As of 2023, Eastern Africa was the region with the largest population in Africa, with around *** million inhabitants. On the contrary, Southern Africa was the least populous area and counted approximately ** million people. In 2021, the total population of the African continent exceeded **** billion.

East Africa is one of the fastest urbanizing areas in the whole continent. From 2000 to 2018, urbanization in the region grew by 4.5 percent. Uganda and Burundi had the fastest urban growth rates, at six and 5.7 percent, respectively. In contrast, Djibouti's urban population expanded by 1.6 percent. Even though, the country was still the most urbanized in East Africa, with a share of close to 78 percent of urban population, in 2018.

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Roughly two out of ten people in East Africa are expected to live in urban areas in 2020. The region is one of the fastest urbanizing in the continent. In 1960, seven percent of East Africa was urbanized, while it was 24 percent in 2020. In absolute numbers, the number of urban residents jumped from three million to 65 million in the period, and Ethiopia is the country with more residents in urban areas, roughly 23 million.

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.

This horizontal bar chart displays urban population (people) by countries using the aggregation sum in Eastern Africa. The data is about countries.

This horizontal bar chart displays male population (people) by countries using the aggregation sum in Eastern Africa. The data is about countries.

Around 65 million people are expected to be living in urban areas in East Africa, by 2020. The region is one of the fastest urbanizing in the entire continent. In ten years, there were nearly 20 million more urban residents, as the total amount was 43 million in 2010. Djibouti is the most urbanized country in East Africa, with a share of approximately 78 percent of urban population, in 2018. In absolute numbers, Ethiopia has the largest number of urban residents, roughly 23 million.

Graph and download economic data for Population Growth for Developing Countries in Middle East and North Africa (SPPOPGROWMNA) from 1961 to 2023 about North Africa, Middle East, population, and rate.

In defining vulnerability, WFP (2009) and IFPRI (2012) have been followed and combined with indicators for food security with health indicators that signal vulnerability in a physical sense. IFPRI's Global Hunger Index uses three indicators to measure hunger: the number of adults being undernourished, the number of children that have low weight for age, and child mortality. Other classifications of food security use the variety of the diet as an indicator, combined with anthropometric data on children. However, in the DHS data there were no information available on child mortality, nor on dietary composition. Given these data limitations, data on nutritional status of women (Body Mass Index, BMI) for women and children (weight for age) have been used as indicators for food security. These data were combined with data on morbidity among adults and children, specifically the occurrence of malaria, cough, and diarrhea. Combinations of indicators have led to a classification of households as being very vulnerable, vulnerable, nearly vulnerable and not vulnerable. The Afrobarometer surveys did not include data on the BMI of adults nor weights for children. Here, the reported times the household went without food in the year were used prior to the date the survey was conducted as vulnerability indicator. The study area of households vulnerability included: rural, urban and total population. This data set was produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 5 (WP5). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata. This study in WP5 aimed to identify, locate and characterize groups that are vulnerable for climate change conditions in two country clusters; one in West Africa (Benin, Burkina Faso, Côte d'Ivoire, Ghana, and Togo) and one in East Africa (Sudan, South Sudan and Uganda). Data used for the study include the Demographic and Health Surveys (DHS) , the Multi Indicator Cluster Survey (MICS) and the Afrobarometer surveys for the socio-economic variables and grid level data on agro-ecological and climatic conditions.

This dataset is about countries in Eastern Africa. It has 17 rows. It features 3 columns: land area, and rural population.

This dataset is about countries in Eastern Africa. It has 17 rows. It features 3 columns: continent, and urban population.

Graph and download economic data for Population ages 65 and above for Developing Countries in Middle East and North Africa (SPPOP65UPTOZSMNA) from 1960 to 2024 about North Africa, Middle East, 65-years +, and population.

This horizontal bar chart displays population (people) by region using the aggregation sum in Eastern Africa. The data is about countries.

In 2018, around 58 percent of the urban population in East Africa lived in slums. The share was higher in South Sudan, where nearly the entire amount of urban residents (91.4 percent) were living in slums. Rwanda and Kenya were the countries with the lowest share of slum population, 42.1 and 46.5 percent, respectively.

Vulnerable population identified by the prevalence of diseases (malaria, cough and diarrhea) as indicator for food security, in sample of households in East Africa study area. Data based on DHS and MICS surveys. In defining vulnerability, WFP (2009) and IFPRI (2012) have been followed and combined with indicators for food security with health indicators that signal vulnerability in a physical sense. IFPRI's Global Hunger Index uses three indicators to measure hunger: the number of adults being undernourished, the number of children that have low weight for age, and child mortality. Other classifications of food security use the variety of the diet as an indicator, combined with anthropometric data on children. However, in the DHS data there were no information available on child mortality, nor on dietary composition. Given these data limitations, data on nutritional status of women (Body Mass Index, BMI) for women and children (weight for age and weight for height) have been used as indicators for food security. These data were combined with data on morbidity among adults and children, specifically the occurrence of malaria, cough, and diarrhea. Combinations of indicators have led to a classification of households as being very vulnerable, vulnerable, nearly vulnerable and not vulnerable. This data set was produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 5 (WP5). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata. This study in WP5 aimed to identify, locate and characterize groups that are vulnerable for climate change conditions in two country clusters; one in West Africa (Benin, Burkina Faso, Côte d'Ivoire, Ghana, and Togo) and one in East Africa (Sudan, South Sudan and Uganda). Data used for the study include the Demographic and Health Surveys (DHS) , the Multi Indicator Cluster Survey (MICS) and the Afrobarometer surveys for the socio-economic variables and grid level data on agro-ecological and climatic conditions.

