Mauritius had the highest population density level in Africa as of 2023, with nearly 630 inhabitants per square kilometer. The country has also one of the smallest territories on the continent, which contributes to the high density. As a matter of fact, the majority of African countries with the largest concentration of people per square kilometer have the smallest geographical area as well. The exception is Nigeria, which ranks among the largest territorial countries in Africa and is very densely populated at the same time. After all, Nigeria has also the largest population on the continent.

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.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in the Central African Republic: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

Lagos, in Nigeria, ranked as the most populated city in Africa as of 2024, with an estimated population of roughly nine million inhabitants living in the city proper. Kinshasa, in Congo, and Cairo, in Egypt, followed with some 7.8 million and 7.7 million dwellers. Among the 15 largest cities in the continent, another two, Kano, and Ibadan, were located in Nigeria, the most populated country in Africa. Population density trends in Africa As of 2022, Africa exhibited a population density of 48.3 individuals per square kilometer. At the beginning of 2000, the population density across the continent has experienced a consistent annual increment. Projections indicated that the average population residing within each square kilometer would rise to approximately 54 by the year 2027. Moreover, Mauritius stood out as the African nation with the most elevated population density, exceeding 640 individuals per square kilometre. Mauritius possesses one of the most compact territories on the continent, a factor that significantly influences its high population density. Urbanization dynamics in Africa The urbanization rate in Africa was anticipated to reach close to 44 percent in 2021. Urbanization across the continent has consistently risen since 2000, with urban areas accommodating 35 percent of the total population. This trajectory is projected to continue its ascent in the years ahead. Nevertheless, the distribution between rural and urban populations shows remarkable diversity throughout the continent. In 2021, Gabon and Libya stood out as Africa’s most urbanized nations, each surpassing 80 percent urbanization. In 2023, Africa's population was estimated to expand by 2.35 percent compared to the preceding year. Since 2000, the population growth rate across the continent has consistently exceeded 2.45 percent, reaching its pinnacle at 2.59 percent between 2012 and 2013. Although the growth rate has experienced a deceleration, Africa's population will persistently grow significantly in the forthcoming years.

The population in Africa is expected to grow by 90 percent by 2050. Among the countries forecast to be the most populated in the continent, Nigeria leads, with an estimated population of over 401 million people. Currently, the nation has already the largest number of inhabitants in Africa. The highest population growth is expected to be measured in Angola, by 143.3 percent between 2019 and 2050. The number of inhabitants in the country is forecast to jump from 31.8 million to 77.4 million in the mentioned period.

This dataset provides values for POPULATION reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The northernmost region of the African continent was home to approximately 208 million individuals in 2023. Egypt, the third most populous country in Africa, had roughly 50 percent of the region's population living within its borders, with over 105 million inhabitants. Algeria, Morocco, and Tunisia followed with 46 million, 37 million, and 12 million citizens, respectively.

Central African Republic CF: Population Density: People per Square Km data was reported at 8.183 Person/sq km in 2022. This records a decrease from the previous number of 8.206 Person/sq km for 2021. Central African Republic CF: Population Density: People per Square Km data is updated yearly, averaging 4.833 Person/sq km from Dec 1961 (Median) to 2022, with 62 observations. The data reached an all-time high of 8.206 Person/sq km in 2021 and a record low of 2.784 Person/sq km in 1961. Central African Republic CF: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Central African Republic – Table CF.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.;Food and Agriculture Organization and World Bank population estimates.;Weighted average;

South Africa ZA: Population Density: People per Square Km data was reported at 46.754 Person/sq km in 2017. This records an increase from the previous number of 46.176 Person/sq km for 2016. South Africa ZA: Population Density: People per Square Km data is updated yearly, averaging 30.287 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 46.754 Person/sq km in 2017 and a record low of 14.773 Person/sq km in 1961. South Africa ZA: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.; ; Food and Agriculture Organization and World Bank population estimates.; Weighted average;

