic on 11 March
2020 (WHO 2020b). By 9 June, there were more than 13 million confirmed cases and at least
570,000 people had lost their lives to the disease (WHO 2020a).
The first COVID-19 case was confirmed in Ethiopia on 13 March. The Ministry of Health
immediately began contact tracing and isolating those who tested positive for the virus. Three days
later, the government closed schools, banned all public gatherings and sporting activities, and
recommended social distancing. Other measures to prevent the spread of the virus soon followed.
Travelers from abroad were put into a 14-day mandatory quarantine, bars were closed until further
notice, and travel through land borders was prohibited. Several regional governments imposed
restrictions on public transportation and other vehicle movement between cities and rural areas.
The purpose of these social distancing measures is to minimize the spread of the virus and to
make sure that the health care systems do not become overwhelmed with COVID-19 patients. So
far, Ethiopia has managed to keep the COVID-19 infection rates relatively low, suggesting the swift
action taken by the government has worked. By 28 June, more than 150,000 laboratory tests had
been conducted out of which only 5,689 were positive (less than 4 percent) (MoH & EPHI 2020).
The overwhelming majority of positive tests have been in the capital, Addis Ababa. By 28 June,
there had been 98 deaths in Ethiopia attributed to the virus.
While social distancing measures can be effective in slowing the spread of the virus, they come
with significant economic costs. In low- and middle-income countries, the economic concern is
different from high income countries, as many adults are self-employed or work in the informal
sector with limited savings and access to safety nets (Barnett-Howell & Mobarak 2020). Thus,
many poor households face a concrete trade-off between hunger and risking exposure to the virus
(Ravallion 2020). Adhering to recommended social distancing measures may also be difficult in low
income country settings due to inadequate access to basic health infrastructure and limited savings
(Baye 2020; Jones, Egger, & Santos 2020).
To gain an understanding of the implications of the COVID 19 crisis on household incomes and
food security, the International Food Policy Research Institute (IFPRI) is conducting a series of
phone surveys across Ethiopia. This paper is a part of a series tracking food and nutrition security
in Addis Ababa. The first two phone surveys were conducted in early May 2020 and in early June
2020, and the findings were reported in Hirvonen, Abate, and de Brauw (2020) and Abate, de
Brauw and Hirvonen (2020), respectively. In this paper, we report our findings from the third Addis
Ababa phone survey conducted at the beginning of July 2020. While households in the capital are
better off on average than households in rural and other urban areas of Ethiopia, the virus is likely
to spread faster in the capital because of the higher population density. Measures to contain the
virus will also have stronger effects on urban residents since their livelihoods are more likely to be
in sectors that are more adversely affected by social distancing policies and travel bans
(Bundervoet & Finn 2020). Moreover, possible disruptions to food value chains (Tamru, Hirvonen,
& Minten 2020; Tesfaye, Habte, & Minten 2020) are also more detrimental to urban households
because they typically do not grow their own food.

5
 IFPRI is monitoring the food security situation in Addis Ababa during the pandemic through a
series of household phone interviews. This research reports the findings after the third phone
survey round. We begin by describing the context of Addis Ababa and the social distancing policy
measures taken by the government. Section 3 describes the data. Section 4 focuses on
households' knowledge and behavioral responses to COVID-19. In Section 5, we describe
household income sources and report how they have changed over the month of June since the
second phone survey was done. Section 6 reports on different indicators of food and nutrition
security. In Section 7, we offer some concluding thoughts.

2. CONTEXT
2.1. Addis Ababa
In 2016, the estimated population of Addis Ababa was 3.8 million (CSA 2018b) out of which
16.8 percent had levels of consumption below the official poverty line (CSA 2018a). Virtually all
households have access to electricity, more than 90 percent are connected to piped water, and
more than half have access to improved sanitation (World Bank 2020). About 44 percent of
households in Addis Ababa are headed by women. The average household size is four members
(CSA 2018b).
Data from the 2016 Demographic and Health Survey show a co-existence of under- and over-
nutrition in Addis Ababa (CSA & ICF 2016). Nearly 15 percent of children under five years of age in
the city are chronically undernourished (stunted; short for their age). Meanwhile, 13 percent of
women and 18 percent of men between the ages of 15 and 49 years are thin with a body-mass
index (BMI) of less than 18.5 kg/m2, even as 29 percent of women and 20 percent of men are
overweight or obese with a BMI above 25 kg/m2.
According to the 2018 Urban Employment Unemployment Survey of the Central Statistical
Agency (CSA), 20 percent of the working age population in Addis Ababa are unemployed (CSA
2018b). Out of the employed population, 30 percent are self-employed (CSA 2018b). In terms of
sector of employment, 20 percent work in wholesale and retail trade, 13 percent in manufacturing,
8 percent in construction, and 5 percent in accommodation and food service activities (CSA
2018b). About 10 percent work for other households as, for example, servants or guards (CSA
2018b). Nearly 9 percent of the working age population in Addis Ababa work in the informal sector
(CSA 2018b). 1

2.2. COVID-19 policy measures in Ethiopia

The first policy measures to limit the spread of the virus in Ethiopia were declared on 16 March,
just three days after the first confirmed case. The government of Ethiopia closed schools, banned
all public gatherings and sporting activities, and encouraged physical distancing. Travelers from
abroad were put into a 14-day mandatory quarantine, bars were closed until further notice, and
travel through land borders was prohibited. Several regional governments imposed restrictions on
public transportation and other vehicle movement between cities and rural areas.
The federal level State of Emergency was declared on 8 April. Land borders were closed,
except for cargo. Face masks became compulsory in public spaces. Restrictions on cross-country
public transportation and city transportation were also declared. Moreover, the government
prohibited employers from laying off their workers or landlords from evicting their tenants or

1
CSA (2018b): "persons who work in an enterprise or business that did not keep book of account, who did not have license and mainly
produced for the market were considered to be working in the informal sector".

