This statistic shows the biggest cities in Ethiopia in 2022. In 2022, approximately 3.86 million people lived in Adis Abeba, making it the biggest city in Ethiopia.

Population in the largest city (% of urban population) in Ethiopia was reported at 18.25 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on May of 2025.

Ethiopia ET: Population in Largest City data was reported at 4,215,965.000 Person in 2017. This records an increase from the previous number of 4,039,927.000 Person for 2016. Ethiopia ET: Population in Largest City data is updated yearly, averaging 1,690,413.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 4,215,965.000 Person in 2017 and a record low of 519,177.000 Person in 1960. Ethiopia ET: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Population in largest city in Ethiopia was reported at 5703628 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Points represent major cities in Ethiopia

Ethiopia ET: Population in Largest City: as % of Urban Population data was reported at 15.931 % in 2017. This records a decrease from the previous number of 16.255 % for 2016. Ethiopia ET: Population in Largest City: as % of Urban Population data is updated yearly, averaging 29.736 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 36.434 % in 1960 and a record low of 15.931 % in 2017. Ethiopia ET: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted Average;

Chart and table of population level and growth rate for the Addis Ababa, Ethiopia metro area from 1950 to 2025.

Accessibility to regional cities dataset is modeled as raster-based travel time/cost analysis, computed for the largest cities surrounding the country. The following cities are included: City - Population Addis Ababa, Ethiopia - 5 153 002 Asmara, Eritrea - 1 258 001 Sohag, Egypt - 979 800 Wau, South Sudan - 328 651 Abeche, Chad - 83 155 This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (or optimal location).

Microplastics (MPs) pollution in water bodies, wastewater, and sewage is of concern due to their probable effects on the environment and human health. This study is a first-time attempt to evaluate MPs occurrence, abundance, characteristics, and polymeric types in sediment and agglomerated sewage water from several urban ditches in Bahir Dar, Ethiopia, in two class sizes (> 0.5 and < 0.5 mm). Out of the total of 239 MP particles, 61.09% were of

Traffic congestion poses a persistent and escalating problem for major cities in both developed and developing countries, exerting a direct impact on the economic growth and development of these urban areas. Quantifying the extent of traffic congestion is the fundamental initial step in comprehending the severity of traffic congestion in order to devise effective methods for alleviation. The city of Addis Ababa is currently experiencing significant traffic congestion at its main intersections. The primary aim of this research is to assess the current level of traffic congestion at specific intersections. The assessment of traffic congestion was conducted using the travel time method. Data on travel time, traffic volume, and travel speed were gathered at three blocks and two intersections using a combination of quantitative and qualitative data collection methods. The travel rate, delay rate, and total travel delay (in vehicle-minutes) were computed. The total vehicle-minute delay for the selected three segments is estimated to be approximately 12,708 vehicle-minutes (or 212 vehicle-hours). The text reveals the significance of measuring the various components of traffic congestion in order to ensure a sustainable traffic system. It also highlights the importance of maintaining a satisfactory level of service for the future sustainability of City.

This marginality hotspot map of Ethiopia uses the lowest quartile as thresholds for the dimensions of marginality. Again, this map shows how many dimension of marginality - as defined by Gatzweiler et al. (2011) - overlap. Quality/Lineage: Indicator - Input - Cut-off point total expenditure at household level - HICE survey data - Total expenditure is defined as all household consumption expenditures as well as non-consumption expenditures; regional level lowest quartile (1671.92 Birr) Prevalence of stunting among children under five, by lowest available subnational administrative unit, varying years (FGGD) - Global raster data layer with 5 arc-minutes resolution. Data compilation by FAO including the prevalence of stunting, LandScan global population database and the percentage of children under five - Percentage of children below 3 standard deviations of WHO growth standards (18.85%) Travel time to major cities: A global map of Accessibility (by Andrew Nelson) - Infrastructural data (based on data of: populated places, cities, road network, travel speeds, railway network, navigable rivers, major waterbodies, shipping lanes, borders, urban areas, elevation and slope); 30 arc-seconds resolution - More than 12 hours travelling to the next agglomeration with ≥50,000 people. percentage of households having health problem in last 2 months and not going to health institution or traditional healer - WMS survey data; regional level - Lowest quartile (49.11%) Global land area with soil constraints Depth, soil chemical status and natural, fertility, drainage, texture, miscellaneous land; - 5 arc-minutes resolution - Soils that have „very frequent severe“ soil constraints as well as soils “unsuitable for agriculture” according to FAO 2007 (FGGD) definition percent of households getting drinking water from unprotected well or spring - DHS survey data; regional level - Lowest quartile (15.83%) percentage of women saying wife beating is ok if she neglects children - DHS survey data - Lowest quartile (70.75%)

