The coronavirus (COVID-19) pandemic impacted East Africa's poverty level. Extreme poverty rate in the region increased from 33 percent in 2019 to 35 percent in 2021. South Sudan and Brurundi had the highest share of population living on less than 1.90 U.S. dollars per day, 85 percent and 80 percent, respectively.

In 2025, 81 percent of the population in South Sudan and Burundi lived in extreme poverty (with less than 2.15 U.S. dollars a day), the highest scores recorded in the East African region. Mauritius registered the lowest share, with one percent of the population living in destitute conditions.

In 2022, the international poverty (based on 2017 purchasing power parity (PPP)) and the lower-income poverty rate (3.65 U.S. dollars in 2017 PPP), was highest in Burundi within the East African region, with 83 percent and 96.6 percent, respectively. However, the upper middle-income poverty rate was highest in Somalia, at 98.8 percent.

In 2025, over 20.4 million people in Madagascar lived in extreme poverty (less than 2.15 U.S. dollars a day), the highest number within East Africa. However, this accounts for 66 percent of the overall population living below the poverty line in the country. Uganda and Malawi followed, with almost 18.5 million and more than 17.2 million people living in destitution, respectively.

In 2025, nearly 11.7 percent of the world population in extreme poverty, with the poverty threshold at 2.15 U.S. dollars a day, lived in Nigeria. Moreover, the Democratic Republic of the Congo accounted for around 11.7 percent of the global population in extreme poverty. Other African nations with a large poor population were Tanzania, Mozambique, and Madagascar. Poverty levels remain high despite the forecast decline Poverty is a widespread issue across Africa. Around 429 million people on the continent were living below the extreme poverty line of 2.15 U.S. dollars a day in 2024. Since the continent had approximately 1.4 billion inhabitants, roughly a third of Africa’s population was in extreme poverty that year. Mozambique, Malawi, Central African Republic, and Niger had Africa’s highest extreme poverty rates based on the 2.15 U.S. dollars per day extreme poverty indicator (updated from 1.90 U.S. dollars in September 2022). Although the levels of poverty on the continent are forecast to decrease in the coming years, Africa will remain the poorest region compared to the rest of the world. Prevalence of poverty and malnutrition across Africa Multiple factors are linked to increased poverty. Regions with critical situations of employment, education, health, nutrition, war, and conflict usually have larger poor populations. Consequently, poverty tends to be more prevalent in least-developed and developing countries worldwide. For similar reasons, rural households also face higher poverty levels. In 2024, the extreme poverty rate in Africa stood at around 45 percent among the rural population, compared to seven percent in urban areas. Together with poverty, malnutrition is also widespread in Africa. Limited access to food leads to low health conditions, increasing the poverty risk. At the same time, poverty can determine inadequate nutrition. Almost 38.3 percent of the global undernourished population lived in Africa in 2022.

Kenya’s population has nearly tripled in the last 35 years, from 16.3 million in 1980 to about 47 million today yet majority of the population are below the poverty line. poverty in Kenya is a widespread problem concentrated in the rural areas. This data set shows poverty rates within the Kenyan counties.

As of November 2021, East Africa counted 51.9 million people with insufficient food for consumption. Among the selected countries in the region, Ethiopia had the highest number of inhabitants facing food insecurity, around 16.9 million. Uganda followed, with 13.9 million people in the same situation. Undergoing conflicts and economic crisis, South Sudan had 6.7 million inhabitants with insufficient food, which equaled over 60 percent of the country's population.

DGEA will determine what are the most appropriate genotypes for the range of dairy production systems and levels of production operated by small-holder farmers in East Africa, and how these genotypes can be delivered to small-holders. The project partners will apply high density snp technology to determine breed composition of cows owned by small-holders, and combine this with traditional and participatory appraisal of animal and farm performance to determine which genotypes are most profitable at different levels of production. An assessment of the potential value of importing, testing and delivery of genotypes from elsewhere will be undertaken. A partnership will be developed that has a fully articulated business model ready to implement delivery of germplasm in a Phase II project and beyond. A design will also be developed for better delivery of R4D in livestock genetics in sub-Saharan Africa., Germplasm for Dairy Development in East Africa. Phase I: Identifying appropriate germplasm and delivery mechanisms (DGEA1 ). DGEA1 will determine what are the most appropriate genotypes for the range of dairy production systems and levels of production operated by small-holder farmers in East Africa, and how these genotypes can be delivered to small-holders. The project partners will apply high density snp technology to determine breed composition of cows owned by small-holders, and combine this with traditional and participatory appraisal of animal and farm performance to determine which genotypes are most profitable at different levels of production. An assessment of the potential value of importing, testing and delivery of genotypes from elsewhere will be undertaken. A partnership will be developed that has a fully articulated business model ready to implement delivery of germplasm in a Phase II project and beyond. A design will also be developed for better delivery of R4D in livestock genetics in sub-Saharan Africa. This confidential dataset provides the signature of Selection & GWAS data used in : Aliloo H, Mrode R, Okeyo AM and Gibson JP (2020) Ancestral Haplotype Mapping for GWAS and Detection of Signatures of Selection in Admixed Dairy Cattle of Kenya. Front. Genet. 11:544. doi: 10.3389/fgene.2020.00544 Due to obligations to our host countries users of the genotypic data must commit to recognizing IP clauses which do not allow development or protection of this IP. If you can satisfy these clauses please contact Raphael Mrode to request the data, after completion of a non-disclosure agreement.