6
increasing rents during the State of Emergency. Some administrative regions have taken even
stricter measures by closing restaurants and limiting movement between rural and urban areas.
The main social protection response to COVID-19 in urban areas of Ethiopia has come through
the Urban Productive Safety Net Programme (UPSNP). Launched in 2017 and jointly funded by
the Government of Ethiopia and the World Bank, UPSNP provides monthly cash transfers against
labor-intensive public works that build community assets. Eligible households with limited labor
capacity receive unconditional cash transfers. Household level targeting takes place at the
community level. In Addis Ababa, UPSNP is targeted at the poorest 18 percent of households
(Abebe, Franklin, & Mejia-Mantilla 2018). Due to the pandemic, the public works requirement was
waived and thus all beneficiaries now are receiving unconditional cash transfers. Beneficiaries
received three months of payments in advance (Gentilini, Almenfi, & Dale 2020). The Addis Ababa
city administration has also established more than 1,000 food banks to support the most affected
households (Ethiopian Press Agency 2020).

3. DATA
3.1. February 2020 survey
Our COVID-19 telephone surveys in Addis Ababa build on an earlier IFPRI-led randomized
controlled trial that tested the effectiveness of video-based behavioral change communication to
increase fruit and vegetable consumption in the city (Abate, Baye, de Brauw, & Hirvonen 2019).
The baseline (or pre-intervention) survey for this project was administered in September and
October 2019 with an endline (or post-intervention) survey in January and February 2020 –
approximately one month before the first confirmed COVID-19 cases in Ethiopia.
In designing these surveys, we adopted a stratified random sampling approach based on
household welfare levels to ensure a balanced sample between wealthy and less wealthy
neighborhoods and between poor and rich households (see Appendix A for more details). The
baseline survey was administered between September and October in 2019 and covered 930
households. The endline survey took place between January and February 2020, and 895
households were interviewed, or 96 percent of the baseline sample. The January and February
2020 survey instrument collected detailed information about household demographics, income
sources, asset levels, food consumption, and food security.

3.2. Phone survey in early May 2020

To understand how the COVID-19 crisis is affecting households in Addis Ababa, this study reports
on the findings of the third of a series of phone surveys. The first survey was administered between
1 and 7 May 2020. The phone survey uses phone numbers for members of the sample for the
survey conducted in January and February 2020. Phone numbers were collected from 99 percent
(887 households) of the 895 sample households. Out of these households, we drew a sub-sample
of 600 households to be included in the phone survey. 2
The phone survey instrument focused on questions about household food purchase patterns,
food and nutrition security, and changes in income sources and levels. We also asked about
household knowledge and their behavioral responses to COVID-19. All interviews were conducted
via phone using structured electronic questionnaires. A verbal informed consent was obtained from
all participants.

2
Ethical approval for the phone survey was obtained from the Institutional Review Board of IFPRI. The project to promote fruit and
vegetable intake in urban Ethiopia and the COVID-19 follow-up phone surveys are all funded by the Food Systems for Healthier Diets
flagship of the CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), which is managed by IFPRI.

7
 To minimize the risk of response bias (Dabalen et al. 2016; Lau et al. 2019), we used sample
stratification and a replacement technique. We first split the sample into deciles according to
household asset holdings, and then randomly selected 60 households from each decile (600
households in total). 3 If the enumerators were unable to reach a selected household after five
attempts, it was replaced with another randomly selected household in the same asset decile.
Because some households could not be reached in the initial sample, they were replaced with
another randomly selected household in the same decile.

3.3. Phone survey of early June 2020

The second phone survey round took place between 30 May and 5 June 2020. The survey
team attempted to reach all 600 households that were called in early May during the first
COVID-19 phone survey. Out of the 600 households, 589 households were interviewed during the
second round, resulting in an attrition rate of less than 2 percent. 4 One household had relocated to
another urban area, the remaining households were still located in Addis Ababa.

3.4. Phone survey of early July 2020

The third phone survey round was administered between 27 June and 4 July 2020. Out of the
600 households interviewed in May, 584 households were interviewed during the third round,
resulting in an attrition rate of less than 3 percent. 5 As in the June survey, all but one household
was still located in Addis Ababa. 6 The third phone survey coincided with an Orthodox fasting
period, during which Orthodox households (81 percent of our sample) follow a vegan diet and
refrain from consuming animal source foods (meat, eggs, and dairy). This is likely to influence our
food security indicators based on household dietary diversity.

4. KNOWLEDGE AND BEHAVIORIAL RESPONSES TO

COVID-19
In our first phone survey in May, practically all respondents had heard about the Coronavirus or
COVID-19 and adherence to the recommended virus prevention practices was relatively high.
In early July, 25 percent of the respondents reported that they had not left the house in the past
seven days, down from 34 percent in early June. This drop is mainly driven by respondents in the
poorest households (Figure 1). In June, nearly half of the respondents in the poorest households
did not leave their house in the seven days prior to the interview. In July, slightly less than 30
percent of the respondents in the poorest households reported to have stayed home.
Out of the 386 respondents that reported leaving the house, 36 percent said that they used public
transportation (Table 1). Virtually all respondents (99 percent) said that they wore facemasks and
9 percent protective gloves. Out of all respondents, 36 percent reported to have attended a
religious gathering in the past seven days.