The metropolitan area of Lagos in Nigeria counted over 14 million middle-class people as of 2018. This was the highest number in Africa. Addis Ababa in Ethiopia followed with 2.7 million individuals belonging to the middle class. The middle-class population included people who had a disposable income of over 75 percent of their salary, were employed, had a business activity, or were in education, and had at least a secondary school degree.

Abstract

Survey based Harmonized Indicators (SHIP) files are harmonized data files from household surveys that are conducted by countries in Africa. To ensure the quality and transparency of the data, it is critical to document the procedures of compiling consumption aggregation and other indicators so that the results can be duplicated with ease. This process enables consistency and continuity that make temporal and cross-country comparisons consistent and more reliable.

Four harmonized data files are prepared for each survey to generate a set of harmonized variables that have the same variable names. Invariably, in each survey, questions are asked in a slightly different way, which poses challenges on consistent definition of harmonized variables. The harmonized household survey data present the best available variables with harmonized definitions, but not identical variables. The four harmonized data files are

a) Individual level file (Labor force indicators in a separate file): This file has information on basic characteristics of individuals such as age and sex, literacy, education, health, anthropometry and child survival. b) Labor force file: This file has information on labor force including employment/unemployment, earnings, sectors of employment, etc. c) Household level file: This file has information on household expenditure, household head characteristics (age and sex, level of education, employment), housing amenities, assets, and access to infrastructure and services. d) Household Expenditure file: This file has consumption/expenditure aggregates by consumption groups according to Purpose (COICOP) of Household Consumption of the UN.

Geographic coverage

National

Analysis unit

• Individual level for datasets with suffix _I and _L
• Household level for datasets with suffix _H and _E

Universe

The survey covered all de jure household members (usual residents).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Frame The list of households obtained from the 2001/2 Ethiopian Agricultural Sample Enumeration (EASE) was used as a frame to select EAs from the rural part of the country. On the other hand, the list consisting of households by EA, which was obtained from the 2004 Ethiopian Urban Economic Establishment Census, (EUEEC), was used as a frame in order to select sample enumeration areas for the urban HICE survey. A fresh list of households from each urban and rural EA was prepared at the beginning of the survey period. This list was, thus, used as a frame in order to select households from sample EAs.

Sample Design For the purpose of the survey the country was divided into three broad categories. That is; rural, major urban center and other urban center categories.

Category I: Rural: - This category consists of the rural areas of eight regional states and two administrative councils (Addis Ababa and Dire Dawa) of the country, except Gambella region. Each region was considered to be a domain (Reporting Level) for which major findings of the survey are reported. This category comprises 10 reporting levels. A stratified two-stage cluster sample design was used to select samples in which the primary sampling units (PSUs) were EAs. Twelve households per sample EA were selected as a Second Stage Sampling Unit (SSU) to which the survey questionnaire were administered.

Category II:- Major urban centers:- In this category all regional capitals (except Gambella region) and four additional urban centers having higher population sizes as compared to other urban centers were included. Each urban center in this category was considered as a reporting level. However, each sub-city of Addis Ababa was considered to be a domain (reporting levels). Since there is a high variation in the standards of living of the residents of these urban centers (that may have a significant impact on the final results of the survey), each urban center was further stratified into the following three sub-strata. Sub-stratum 1:- Households having a relatively high standards of living Sub-stratum 2:- Households having a relatively medium standards of living and Sub-stratum 3:- Households having a relatively low standards of living. The category has a total of 14 reporting levels. A stratified two-stage cluster sample design was also adopted in this instance. The primary sampling units were EAs of each urban center. Allocation of sample EAs of a reporting level among the above mentioned strata were accomplished in proportion to the number of EAs each stratum consists of. Sixteen households from each sample EA were inally selected as a Secondary Sampling Unit (SSU).