Data publication: 2013-08-01

Supplemental Information:

ClimAfrica was an international project funded by European Commission under the 7th Framework Programme (FP7) for the period 2010-2014. The ClimAfrica consortium was formed by 18 institutions, 9 from Europe, 8 from Africa, and the Food and Agriculture Organization of United Nations (FAO).

ClimAfrica was conceived to respond to the urgent international need for the most appropriate and up-to-date tools and methodologies to better understand and predict climate change, assess its impact on African ecosystems and population, and develop the correct adaptation strategies. Africa is probably the most vulnerable continent to climate change and climate variability and shows diverse range of agro-ecological and geographical features. Thus the impacts of climate change can be very high and can greatly differ across the continent, and even within countries.

The project focused on the following specific objectives:

1. Develop improved climate predictions on seasonal to decadal climatic scales, especially relevant to SSA;

2. Assess climate impacts in key sectors of SSA livelihood and economy, especially water resources and agriculture;

3. Evaluate the vulnerability of ecosystems and civil population to inter-annual variations and longer trends (10 years) in climate;

4. Suggest and analyse new suited adaptation strategies, focused on local needs;

5. Develop a new concept of 10 years monitoring and forecasting warning system, useful for food security, risk management and civil protection in SSA;

6. Analyse the economic impacts of climate change on agriculture and water resources in SSA and the cost-effectiveness of potential adaptation measures.

The work of ClimAfrica project was broken down into the following work packages (WPs) closely connected. All the activities described in WP1, WP2, WP3, WP4, WP5 consider the domain of the entire South Sahara Africa region. Only WP6 has a country specific (watershed) spatial scale where models validation and detailed processes analysis are carried out.

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Lia van Wesenbeeck

Resource Contact: Ben Sonneveld

Resource constraints:

copyright

Online resources:

0 diseases, % of population - Prevalence of diseases in sample of households in East Africa

1 diseases, % of population - Prevalence of diseases in sample of households in East Africa

2 diseases, % of population - Prevalence of diseases in sample of households in East Africa

3 diseases, % of population - Prevalence of diseases in sample of households in East Africa

A spatially explicit assessment of specific vulnerabilities of the food system due to climate change and the identification of their causes; Technical report

CLIMAFRICA – Climate change predictions in Sub-Saharan Africa: impacts and adaptations

Scenarios of major production systems in Africa

This map contains estimates for total population by country from 1950 to 2015. Symbology changes slightly when zoomed in to individual continents (1:50,000,000). Source: United Nations Population Division, Department of Economic and Social Affairs, World Population Prospects: The 2015 Revision, File POP/1-1.Estimates are in thousands. Other fields in the Country Population Estimates layer include: Major Region (e.g. Africa), Minor Region (e.g. Eastern Africa), and UN Documentation Notes. The UN Documentation Notes field corresponds to the following notes:(1) Including Agalega, Rodrigues and Saint Brandon.(2) Including Zanzibar.(3) Including Ascension and Tristan da Cunha.(4) For statistical purposes, the data for China do not include Hong Kong and Macao, Special Administrative Regions (SAR) of China, and Taiwan Province of China.(5) As of 1 July 1997, Hong Kong became a Special Administrative Region (SAR) of China.(6) As of 20 December 1999, Macao became a Special Administrative Region (SAR) of China.(7) The regions Southern Asia and Central Asia are combined into South-Central Asia.(8) Including Sabah and Sarawak.(9) Including Nagorno-Karabakh.(10) Refers to the whole country(11) Including Abkhazia and South Ossetia.(12) Including East Jerusalem.(13) Including Transnistria.(14) Including Crimea(15) Refers to Guernsey, and Jersey.(16) Including Åland Islands.(17) Including Svalbard and Jan Mayen Islands.(18) Refers to the Vatican City State.(19) Including Kosovo.(20) Including Canary Islands, Ceuta and Melilla.(21) The former Yugoslav Republic of Macedonia.(22) Refers to Bonaire, Saba and Sint Eustatius.(23) Including Saint-Barthélemy and Saint-Martin (French part).(24) Including Christmas Island, Cocos (Keeling) Islands and Norfolk Island.(25) Including Pitcairn.

South Africa Population: Mid Year: Eastern Cape: 20 to 24 Years data was reported at 531,545.000 Person in 2018. This records a decrease from the previous number of 568,062.743 Person for 2017. South Africa Population: Mid Year: Eastern Cape: 20 to 24 Years data is updated yearly, averaging 620,146.947 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 671,734.772 Person in 2009 and a record low of 482,541.064 Person in 2001. South Africa Population: Mid Year: Eastern Cape: 20 to 24 Years data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G004: Population: Mid Year: by Province, Age and Sex.

Graph and download economic data for Population Growth: All Income Levels for Middle East and North Africa (SPPOPGROWMEA) from 1961 to 2024 about North Africa, Middle East, income, population, and rate.

South Africa Population: Mid Year: Eastern Cape: Male: 25 to 29 Years data was reported at 257,881.000 Person in 2018. This records a decrease from the previous number of 264,018.280 Person for 2017. South Africa Population: Mid Year: Eastern Cape: Male: 25 to 29 Years data is updated yearly, averaging 240,210.204 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 266,761.931 Person in 2015 and a record low of 166,088.006 Person in 2001. South Africa Population: Mid Year: Eastern Cape: Male: 25 to 29 Years data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G004: Population: Mid Year: by Province, Age and Sex.