DGEA will determine what are the most appropriate genotypes for the range of dairy production systems and levels of production operated by small-holder farmers in East Africa, and how these genotypes can be delivered to small-holders. The project partners will apply high density snp technology to determine breed composition of cows owned by small-holders, and combine this with traditional and participatory appraisal of animal and farm performance to determine which genotypes are most profitable at different levels of production. An assessment of the potential value of importing, testing and delivery of genotypes from elsewhere will be undertaken. A partnership will be developed that has a fully articulated business model ready to implement delivery of germplasm in a Phase II project and beyond. A design will also be developed for better delivery of R4D in livestock genetics in sub-Saharan Africa., Germplasm for Dairy Development in East Africa. Phase I: Identifying appropriate germplasm and delivery mechanisms (DGEA1 ). DGEA1 will determine what are the most appropriate genotypes for the range of dairy production systems and levels of production operated by small-holder farmers in East Africa, and how these genotypes can be delivered to small-holders. The project partners will apply high density snp technology to determine breed composition of cows owned by small-holders, and combine this with traditional and participatory appraisal of animal and farm performance to determine which genotypes are most profitable at different levels of production. An assessment of the potential value of importing, testing and delivery of genotypes from elsewhere will be undertaken. A partnership will be developed that has a fully articulated business model ready to implement delivery of germplasm in a Phase II project and beyond. A design will also be developed for better delivery of R4D in livestock genetics in sub-Saharan Africa. This dataset contains monitoring productivity of animals in DGEA1 dairy cattle keeping households

Community-level characteristics of respondents in Eastern Africa.

Individual and household level characteristics of respondents in Eastern Africa.

South Sudan had the highest prevalence of food insecurity in East Africa as of November 2021. Over 60 percent of the country's population had insufficient food for consumption in the period. Uganda had the second most deteriorated situation in the region, with the share of food insecure population reaching roughly 33 percent. Overall, East Africa counted 51.9 million people with insufficient food for consumption in the same period.

Abstract

In an environment where the Bank must demonstrate its impact and value, it is critical that the institution collects and tracks empirical data on how its work is perceived by clients, partners and other stakeholders in our client countries.

In FY 2013, the Country Opinion Survey Program was scaled up in order to: - Annually assess perceptions of the World Bank among key stakeholders in a representative sample of client countries; - Track these opinions over time, representative of: regions, stakeholders, country lending levels, country income/size levels, etc. - Inform strategy and decision making: apply findings to challenges to ensure real time response at several levels: corporate, regional, country - Obtain systematic feedback from stakeholders regarding: - The general environment in their country; - Value of the World Bank in their country; - World Bank's presence (work, relationships, etc.); - World Bank's future role in their country. - Create a feedback loop that allows data to be shared with stakeholders.

Geographic coverage

The data from the 41 country surveys were combined in this review. Although individual countries are not specified, each country was designated as part of a particular region: Africa (AFR), East Asia (EAP), Europe/Central Asia (ECA), Latin America (LAC), Middle East/North Africa (MNA), and South Asia (SAR).

Analysis unit

Client Country

Kind of data

Sample survey data [ssd]

Sampling procedure

In FY 2013 (July 2012 to July 1, 2013), 26,014 stakeholders of the World Bank in 41 different countries were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in these surveys were drawn from among senior government officials (from the office of the Prime Minister, President, Minister, Parliamentarian; i.e., elected officials), staff of ministries (employees of ministries, ministerial departments, or implementation agencies, and government officials; i.e., non-elected government officials, and those attached to agencies implementing Bank-supported projects), consultants/contractors working on World Bank-supported projects/programs; project management units (PMUs) overseeing implementation of a project; local government officials or staff, bilateral and multilateral agency staff, private sector organizations, private foundations; the financial sector/private banks; non-government organizations (NGOs, including CBOs), the media, independent government institutions (e.g., regulatory agencies, central banks), trade unions, faith-based groups, members of academia or research institutes, and members of the judiciary.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The Questionnaire consists of the following sections:

A. General Issues facing a country: Respondents were asked to indicate whether the country is headed in the right direction, what they thought were the top three most important development priorities, and which areas would contribute most to reducing poverty and generating economic growth in the country.