Category III: - Other urban centers: - Urban centers in the country other than those under category II were grouped into this category. Excluding Gambella region a domain of "other urban centers" is formed for each region. Consequently, 7 reporting levels were formed in this category. Harari, Addis Ababa and Dire Dawa do not have urban centers other than that grouped in category II. Hence, no domain was formed for these regions under this category. Unlike the above two categories a stratified three-stage cluster sample design was adopted to select samples from this category. The primary sampling units were urban centers and the second stage sampling units were EAs. Sixteen households from each EA were lastly selected at the third stage and the survey questionnaires administered for all of them.

Mode of data collection

Face-to-face [f2f]

Abstract

The Central Statistical Agency (CSA) has been providing labour force and related data at different levels and with varying details in their content. These include the 1976 Addis Ababa Manpower and Housing Sample Survey, the 1978 Survey on Population and Housing Characteristics of Seventeen Major Towns, the 1980/81 and 1987/88 Rural Labour Force Surveys, the 1984 and 1994 Population and Housing Census, and 2003 and 2004 Urban Bi-annual Employment Unemployment Survey. The 1996 and 2002 Surveys of Informal Sector and most of the household surveys undertaken by the Agency also provide limited information on the area. Still pieces of information in relation to that of employment can also be derived from small, large and medium scale establishment surveys. Till the 1999 Labour Force Survey (LFS) there hasn't been a comprehensive national labour force survey representing both urban and rural areas. This 2005 LFS is the second in the series.

The 2005 National Labor Force Survey was designed to provide statistical data on the size and characteristics of the economically active and the non-active population of the country, both in urban and rural areas. The data will be useful for policy makers, planners, researchers, and other institutionsand individuals engaged in the design, implementation and monitoring of human resource development plans, programs and projects. The specific objectives of this survey are to: - generate data on the size of work force that is available to participate in production process; - determine the status and rate of economic participation of different sub-groups of the population; - identify those who are actually contributing to the economic development (i.e., employed) and those out of the sphere; - determine the size and rate of unemployed population; - provide data on the structure of the working population; - obtain information about earnings from paid employment; - identify the distribution of employed population working in the formal/informal enterprises; and - provide time series data and trace changes over time.

Geographic coverage

Like the National Labour Force Survey of 1999, it covered both the urban and rural areas of all regions. Exceptions are Gambella Region, where only the urban parts of the region are covered, Affar Region with only zone one and zone three were covered and Somali Region where only Shinile, Jijiga and Liben zones were covered.

Analysis unit

• HouseHold (HH)
• Household Member

Universe

The survey is mainly aimed at providing information on the economic characteristics of the population aged 10 years and over,

Kind of data

Données échantillonées [ssd]

Sampling procedure

2.1 COVERAGE The 2005 (1997 E.C) Labour Force Sample Survey covered all rural and urban parts of the country except all zones of Gambella Region excluding Gambella town, and the non-sedentary population of three zones of Afar & six zones of Somali regions. In the rural parts of the country it was planned to cover 830 Enumeration Areas (EAs) and 24,900 households. All planned EAs were actually covered by the survey; however, due to various reasons it was not possible to conduct the survey in 39 sample households. Ultimately 100.00 % EAs and 99.84% household were covered by the survey. Regarding urban parts of the country it was initially planned to cover 995 EAs and 29,850 households. Eventually 100% of the EAs and 99.24% of the households were successfully covered by the survey.

2.2 SAMPLING FRAME The list of households obtained from the 2001/2 Ethiopian Agricultural Sample Enumeration (EASE) is used to select EAs from the rural part of the country. For urban sample EAs on the other hand the list consisting of households by EA, which was obtained from the 2004 Ethiopian Urban Economic Establishment Census, (EUEEC) was used as a frame. A fresh list of households from each urban and rural EA was prepared at the beginning of the survey period. The list was then used as a frame for selecting sample households of each EAs.