3
Using the information from the February 2020 survey, the asset index was constructed using a principal components analysis method.
4
Out of the 11 households that were not interviewed in this round, three refused to take part in the survey and eight could not be
reached despite multiple attempts.
5
Out of the 16 households that were not interviewed in this round, 10 refused to take part in the survey and six could not be reached
despite multiple attempts.
6
The one household that relocated was kept in the analytical sample.

8
Figure 1. Percent of respondents who did not leave their home in the previous seven days,
by asset quintile and survey round

Source: Own calculation from Addis Ababa COVID-19 phone surveys in June & July 2020. Observations = 584 households.
Note: The wealth quintiles are constructed using a principal components method based on household asset ownership using data
collected in the January and February 2020 Addis Ababa food consumption survey.

Table 1. Use of public transportation, face masks, and protective gloves, and attendance at
religious gatherings in the past seven days, percent of respondents

All By wealth quintile

households Poorest Poorer Middle Richer Richest
Last time left house in the past seven days (N=386):
Used public transportation 36 23 44 39 45 28
Wore a face mask 99 99 97 100 98 100
Wore protective gloves 9 13 5 7 1 18
In the past seven days (N=584):
Attended a religious gathering 36 12 36 53 46 33
Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.

At the time of the first COVID-19 infections in Addis Ababa, there were rumors circulating that
the virus was spreading through certain food items. While these rumors or views are not supported
by scientific evidence, we wanted to understand how widespread practices related to these rumors
are. As in the previous survey round, responses to these questions reveal that households are
mostly avoiding unprocessed dairy, as well as uncooked meat and vegetables. 7 Nearly 9 percent
(down from 14 percent in June survey), while 3 percent reported avoiding fruit (down from
8 percent in June survey).

7
Raw meat is a local delicacy in many parts of Ethiopia.

9
Figure 2. Foods that respondents are avoiding because of COVID-19 risk

Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.

In early May, we asked the respondents which aspect of the COVID-19 crisis has had the
greatest impact on their household. The most commonly cited aspects were unemployment or loss
of income (33 percent), social distancing (16 percent), shortages or high costs of food (18 percent),
getting sick (10 percent), or fear of dying (8 percent). Figure 3 summarizes the responses to the
same question in early July. This time, 37 percent of households reported that unemployment or
loss of income was the main aspect of the crisis adversely affecting their household, while
21 percent cited social distancing and 20 percent getting sick. Interestingly, none of the
respondents in July reported that the crisis aspect with greatest impact was shortages or high
costs of food. The breakdown of the responses to this question in the June survey was very similar
to what was observed in July.

Figure 3. Aspect of COVID-19 crisis that respondents reported as having the greatest
impact on their household, by survey round

Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.

We asked respondents about their overall stress level at the time of the interview using a 0 to
10 scale where 1 indicated that the respondent was not stressed at all and 10 that the respondent
was extremely stressed. In early May, 35 percent of the respondents reported that they were

10
extremely stressed, while 11 percent responded that they were not stressed at all. In early June,
45 percent reported to be extremely stressed and only 4 percent reported that they were not
stressed at all. In July, 42 percent were extremely stressed and 5.5 percent were not stressed at all
(Figure 4). Figure 5 shows how the mean stress levels decreases with households' pre-pandemic
asset levels. Since early June, stress levels have decreased for all wealth groups, except for the
wealthiest households.

Figure 4. Self-reported stress level, by survey round

Source: Own calculation from Addis Ababa COVID-19 phone survey in May, June, and July 2020 – May (N=600 households),
June (N=589), July (N = 584).

Figure 5. Self-reported stress level, by household wealth and survey round

Source: Own calculation from Addis Ababa COVID-19 phone survey in June & July 2020. Observations = 584 households.
Note: Local polynomial regression. The shaded areas represent 95 % confidence intervals. The wealth index (vertical axis) is
constructed using a principal components method based on household asset ownership using data collected in the January and
February 2020 Addis Ababa food consumption survey. The wealth index has been scaled to 0-10.

11
5. INCOME SOURCES AND CHANGES
5.1. Income sources before the COVID-19 crisis
The survey instrument fielded in January and February 2020 included questions about households'
income sources over the previous 12 months. The median household in our phone survey sub-
sample received income from two different sources in the previous 12 months. More than
85 percent of the income sources provided income in each month, indicating little seasonality in
income sources. Figure 6 shows the percent of female- and male-headed households reporting
different income sources. Before the pandemic started, nearly 60 percent of households received
wage income, while about one-third received rental income. Business income was reported by
about 18 percent of the households and income from assistance programs was received by close
to 20 percent of the households. Female-headed households were more likely to receive income
from income assistance programs, pensions, and remittances than were male-headed households.

Figure 6. Household income sources in the past 12 months, by sex of household head and
sex of person responsible for the income generating activity
Female-headed households Male-headed households

Source: Own calculation from January and February 2020 Addis Ababa food consumption survey. Observations = 600 households.
Note: Sample restricted to households that were interviewed in the May 2020 phone survey.