B. Overall Attitudes toward the World Bank: Respondents were asked to rate their familiarity with the World Bank, the Bank's effectiveness in the country, the extent to which the Bank meets the country's needs for knowledge services and financial instruments, and the extent to which the Bank should seek or does seek to influence the global development agenda. Respondents were also asked to rate their agreement with various statements regarding the Bank's work and the extent to which the Bank is an effective development partner. Furthermore, respondents were asked to indicate the sectoral areas on which it would be most productive for the Bank to focus its resources, the Bank's greatest values and greatest weaknesses in its work, the most and least effective instruments in helping to reduce poverty in the country, with which groups the Bank should collaborate more, and to what reasons respondents attributed failed or slow reform efforts.

C. World Bank Effectiveness and Results: Respondents were asked to rate the extent to which the Bank's work helps achieve sustainable development results in the country, and the Bank's level of effectiveness across thirty-five development areas, such as economic growth, public sector governance, basic infrastructure, social protection, and others.

D. The World Bank's Knowledge: Respondents were asked to indicate the areas on which the Bank should focus its research efforts, and to rate the effectiveness and quality of the Bank's knowledge/research, including how significant of a contribution it makes to development results, its technical quality, and the Bank's effectiveness at providing linkage to non-Bank expertise.

E. Working with the World Bank: Respondents were asked to rate their level of agreement with a series of statements regarding working with the Bank, such as the World Bank's "Safeguard Policy" requirements being reasonable, the Bank imposing reasonable conditions on its lending, disbursing funds promptly, and increasing the country's institutional capacity.

F. The Future Role of the World Bank in the country: Respondents were asked to rate how significant a role the Bank should play in the country's development in the near future, and to indicate what the Bank should do to make itself of greater value in the country.

G. Communication and Information Sharing: Respondents were asked to indicate where they get information about economic and social development issues, how they prefer to receive information from the Bank, their access to the Internet, and their usage and evaluation of the Bank's websites. Respondents were asked about their awareness of the Bank's Access to Information policy, past information requests from the Bank, and their level of agreement that they use more data from the World Bank as a result of the Bank's Open Data policy. Respondents were also asked to indicate their level of agreement that they know how to find information from the Bank and that the Bank is responsive to information requests.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the World Bank, their exposure to the Bank in the country, and their geographic location.

Response rate

A total of 9,279 stakeholders (36% response rate) participated and are part of this review.

In 2022, almost 94 percent of Mozambique's population could not afford a health diet, the highest in the East African region. Malawi followed, with around 90 percent of their population experiencing dietary poverty.

In 2025, around 438.6 million people in Africa were living in extreme poverty, with the poverty threshold at 2.15 U.S. dollars a day. The number of poor people on the continent dropped slightly compared to the previous year. Poverty in Africa is expected to decline slightly in the coming years, even in the face of a growing population. The number of inhabitants living below the extreme poverty line would decrease to around 426 million by 2030.

Individual & household/community level characteristics of respondents.

In 2025, over 24.6 million people in Mozambique lived in extreme poverty (with less than 2.15 U.S. dollars a day), the highest number within Southern Africa. The country also scored the highest share of its overall population living below the poverty line in the region. On the other hand, Botswana had the lowest number of just over 322,400 people living in impoverished conditions, accounting for 13 percent of the overall population.

The contribution of this article is providing evidence of the impact of intrahousehold cooperation on household welfare and household public goods provision in agricultural households in East Africa. While one of the main empirical challenges is that intrahousehold cooperation and household welfare are likely to be endogenous, we make use of the random encouragement for an intervention intended to stimulate intrahousehold cooperation to estimate the effect on household welfare and household public goods provision that is mediated through cooperation. The random encouragement fulfils the conditions to be used as an instrument to estimate the causal effect of the otherwise potentially endogenous treatment variable cooperation. We demonstrate that improved cooperation, as measured by jointly controlling a substantial share of the coffee income and livestock, joint decision-making over cash crops and adoption of sustainable intensification practices, and the joint management of the main household food and cash crops, has substantial positive effects on household income per capita and on the likelihood of household food security. The likelihood of investing in agricultural production, an important public good in these households, is greatly increased by improved cooperation as well. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