2.3 SAMPLE DESIGN For the purpose of the survey the country was divided into three broad categories. That is; rural, major urban center and other urban center categories.

Category I: Rural: - This category consists of the rural areas of 8 regions and two city administrations found in the country. Regarding the survey domains, each region or city administration was considered to be a domain (Reporting Level) for which major findings of the survey are reported. This category totally comprises 10 reporting levels. A stratified two-stage cluster sample design was used to select samples in which the primary sampling units (PSUs) were EAs. Households per sample EA were selected as a second Stage Sampling Unit (SSU) and the survey questionnaire finally administered to all members of sample households

Category II:- Major urban centers:- In this category all regional capitals and 15 other major urban centers that had a population size of 40,000 or more in 2004 were included. Each urban center in this category was considered as a reporting level. The category has totally 26 reporting levels. In this category too, in order to select the samples, a stratified two-stage cluster sample design was implemented. The primary sampling units were EAs. Households from each sample EA were then selected as a Second Stage Unit.

Category III: - Other urban centers: Urban centers in the country other than those under category II were grouped into this category. Excluding Gambella a domain of other urban centers is formed for each region. Consequently 7 reporting levels were formed in this category. Harari, Addis Ababa and Dire Dawa do not have urban centers other than that grouped in category II. Hence, no domain was formed for these regions under this category. Unlike the above two categories a stratified three stage cluster sample design was adopted to select samples from this category. The primary sampling units were urban centers and the second stage sampling units were EAs. Households from each EA were finely selected at the third stage and the survey questionnaires administered for all of them.

To have more informations on th sampling view the report (Page 8)

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire was organized in to five sections; Section - 1 Area identification of the selected household: this section dealt with area identification of respondents such as region, zone, wereda, etc.,

Section -2 Socio- demographic characteristics of households: it consisted of the general sociodemographic characteristics of the population such as age, sex, education, status and type of disability, status and types of training, marital status and fertility questions.

Section - 3 Productive activities during the last seven days: this section dealt with a range of questions which helps to see the status and characteristics of employed persons in a current status approach such as hours of work in productive activities, occupation, industry, employment status, and earnings from employment. Also questions included are hours spent on fetching water, collection of firewood, and domestic chores and place of work.

Section - 4 Unemployment and characteristics of unemployed persons: this section focused on the size and characteristics of the unemployed population.

Section - 5 Economic activities during the last twelve months: this section covered the usual economic activity status (refereeing to the long reference period), number of weeks of employment /unemployment/inactive, reasons for inactivity, employment status, whether working in the agricultural sector or not and the proportion of income gainedfrom non-agricultural sector.

The questionnaire used in the field for data collection was prepared in Amharic language. Most questions have pre-coded answers.

Cleaning operations

During the fieldwork, the field supervisors, statisticians and the heads of branch statistical offices have checked the filled-in questionnaires and carried out some editing. However, the major editing and coding operation was carried out at the head office. All urban questionnaires were subjected to complete manual editing, while most of rural questionnaires were partially edited. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry. This system of data processing was followed on the assumption that, there is less complication of activities in rural areas than urban centers.

After the data was entered, it was again verified using the computer edit specification prepared earlier for this purpose, the entered data were checked for consistencies and then computer editing or data cleaning was made by referring back to the filled-in questionnaire. This is an important part of data processing operation in attaining the required level of data quality. Consistency checks and re-checks were also made based on tabulation results. Computer programs used in data entry, machine editing and tabulation were prepared using the Integrated Microcomputer Processing System (IMPS).

Addis Ababa, in Ethiopia, ranked as the most expensive city to live in Africa as of 2024, considering consumer goods prices. The Ethiopian capital obtained an index score of 46.7, followed by Harare, in Zimbabwe, with 37.4. Morocco and South Africa were the countries with the most representatives among the 15 cities with the highest cost of living in Africa.

Nigeria has the largest population in Africa. As of 2024, the country counted over 232.6 million individuals, whereas Ethiopia, which ranked second, has around 132 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 116 million people. In terms of inhabitants per square kilometer, Nigeria only ranks seventh, while Mauritius has the highest population density on the whole African continent. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Niger, the Democratic Republic of Congo, and Chad, the population increase peaks at over three percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. However, African cities are currently growing at larger rates. Indeed, most of the fastest-growing cities in the world are located in Sub-Saharan Africa. Gwagwalada, in Nigeria, and Kabinda, in the Democratic Republic of the Congo, ranked first worldwide. By 2035, instead, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria.