We also asked who in the household was mainly responsible for each income source.
Disaggregating these data by sex, we see that in male-headed households, men are largely in
charge of generating wage and business income and are more likely to receive a pension. The
situation is more balanced when it comes to income from rent, trading, remittances, and income
assistance programs.

5.2. Income sources and changes in employment status during the

COVID-19 pandemic
Figure 7 compares income sources in 2019 to those reported in our June 2020 survey based on a
one-month recall. Compared to the responses given in the January and February survey that were
based on 12-month recall that covered 2019, we see that households were considerably less likely
to report receiving income from business activities and assistance programs in the July survey
(recall period covering June 2020). In this survey round, we also see a drop in the share of
households reporting income from remittances from abroad. In contrast, the share of households
reporting income from pensions, remittances from domestic sources (especially from Addis
Ababa), and trading activities were mentioned by a greater share of respondents in the July
survey.

12
Figure 7. Contrasting household income sources in 2019 and in June 2020

Source: Own calculation from January and February 2020 Addis Ababa food consumption survey and from Addis Ababa COVID-19
phone survey in July 2020. Observations = 584 households.
Note: "Jan-Dec 2019" refers to the 12-month recall responses given in January and February 2020. "June 2020" refers to one-month
recall responses given in July 2020. Sample restricted to households that were interviewed in July 2020 phone survey.

The lower share of households reporting income from assistance programs for May could be
due to the three-month advance payment under UPSNP, which occurred at the onset of the
pandemic. Our June survey revealed that about 31 percent of households in our sample reported
receiving support from UPSNP since January 2020. Figure 8 shows the percent of households that
had received support in the four-week period before the July interview from different support
programs or activities. Nearly 20 percent reported having received an UPSNP transfer, 9 percent
received support from their community, 4.5 percent from Food Banks and 1.5 percent from NGOs.

Figure 8. Surveyed households receiving cash or in-kind support in the past four weeks, by
source

Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.

5.3. Changes in income levels and coping during the COVID-19 pandemic
We asked our phone survey respondents to compare incomes they received in the last month to
the incomes they usually receive at this time of the year. In the early May survey round, 58 percent

13
of respondents said that the incomes in the past month (i.e., in April) were lower or much lower
than usual. In the second phone survey in early June, this number had increased to 67 percent. In
July, we observe a slight improvement. In the third survey in early July, 64 percent of respondents
reported their incomes were lower in the past month than usual (Figure 9). We then used an asset-
based quintile ranking to assess how these responses varied between wealthy and less wealthy
households. As in previous survey rounds (Hirvonen et al. 2020; Abate et al. 2020), we find that
poorer households are considerably more likely to report income losses than richer households
(Figure 10).

Figure 9. Change in income levels in this month compared to usual incomes

Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.

Figure 10. Change in income levels in this month compared to usual incomes, by household
wealth quintile

Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.

When households reported income losses, we asked whose income was mostly affected. In
female-headed households, in 72 percent of the cases the most affected was the income of a
female household member. In male-headed households, 34 percent responded that the main effect

14
was on a female household members' income, while 66 percent reported it was on a male
household member.

Figure 11. Coping mechanisms used by the households in the past 30 days

Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.

As in the previous survey round, we asked all households – irrespective of whether they
reported income losses or not – about the type of coping mechanisms they used in the past 30
days (Figure 11). Nearly 65 percent of households reported to have used their savings (down from
75 percent in the June survey). Meanwhile, 66 percent reduced non-food consumption (down from
72 percent), while 49 percent reduced food consumption (down from 55 percent). The other coping
mechanisms were relatively less frequently used. 8 Poorer households were more likely to reduce
food and non-food expenditures than richer households (Table A3 in Appendix C).

6. FOOD AND NUTRITION SECURITY

The phone survey instrument had a series of questions about household food security, some of
which also appeared in the pre-pandemic instrument administered in January and February 2020.
First, we asked respondents to estimate how long they can meet their food needs with current
savings. In the first phone survey conducted in early May, 15 percent of households responded
less than a week, while in the survey round of early June this share had increased to 22 percent. In
early July, 15 percent of households responded less than a week, indicating some improvement
since our previous phone survey (Figure 12).
We also asked households to anticipate their income streams over the next 30 days and
contrast those incomes to the cost of their foods needs over the same period (Figure 13). One-third
of households were certain that their incomes will be sufficient to cover household food needs over
the next 30 days (up from 31 percent in the June survey). The rest were either unsure (31 percent)
or quite certain that their incomes will be less than the amount of money needed for food
(35 percent).

8
Note that these coping mechanism percentages are not comparable to those reported in Hirvonen, Abate, and de Brauw (2020). In
May, we focused on the primary coping mechanism employed and only asked households that reported income losses. In June, we had
questions about each coping mechanism type and asked whether the household had resorted to the coping mechanism in the past 30
days. Moreover, we asked these questions to all households, irrespective whether they reported income losses or not.

15
Figure 12. Duration of how long household estimate they can meet their foods needs with
current savings

Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.

Figure 13. Do you think that the income your household will receive in the next 30 days will
be enough to cover the household’s food needs over the next 30 days?

Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.