Abstract

Since 1992, Kenya has been a generous host of refugees and asylum seekers, a population which today exceeds 500,000 people. The Kakuma Refugee Camps have long been among the largest hosting sites (about 40% of the total refugees in Kenya), and have become even larger in recent years, with an estimated 67 percent of the current refugee population arriving in the past five years. In 2015, UNHCR, the Government of Kenya, and partners established Kalobeyei Settlement, located 40 kilometers north of Kakuma, to reduce the population burden on the other camps and facilitate a shift towards an area-based development model that addresses the longer term prospects of both refugees and the host community. The refugee population makes up a significant share of the local population (an estimated 40 percent at the district level) and economy, engendering both positive and negative impacts on local Kenyans. While Kenya has emerged as a leader in measuring the impacts of forced displacement, refugees are not systematically included in the national household surveys that serve as the primary tools for measuring and monitoring poverty, labor markets and other welfare indicators at a country-wide level. As a result, comparison of poverty and vulnerability between refugees, host communities and nationals remains difficult. Initiated jointly by UNHCR and the World Bank, this survey replicates the preceding Kalobeyei SES (2018), designed to address these shortcomings and support the wider global vision laid out by the Global Refugee Compact and the Sustainable Development Goals. Data was collected in October 2019 to December 2019, covering about 2,122 households.

Geographic coverage

Kakuma Refugee Camp, Kenya

Analysis unit

Household and individual

Universe

Sampled household survey, representative of all refugees living in Kakuma refugee camp.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Kakuma SES utilized a two-stage sampling process where the first stage samples dwellings, stratified by subcamp, followed by second-stage households. Dwellings were drawn as the primary sampling unit (PSU) from an up-to-date list of all dwellings in the camp provided by UNHCR shelter unit, which serves as the sampling frame. The sample was drawn with explicit stratification for the four Kakuma subcamps, with uniform probability for Kakuma 1-3. For Kakuma 4, the selection probability was slightly increased because of higher expected nonresponse

The survey was designed to accurately estimate socioeconomic indicators such as the poverty rate for group sof the population that have at least a 50 percent representation in the population. A 3 percent margin of error at a confidence level of 95 percent is considered accurate, resulting in a sample size of 2,122. Considering a 10 percent nonresponse rate, the target sample size was 2,347.

Sampling deviation

None

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The following sections are included: household roster, education, employment, household characteristics, assets, access, vulnerabilities, social cohesion, coping mechanism, displacement and cunsumption and expenditure.

Cleaning operations

The dataset presented here has undergone light checking, cleaning and restructuring (data may still contain errors) as well as anonymization (includes removal of direct identifiers and sensitive variables, recoding and local suppression).

Response rate

The SES has a non-response rate of about 5%, mainly due to absence of respondent and refusal to participate in the survey

In 2024, 7.8 percent of Kenya’s population lived below 2.15 U.S. dollars per day. This meant that over 8.9 million Kenyans were in extreme poverty, most of whom were in rural areas. Over 7.8 million Kenyans in rural communities lived on less than 1.90 U.S. dollars daily, an amount 6.5 times higher than that recorded in urban regions. Nevertheless, the poverty incidence has declined compared to 2020. That year, businesses closed, unemployment increased, and food prices soared due to the coronavirus (COVID-19) pandemic. Consequently, the country witnessed higher levels of impoverishment, although improvements were already visible in 2021. Overall, the poverty rate in Kenya is expected to decline to 14 percent by 2025.

Poverty triggers food insecurity

Reducing poverty in Kenya puts the country on the way to enhancing food security. As of November 2021, 7.9 million Kenyans lacked sufficient food for consumption. That corresponded to 15.4 percent of the country's population. Also, in 2021, over one-quarter of Kenyan children under five years suffered from chronic malnutrition, a growth failure resulting from a lack of adequate nutrients over a long period. Another 4.2 percent of the children were affected by acute malnutrition, which concerns a rapid deterioration in the nutritional status over a short period.

A country where prosperity and poverty walk side by side

The poverty incidence in Kenya contrasts with the country's economic development. In 2021, Kenya ranked among the ten highest GDPs in Africa, at almost 116 billion U.S. dollars. Moreover, its gross national income per capita has increased to 2,170 U.S. dollars over the last 10 years, a growth of above 100 percent. Generally, while poverty decreased in the country during the same period, Kenya still seems to be far from reaching the United Nation's Sustainable Development Goals (SDGs) to eliminate extreme poverty by 2030.