Motivation for the study: The motivation for the study started from the fact that the world is characterised by a high degree of mobility. Subsequently, social, political and economic processes and outcomes within nation states are significantly impacted by migration, making it untenable to understand political processes solely by looking at actors within states. In parallel, in the context of transnational movements, concepts of citizenship have expanded beyond the nation state, and citizenship is in various ways conceived of as a relational practice. In such an understanding, citizenship moves away from legal status, but focuses on concrete, often everyday acts. Focusing on such acts of citizenship makes it possible to analyse citizenship as a practice related to homelands, hostlands, or the wider transnational social field in often interconnected and overlapping ways. The study brought a critical analysis of these strands of literature together and investigated how practices of citizenship among emerging diaspora constitute (political) belonging and unbelonging - to the homeland but also the hostland and the transnational social field. In a further step, it also investigated what forms of political engagement or non-engagement may emerge from such practices. In order to say something meaningful about these theoretical and empirical questions, three cities in the wider Horn of Africa were chosen as case study locations, as the Horn is a prototypical example of an origin-area of out-migration and a region where many migrants stay in neighbouring countries, near their homeland. Focusing on how migrants become emerging diasporas, the project looked at migrants from Ethiopia and Eritrea who reside in key cities of the region, namely Addis Ababa; Khartoum; and Nairobi. Such a detailed focus allowed to understand how migration shapes lived citizenship practices, political belonging and engagement, and this in turn speaks to the wider debates on patterns of migration, belonging and transnationalism, but also the potential and pitfalls of conceptions of lived citizenship.

Aims and Topics covered: The overall aim of the project has been to improve our understanding of the ways in which diaspora populations embrace, subvert and refine ideas, narratives and practices of citizenship and establish different forms of (political) belonging and unbelonging to their homeland, their place of residence and the wider transnational social field. The project was conceived as having an extensive qualitative component that would have included (in addition to in-depths interviews) participant observation; knowledge production by participants (based on methods like photo-voice); and co-production of knowledge through dissemination activities. Due to the COVID-19 pandemic, the only possible means of data collection became in-depth virtual interviews (for a discussion of these changes in data collection methods and the potential and pitfalls, please refer to the sections on methods). These interviews still allowed to achieve the key objectives of the project: a detailed analysis of how emerging Eritrean and Ethiopian diaspora perform and practice citizenship, and through these performances assert political belonging in relation to Eritrea and Ethiopia, their host-cities in neighbouring countries (Addis Ababa; Khartoum; Nairobi) and the wider Eritrean and Ethiopian diaspora spread across the world. Following a lose interview guide, the project data provided key insights into how political belonging is produced, performed, and contested by emerging Eritrean and Ethiopian diaspora through acts of citizenship. This then contributed to an interrogation of the concept of transnational lived citizenship as a useful theoretical framing for understanding political belonging in relation to homelands, hostlands and the transnational social field of emerging diaspora. It built on previous work on diaspora that has examined everyday practices as expressions of belonging and identification and brought this together with work on diaspora politics and contested connections to and beyond the nation state. The COVID-19 pandemic provided an additional lens to interrogate lived citizenship practices and changing patterns of belonging, and how those may be transformed by intersecting crises, as did the outbreak of internal armed conflict in Ethiopia during the interview phase that also involved Eritrea.

Key findings: The project contributed first to the call to re-theorise transnational citizenship practices as a specific form of political belonging going beyond the nation-state but at the same time intimately linked to it. Second, it provided comparative empirical data on concrete citizenship practices and the forms of political belonging these generate. This makes the contribution to theory intimately linked with an empirical investigation. Third, it focused on emerging diaspora in key urban settings in the Global South, cities more generally being seen as important sites for a reconfiguration of citizenship practices. Fourth, through having provided a thorough understanding of how emerging diaspora exercise transnational lived citizenship, a detailed understanding of the ambivalent loyalties that often characterise migrant lives has become visible, as a response to crises but also more generally. This has also been linked to the literature in liminal legality in cities of residence, and to how such liminality determines everyday practices of lived citizenship and belonging. Ultimately, the key findings enforce a focus that also underpins the lived-citizenship literature: It is vital to understand and analyse the tensions that characterise migrant struggles in cities all over the world, and from there think creatively about localised solutions within a transnational social field where migrant rights are increasingly threatened.