Second, we administered the Food Insecurity Experience Scale (FIES) module (Ballard,
Kepple, & Cafiero 2013) that asks about household's access to food in the past four weeks. Table
2 lists the questions and the percent of households responding positively to each question. The
severity of food insecurity increases as one moves down the list of questions, which explains why
the percent of households responding positively to the question decreases. A positive answer to
the last two questions capture insufficient food quantity and are indicators of severe food insecurity
(hunger) (Ballard et al. 2013).
Compared to the early June round (recall period covering May), we see that households are
less likely to respond positively to each question in the early July round (recall period of June),
indicating a slight improvement in the food security situation in Addis Ababa. To understand how
the overall food security status has changed during the pandemic, we assigned a value 1 to each
positive response and add them up. Following FAO (2015) guidelines, a zero score (i.e., household
responded "No" to each question) indicates that the household is food secure. A score between 1
and 3 indicates mild food security, a score between 4 and 6 indicates moderate food security and a

16
score higher than that is a marker for severe food security. Figure 14 shows the share of
households in each category by survey round. We find that food security status improved slightly in
the latest survey round. In both the May and the June surveys, about 6 percent of survey
households were severely food insecure, while in July, only 3 percent were severely food insecure.
Meanwhile, the share of fully food secure households increased slightly from 19 and 18 percent in
May and June, respectively, to 20 percent in July.

Table 2. Households responding positively to Food Insecurity Experience Scale questions,

by household wealth quintile, percent
June July survey
survey
Female- Male-
Question All All headed headed Poorest Poorer Middle Richer Richest
Worried about not having enough food
to eat because of a lack of money or 53.1 40.2 45.8 35.6 49.6 28.3 63.8 35.6 24.3
other resources
Unable to eat healthy and nutritious
food because of a lack of money or 74.2 70.7 74.2 67.8 75.7 90.0 81.0 58.5 47.8
other resources
Ate only a few kinds of foods because
75.6 70.9 72.7 69.4 80.0 90.8 59.5 64.4 59.1
of a lack of money or other resources
Had to skip a meal because there was
not enough money or other resources 27.3 22.4 25.8 19.7 33.9 25.0 25.0 22.0 6.1
to get food
Ate less than you thought you should
because of a lack of money or other 45.2 42.8 43.9 41.9 52.2 72.5 18.1 48.3 21.7
resources
Ran out of food because of a lack of
8.8 5.7 6.4 5.0 9.6 6.7 2.6 5.9 3.5
money or other resources
Were hungry but did not eat because
there was not enough money or other 7.8 6.3 9.1 4.1 16.5 4.2 6.0 3.4 1.7
resources for food
Went without eating for a whole day
because of a lack of money or other 2.9 1.4 1.5 1.3 2.6 0.8 0.9 0.8 1.7
resources
Source: Own calculation from Addis Ababa COVID-19 phone surveys in May & June 2020. Observations = 589 households in June &
584 in July. Recall period is last 4 weeks.

Figure 14. Household food security status, by survey round

Source: Own calculation from Addis Ababa COVID-19 phone survey in May, June, and July 2020.

17
 Third, in the January and February round and in all phone survey rounds, we asked
households about their food consumption patterns over the past seven days. We use these data to
construct a Household Dietary Diversity Score (HDDS) in which consumed food items are grouped
into 12 food groups, listed in the first column of Table 3 (Swindale & Bilinsky 2006). Overall, the
share of households consuming from each food group remained relatively stable across survey
rounds. However, we observe that, compared to January and February, households are less likely
to consume fruit and animal source foods (meat products, dairy, and eggs) after the pandemic
began. The drop in animal source food consumption is particularly steep in the July round, most
likely because the survey coincided with an Orthodox fasting season. Table A4 in Appendix C
shows HDDS food group consumption prevalence by household headship and asset quintile.

Table 3. Households consuming from each Household Dietary Diversity Score food group,
by survey round, percent
May phone June phone July phone
HDDS food group Jan/Feb survey survey survey survey
Cereals 100 100 100 100
Roots or tubers 79 67 78 88
Vegetables 100 99 99 99
Fruits 81 60 59 61
Meat or poultry 65 54 34 13
Eggs 52 54 43 24
Fish and seafood 3 2 3 1
Nuts or pulses 99 98 100 99
Dairy 56 45 45 30
Oil or fats 99 98 98 99
Sugar/honey 98 85 95 93
Miscellaneous foods 100 93 97 99
Household Dietary Diversity Score 9.3 8.5 8.5 8.1
Source: Own calculation from January and February 2020 Addis Ababa food consumption survey and from Addis Ababa COVID-19
phone surveys in May, June, and July 2020. Observations = 600 households in Jan/Feb and May rounds; 589 in June; 584 in July.
Note: HDDS = Household Dietary Diversity Score. Recall period is last 7 days.

Assigning a value of 1 for each positive response and summing, we can construct the HDDS in
which higher scores indicate a better household food security situation. The mean HDDS in this
sample was 9.3 in January and February. In the May and June surveys, the mean HDDS score
was 8.5 (Table 3). In the July survey, HDDS fell to 8.1 – again, most likely because the recall
period coincided with an Orthodox fasting period. The local polynomial regression presented in
Figure 15 shows that richer households have higher HDDS than poorer households. The fall in
HDDS observed in the July survey is mainly seen among richer households.

18
Figure 15. Household wealth and Household Dietary Diversity Score

Source: Own calculation from Addis Ababa COVID-19 phone survey in June and July 2020. Observations = 589 households in June &
584 in July. Note: Local polynomial regression. The shaded areas represent 95 % confidence intervals. The recall period is last 7 days.
The wealth index (vertical axis) is constructed using a principal components method based on household asset ownership using data
collected in the January and February 2020 Addis Ababa food consumption survey. The wealth index has been scaled to 0-10.

Finally, we construct the Food Consumption Score (FCS), a weighted index that combines
dietary diversity and consumption frequency (WFP 2008). The index is based on household
consumption of nine food groups over the past seven days (Table 4). The weighted index ranges
between 0 and 112, with higher scores indicating better food security. WFP categorizes household
diets as poor if the FCS is below 21, borderline if the score is above 21 but below 35, and
acceptable if above 35.

Table 4. Mean number of days households consume from the Food Consumption Score
food groups, by survey round

FCS Jan/Feb May phone June phone July phone

FCS food group weight survey survey survey survey
Main staples 2 7.0 7.0 7.0 7.0
Pulses 3 5.5 4.8 5.4 5.6
Vegetables 1 7.0 6.7 6.8 6.7
Fruit 1 3.7 1.7 1.6 1.7
Meat, eggs, fish 4 2.8 2.6 1.6 0.8
Dairy products 4 2.2 1.6 1.6 1.2
Sugar 0.5 6.8 5.5 6.2 6.2
Oil/butter 0.5 6.7 6.8 6.8 6.8
Condiments 0 7.0 6.1 6.1 6.6
Food Consumption Score n/a 67.8 59.7 57.4 53.4
Source: Own calculation from Addis Ababa COVID-19 phone survey in May and June 2020. Observations = 600 households in Jan &
Feb and May, 589 households in June and 584 households in July. Note: FCS = Food Consumption Score. Recall period is 7 days.

Table 4 shows results for the January-February survey round and phone survey rounds
conducted in early May, early June, and early July. Compared to January and February,
households are consuming fruit, dairy, pulses, and sugar products less frequently during the
pandemic. Consequently, the mean FCS is considerably lower in the three phone survey rounds
than in the in-person survey conducted in January-February. As before, the consumption
frequency of animal source foods in July is lower than in other rounds, most likely because the July
survey took place during an Orthodox fasting period. However, less than three percent of
households in July were categorized as being in the poor or borderline FCS categories, i.e., below

19
35. Table A5 in Appendix C breaks down the data provided in Table 4 by household headship and
asset quintile.
Figure 16 illustrates how household wealth is positively correlated with FCS in the June and
July survey rounds. The FCS in July is slightly below the one calculated for the June round for
almost all asset levels, suggesting that the food security situation worsened in July. However, the
difference is marginal and as noted above, most likely driven by the Orthodox fasting season that
took place at the end of June and beginning of July.

Figure 16. Household wealth and Food Consumption Score

Source: Own calculation from Addis Ababa COVID-19 phone survey in June & July 2020. Observations = 584 households.
Note: Local polynomial regression. The shaded areas represent 95 % confidence intervals. The wealth index (vertical axis) is
constructed using a principal components method based on household asset ownership using data collected in the January and
February 2020 Addis Ababa food consumption survey. The wealth index has been scaled to 0-10.

7. CONCLUSIONS
Our phone survey results suggest the COVID-19 pandemic has negatively affected the majority of
households in Addis Ababa. More than two-third of our respondents indicated that their incomes
were lower than expected in May, and 42 percent reported that they are extremely stressed about
the ongoing situation. Moreover, we find strong evidence that the adverse impacts of COVID-19
are disproportionally affecting less-wealthy households. Compared to a period just before the
pandemic, all available indicators show that the food security situation in Addis Ababa has
worsened over the past few months. However, for the average household, these indicators did not
deteriorate further between April (May phone survey) and May (June survey). Moreover, we see
some suggestive evidence that the income and food security situation improved in June (July
survey), after accounting for the influence of the short Orthodox fasting season that coincided with
this latest survey. This finding is in line with the recent household and firm surveys conducted by
the World Bank that suggest a partial economic recovery (Bundervoet, Abebe, & Wieser 2020;
World Bank 2020). For nutrition security, it is particularly worrying that many households are now
less frequently consuming relatively more expensive but nutritionally beneficial foods, such as
meat, fruit, and dairy products. The overall food security status in Addis Ababa is not alarming,
possibly because most households have been able to use their savings to buffer food
consumption. Our results further show that households do not have much savings and many
households express concerns about their near-future income streams.