Abstract

This survey was conducted as part of a review of the different civil service reform tools in Ethiopia, to assess what has been achieved, and what to consider next. The review aimed to take stock of what has been done, identify remaining and potential new challenges, and draw lessons, as well as suggest recommendations on how to move further ahead in the coming years to foster a fair, responsible, efficient, ethical, and transparent civil service. A survey of civil servants at the Federal, Regional and Woreda levels was implemented that focused on five sectors, namely, agriculture, education, health, revenue administration, and trade.

The aim of the Ethiopia Civil Servant Survey was to gather micro-level data on the perceptions and experiences of civil servants, and on the key restraints to civil servants performing their duties to the best of their abilities, and to the provision of public goods. This civil servant survey aimed to contribute to the development of diagnostic tools which would allow to better understand the incentive environments which lead to different types of behavior and the determinants of service delivery in the civil service.

Report available at: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/981311547566282423/moving-further-on-civil-service-reforms-in-ethiopia-findings-and-implications-from-a-civil-service-survey-and-qualitative-analysis

Geographic coverage

At the Federal level 330 individuals were planned to be interviewed; 550 at the Region level (Harar, Afar, SNNPR, Oromiya, Amhara, Dire Dawa, Addis Ababa, Benishangul, Somali, Tigray, Gambella); and 1615 at the Woreda (66 Woredas) level. Within each region 50 individuals were targeted to be interviewed, except in Addis Ababa, where the target was 40 due to not having an agriculture bureau, and except in Oromiya, where, due to additional funds becoming available, the target became 60. Within each Woreda, 25 individuals were planned to be sampled.

Analysis unit

Public servants, including managers and non-managers at the Federal, Regional and Woreda levels.

Kind of data

Aggregate data [agg]

Sampling procedure

To provide a large sample for statistical analysis, while remaining within budget, the Ethiopian civil servants survey focused on the three major policy making tiers of government: Federal; Regional; and Woreda. The Ministry of Public Sector and Human Resource Development identified the 5 core sectors that the survey should include: agriculture, education, health, revenue, and trade. The decision was made then to plan to interview a sufficient number of individuals from each of those tiers and allocate the remaining funds to Woreda-level interviews. With this methodology, with the funds available, 70 Woredas were included in the target sample at the planning stage. At the Federal level 330 individuals were planned to be interviewed; 550 at the Region level; and 1615 at the Woreda level. Within each region 50 individuals were targeted to be interviewed, except in Addis Ababa, where the target was 40 due to not having an agriculture bureau, and except in Oromiya, where, due to additional funds becoming available, the target became 60. Within each Woreda, 25 individuals were planned to be sampled.

Stratified randomization was conducted to select 70 Woredas from the 9 regional states in a way that is proportional to the size of the region (in terms of number of Woredas as per the 2007 census). However, 4 Woredas were dropped due to security challenges.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey questionnaire comprises following modules: 1- Cover page, 2- Demographic and work history information, 3- Management practices, 4- Turnover, 5- Recruitment and selection, 6- Attitude, 7- Time use and bottlenecks, 8- Information, 9- Information technology, 10- Stakeholder engagement, 11- Reforms, and 12- Woreda and city benchmarking.

The questionnaire was prepared in English and Amharic.

Response rate

Response rate was 88%.

Abstract

The 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) is a nationwide survey with a nationally representative sample of 9,150 selected households. All women age 15-49 who were usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. In the selected households, all children under age 5 were eligible for height and weight measurements. The survey was designed to produce reliable estimates of key indicators at the national level as well as for urban and rural areas and each of the 11 regions in Ethiopia.