20
 As in our previous survey rounds, we observed high adherence to the recommended practices
to minimize the virus risk. Virtually all respondents reported using facemasks in public spaces.
Our study has limitations. First, while our sample is unlikely to suffer from response or sampling
biases, some of the documented differences between survey types could be due to differences in
survey mode, i.e., face-to-face versus phone (Lamanna et al. 2019). This point should be kept in
mind when comparing the data collected in the January-February survey and our phone surveys.
Second, we cannot administer a full household consumption survey module over the phone, which
is unfortunate because it would have allowed us to compare real-world poverty estimates to the
predictions from computable general equilibrium and other simulation models (Bundervoet & Finn
2020; Sumner, Hoy, & Ortiz-Juarez 2020; Vos, Martin, & Laborde 2020).
Third, the analysis falls short in assessing gender aspects of this crisis. A relatively large
fraction of households in Addis Ababa are headed by women. Compared to male-headed
households, our analysis suggests that female-headed households are not more (or less) affected
by the pandemic. However, probably a more relevant metric for assessing gender inequality is
intra-household allocation of resources (Beegle & van de Walle 2019). Unfortunately, due to
concerns about the length of the survey instrument, we were not able to include such questions in
our phone survey. The data collected before the pandemic indicate that in male-headed
households, women are often responsible for income from wages, rent, remittances, and
assistance programs. Fortunately, these income sources have not been among the worst affected
by the pandemic (Hirvonen et al. 2020). Moreover, the potential scale-up of assistance programs is
likely to channel more resources to women.
Despite these caveats, we believe this report provides a useful input to policy discussions in
Ethiopia and potentially beyond. While it is certainly encouraging that the economy seems to be
bouncing back, it is too early to celebrate, especially as the COVID-19 caseloads are still on the
rise in the country. Our analysis of the coping mechanisms suggests that many households have
drawn on their savings to cope with the economic impacts of the pandemic. Consequently, the
buffer savings are likely to be low, especially among the poorest households and consequently,
they may not be able to sustain further economic shocks. Thus, there remains a case for scaling-
up existing support programs, particularly since we do not know how the pandemic will evolve in
Ethiopia and globally. Some commentators have raised concerns about the difficulty in targeting
income support during the pandemic (Jerving 2020). In urban Ethiopia, the UPSNP provides an
already established framework, based on community selection, to identify the poorest and most
affected households. So, this concern should be minimized in targeting additional social protection,
at least within urban Ethiopia.

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APPENDICES
Appendix A: Sampling approach
The sampling frame for the 2019 baseline survey in Addis Ababa was based on a 2017 survey with
the same households (Melesse, van den Berg, de Brauw, & Abate 2019) and followed a multi-
stage sampling approach. First, a stratified random sampling method was used to select sub-cities
and districts (woredas) of Addis Ababa for the survey. To do so, sub-cities were grouped according
to their welfare level, after which six sub-cities were randomly drawn from these groups. A similar
welfare-based stratification was applied when 20 districts (woredas) were randomly selected from
the selected sub-cities. Second, two urban neighborhoods (ketenas) from each selected woreda
were then randomly selected and from each ketena, 25 households were randomly selected for
interviewing. In total, 930 households were interviewed in September and October 2019 (Wolle,
Hirvonen, de Brauw, Baye, & Abate 2020). 9
The same households were revisited for the January and February 2020 endline survey. This
time 895 households were interviewed; 96 percent of the households interviewed during the
baseline survey in September and October 2019.
Table A1 shows summary statistics for key household characteristics based on the January
and February 2020 survey data. Forty-five percent of the households were female-headed, which
corresponds to the previous estimates by CSA (2018). The average household in our January and
February face-to-face survey sample was 4.5 (median = 4). The average household head was 51
years old and she or he had 6.4 years of education. The average Food Consumption Score (see
WFP 2008) was 68.2 and the average Household Dietary Diversity Score (see Swindale & Bilinsky
2006) was 9.3 food groups.

Table A1. Basic household characteristics, January and February 2020 survey
Standard
Mean Median deviation Minimum Maximum
Household size 4.54 4.0 1.9 1 13
Female-headed household 0.45 n/a n/a 0 1
Head's age in years 51.2 50.0 15.4 11 92
Head's education in years 6.42 7.0 4.6 0 13
Food Consumption Score 68.2 64.0 20.9 8.5 112
Household Dietary Diversity Score 9.27 10.0 1.6 4 12
Source: Own calculation from January and February 2020 Addis Ababa food consumption survey.
Observations: 895 households.

9
A replacement household was randomly drawn if the household interviewed in 2017 was not available in 2019.

24
Appendix B: Comparing characteristics of survey households from the
January and February 2020 survey sample that were and were not
included in the May 2020 phone survey
Table A2 provides means for selected households characteristics from the January and
February 2020 Addis Ababa food consumption survey for the households included in the May 2020
phone survey (N=600) and for the households from the sample for the earlier survey that were not
selected to take part in the phone survey. We see that the two sub-samples are generally well
balanced. The differences in means are not statistically different from zero, except for the age of
the household head, for which the p-value is significant at the ten percent level. The household
heads in the sample included in the phone survey are about two years younger, on average, than
households that were not included in the phone survey sample.

Table A2. Comparing pre-pandemic household characteristics between households from

the January and February 2020 survey sample that were and were not included in the
May 2020 phone survey
Included Not included
Number of households: 600 295
Mean Mean Difference p-value
Household asset index 3.62 3.62 0.00 0.965
Household size 4.51 4.60 -0.08 0.547
Female-headed household 0.46 0.44 0.02 0.547
Head's age, years 50.4 52.7 -2.2 0.058
Head's education, years 6.57 6.11 0.46 0.153
Food Consumption Score 67.82 68.87 -1.05 0.471
Household Dietary Diversity Score 9.31 9.20 0.12 0.275
Source: Own calculation from January and February 2020 Addis Ababa food consumption survey.
Note: Statistical significance tested using a two-sample t-test with standard errors clustered at the enumeration area level.

25
Appendix C: Disaggregation of July 2020 survey results by household wealth
quintile
Table A3. Coping mechanisms used by the households in the past 30 days, by wealth
quintile, percent
Female- Male-
HDDS food group All headed headed Poorest Poorer Middle Richer Richest
Used cash/bank savings 65 66 64 81 64 71 71 37
Reduced non-food consumption 66 64 68 83 57 59 68 63
Reduced food consumption 49 47 50 59 55 41 52 37
Bought items of credit 16 16 16 22 19 16 16 7
Borrowed money 12 13 10 17 4 16 12 10
Sold off assets 2 3 2 4 0 3 4 1
Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.