The primary objective of the 2019 EMDHS is to provide up-to-date estimates of key demographic and health indicators. Specifically, the main objectives of the survey are: ▪ To collect high-quality data on contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; child nutrition; and other health issues relevant to achievement of the Sustainable Development Goals (SDGs) ▪ To collect information on health-related matters such as breastfeeding, maternal and child care (antenatal, delivery, and postnatal), children’s immunizations, and childhood diseases ▪ To assess the nutritional status of children under age 5 by measuring weight and height

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Health facility

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2019 EMDHS is a frame of all census enumeration areas (EAs) created for the 2019 Ethiopia Population and Housing Census (EPHC) and conducted by the Central Statistical Agency (CSA). The census frame is a complete list of the 149,093 EAs created for the 2019 EPHC. An EA is a geographic area covering an average of 131 households. The sampling frame contains information about EA location, type of residence (urban or rural), and estimated number of residential households.

Administratively, Ethiopia is divided into nine geographical regions and two administrative cities. The sample for the 2019 EMDHS was designed to provide estimates of key indicators for the country as a whole, for urban and rural areas separately, and for each of the nine regions and the two administrative cities.

The 2019 EMDHS sample was stratified and selected in two stages. Each region was stratified into urban and rural areas, yielding 21 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage of sampling.

To ensure that survey precision was comparable across regions, sample allocation was done through an equal allocation wherein 25 EAs were selected from eight regions. However, 35 EAs were selected from each of the three larger regions: Amhara, Oromia, and the Southern Nations, Nationalities, and Peoples’ Region (SNNPR).

In the first stage, a total of 305 EAs (93 in urban areas and 212 in rural areas) were selected with probability proportional to EA size (based on the 2019 EPHC frame) and with independent selection in each sampling stratum. A household listing operation was carried out in all selected EAs from January through April 2019. The resulting lists of households served as a sampling frame for the selection of households in the second stage. Some of the selected EAs for the 2019 EMDHS were large, with more than 300 households. To minimise the task of household listing, each large EA selected for the 2019 EMDHS was segmented. Only one segment was selected for the survey, with probability proportional to segment size. Household listing was conducted only in the selected segment; that is, a 2019 EMDHS cluster is either an EA or a segment of an EA.

In the second stage of selection, a fixed number of 30 households per cluster were selected with an equal probability systematic selection from the newly created household listing. All women age 15-49 who were either permanent residents of the selected households or visitors who slept in the household the night before the survey were eligible to be interviewed. In all selected households, height and weight measurements were collected from children age 0-59 months, and women age 15-49 were interviewed using the Woman’s Questionnaire.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2019 EMDHS: (1) the Household Questionnaire, (2) the Woman’s Questionnaire, (3) the Anthropometry Questionnaire, (4) the Health Facility Questionnaire, and (5) the Fieldworker’s Questionnaire. These questionnaires, based on The DHS Program’s standard questionnaires, were adapted to reflect the population and health issues relevant to Ethiopia. They were shortened substantially to collect data on indicators of particular relevance to Ethiopia and donors to child health programmes.

Cleaning operations

All electronic data files were transferred via the secure internet file streaming system (IFSS) to the EPHI central office in Addis Ababa, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by EPHI staff members and an ICF consultant who took part in the main fieldwork training. They were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro System software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing, double data entry from both the anthropometry and health facility questionnaires, and data processing were initiated in April 2019 and completed in July 2019.

Response rate

A total of 9,150 households were selected for the sample, of which 8,794 were occupied. Of the occupied households, 8,663 were successfully interviewed, yielding a response rate of 99%.

In the interviewed households, 9,012 eligible women were identified for individual interviews; interviews were completed with 8,885 women, yielding a response rate of 99%. Overall, there was little variation in response rates according to residence; however, rates were slightly higher in rural than in urban areas.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2019 EMDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019 EMDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution

- Age distribution of eligible and interviewed women

As of 2018, more than 60 million people were living in urban areas in East Africa. Ethiopia was the country with the largest urban residents in the region, in terms of absolute numbers, roughly 23 million. In its turn, in Djibouti, 760 thousand people lived in urban areas by the same period. Even though, the country was the most urbanized in East Africa, with a share of 78 percent of urban population, in 2018.