Table A4. Households consuming from each Household Dietary Diversity Score food group
over the past seven days, by wealth quintile, percent
Female- Male-
HDDS food group All headed headed Poorest Poorer Middle Richer Richest
Cereals 100 100 100 100 100 100 100 100
Roots or tubers 88 85 89 79 92 88 85 94
Vegetables 99 99 99 97 100 99 100 99
Fruits 61 55 65 31 72 58 69 73
Meat or poultry 13 9 17 8 8 16 12 23
Eggs 24 20 28 10 24 20 26 42
Fish and seafood 1 1 1 0 0 1 0 4
Nuts or pulses 99 99 99 99 99 98 100 100
Dairy 30 24 36 17 36 35 25 38
Oil or fats 99 99 99 98 99 97 100 99
Sugar/honey 93 93 93 94 98 79 99 97
Miscellaneous foods 99 98 99 98 98 99 100 98
Household Dietary
8.1 7.8 8.3 7.3 8.3 7.9 8.2 8.7
Diversity Score
Source: Own calculation from Addis Ababa COVID-19 phone surveys in July 2020. Observations = 584 households.
Note: HDDS = Household Dietary Diversity Score. Recall period is last 7 days.

Table A5. Mean number of days over the past seven that households reported consuming
from the Food Consumption Score food groups, by household wealth quintile
FCS Female- Male-
FCS food group weight All headed headed Poorest Poorer Middle Richer Richest
Main staples 2 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
Pulses 3 5.6 5.7 5.5 4.9 5.8 6.7 4.9 5.7
Vegetables 1 6.7 6.7 6.8 6.6 6.7 6.5 7.0 6.9
Fruits 1 1.7 1.5 1.8 0.7 1.8 1.3 2.0 2.5
Meat, eggs, fish 4 0.8 0.6 0.9 0.3 0.6 0.7 0.7 1.7
Dairy products 4 1.2 1.0 1.3 0.7 1.2 1.0 0.9 2.1
Sugar 0.5 6.2 6.2 6.2 6.1 6.4 4.9 6.9 6.6
Oil/butter 0.5 6.8 6.8 6.8 6.8 6.7 6.7 7.0 6.8
Condiments 0 6.6 6.5 6.7 6.4 6.4 6.5 6.9 6.6
Food Consumption
n/a 53.4 52.1 54.5 46.5 53.3 54.4 50.9 62.0
Score
Source: Own calculation from Addis Ababa COVID-19 phone survey in July 2020. Observations = 584 households.
Note: FCS = Food Consumption Score.

26
 ABOUT THE AUTHORS
Alan de Brauw is a Senior Research Fellow in the Markets, Trade, and Institutions Division
(MTID) at the International Food Policy Research Institute (IFPRI), based in Washington DC, USA.
Kalle Hirvonen is a Senior Research Fellow in the Development Strategy and Governance
Division at IFPRI, based in Addis Ababa, Ethiopia. Gashaw T. Abate is a Research Fellow in the
MTID at IFPRI, based in Addis Ababa, Ethiopia.

ACKNOWLEGEMENTS
This research note is an output of the Food Systems for Healthier Diets Flagship of the CGIAR Re-
search Program on Agriculture for Nutrition and Health (A4NH) produced by the Markets, Trade,
and Institutions Division of the International Food Policy Research Institute as part of an ongoing
project, funded by A4NH. We are grateful for Abinet Tekle and Alemayehu Deme from NEED and
Abraha Weldegerima for excellent survey coordination as well as Berhe Kiros, Dagne Alemu, Dirb
Mola, Habtamu Ayele, Hiwot Zelalem, Huluhager Endashaw, Meaza Niguse, Meskerem Abera,
Nadiya Kemal, and Selamawit Genene for their hard work in interviewing the respondents. None of
this work would have been possible without the generosity of the households that took part in these
surveys. We thank them all sincerely.

This publication has not been peer reviewed. Any opinions stated in this publication are those
of the author(s) and are not necessarily representative of or endorsed by IFPRI.

INTERNATIONAL FOOD POLICY IFPRI–ESSP ADDIS ABABA POLICY STUDIES INSTITUTE

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The Ethiopia Strategy Support Program (ESSP) is managed by the International Food Policy Research Institute (IFPRI); is jointly implemented
with the Policy Studies Institute (PSI); and is financially supported by the United States Agency for International Development (USAID), the
Department for International Development (DFID) of the government of the United Kingdom, and the European Union (EU).

This working paper is an output of the Food Systems for Healthier Diets flagship of the CGIAR Research Program on Agriculture for Nutrition
and Health (A4NH). This paper has been produced by the Markets, Trade, and Institutions Division of the International Food Policy Research
Institute as part of an ongoing project that is funded by A4NH.

This publication has been prepared as an output of ESSP and has not been independently peer reviewed. Any opinions expressed here belong
to the author(s) and are not necessarily representative of or endorsed by IFPRI, PSI, USAID, DFID, EU, A4NH, or CGIAR.

© 2020, Copyright remains with the author(s). This publication is licensed for use under a Creative Commons Attribution 4.0 International License
(CC BY 4.0). To view this license, visit https://creativecommons.org/licenses/by/4.0.
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