African countries. name, long name, population (source), population, constitutional form, drives on, head of state authority, Main continent, number of airports, Airports - with paved runways, Airports - with unpaved runways, Area, Birth rate, calling code, Children under the age of 5 years underweight, Current Account Balance, Death rate, Debt - external, Economic aid donor, Electricity consumption, Electricity consumption per capita, Electricity exports, Electricity imports, Electricity production, Exports, GDP - per capita (PPP), GDP (purchasing power parity), GDP real growth rate, Gross national income, Human Development Index, Health expenditures, Heliports, HIV AIDS adult prevalence rate, HIV AIDS deaths, HIV AIDS people living with HIV AIDS, Hospital bed density, capital city, Currency, Imports, Industrial production growth rate, Infant mortality rate, Inflation rate consumer prices, Internet hosts, internet tld, Internet users, Investment (gross fixed), iso 3166 code, ISO CODE, Labor force, Life expectancy at birth, Literacy, Manpower available for military service, Manpower fit for military service, Manpower reaching militarily age annually, is democracy, Market value of publicly traded shares, Maternal mortality rate, Merchant marine, Military expenditures percent of GDP, Natural gas consumption, Natural gas consumption per capita, Natural gas exports, Natural gas imports, Natural gas production, Natural gas proved reserves, Net migration rate, Obesity adult prevalence rate, Oil consumption, Oil consumption per capita, Oil exports, Oil imports, Oil production, Oil proved reserves, Physicians density, Population below poverty line, Population census, Population density, Population estimate, Population growth rate, Public debt, Railways, Reserves of foreign exchange and gold, Roadways, Stock of direct foreign investment abroad, Stock of direct foreign investment at home, Telephones main lines in use, Telephones main lines in use per capita, Telephones mobile cellular, Telephones mobile cellular per capita, Total fertility rate, Unemployment rate, Unemployment, youth ages 15-24, Waterways, valley, helicopter, canyon, artillery, crater, religion, continent, border, Plateau, marsh, Demonym

Abstract

The Future of African Remittances (FAR) team conducted research on remittance flows to measure and understand the remittance process in sub-Saharan Africa. This ambitious and important research is initially focused on three countries in East Africa - Ethiopia, Kenya and Uganda.

In order to glean insights into the remittance process in the three designated countries, the World Bank designed a two-phase survey process. Phase 1 involved conducting a national survey in each of the three countries. The purpose of the first phase of research was to collect a large representative sample of the adult population in each country. The national surveys provide important baseline data about international remittance flows including: an estimate of the percent of the total adult population that regularly receives remittances, the average amount of each remittance received, most common methods of receipt and top sending countries. Additionally, through the analysis of the national survey results, World Bank was able to identify areas of each country that have high concentrations of international remittance recipients. This important piece of information guided Phase 2 of the research - surveys of remittance receivers in each country. Whereas the national surveys aimed to collect general data about the remittance process, the surveys of remittance recipients allowed for the collection of more detailed data about the remittance process itself, how remittances are used, the relationship between sender and receiver, and interest in various financial products.

The results of this research will not only provide estimates of total annual amounts of remittances for each country, but also will tell us the percentage of the population in each country that is involved in the international remittance process. Furthermore, it will offer insights as to the degree to which Ethiopians, Kenyans and Ugandans depend on international remittances and how the money is used, saved and/or invested. Results will also measure interest in financial products that, if utilized, can significantly impact the financial well-being of the population and the overall economic stability of each country.

Geographic coverage

National Coverage

Analysis unit

Households Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

General:

The total samples were compiled utilizing multi-stage stratified random sampling through respondent selection. Multi-stage random sampling ensured that a random sample of adults was collected in each country. First, after stratifying the population of each country by region and population density, sampling points (SPs) were determined. SPs were then randomly selected within each stratum. At each SP, respondents were randomly selected to participate in the survey.

Phase 1:

The first phase consisted of national surveys of the adult population of each country. The three survey samples were designed to be representative of the adult populations of these three countries. World Bank coordinated and oversaw all aspects of the sampling and interviewing process. A team of local field experts was hired in each country to conduct the actual interviews. All interviewers were professionally trained and supervised by research personnel. In this phase of the research, a total of 2022 Kenyan adults were interviewed.

Phase 2:

Once the national surveys were completed, the results were analyzed to determine the areas of concentration of the remittance recipient population, after which the second phase of the project was conducted. This phase of the project included a targeted survey of the remittance recipient population of each of the three East African countries. Sampling Points were established based on the analysis of the national survey data and the identification of areas within each country that showed the highest concentrations of remittances received from relatives abroad in proportion to the sample size of all areas surveyed. Once again, local field experts were hired in each country to conduct the interviews, training and supervision of field operations. Languages of interviews were the same as those employed in Phase 1 and, again, all interviews were conducted in person using the PAPI method. A total of 400 interviews with regular international remittance recipients were completed in each country during August and September of 2010. The margin of error for all three surveys is approximately ±5 percentage points and the 95 percent level of confidence.

Detail:

The total sample was compiled utilizing multi-stage stratified random sampling through respondent selection. This sampling method enabled B&A to ensure that a representative random sample of Kenyan adults was collected. There are three stages to this type of sampling methodology. First, after stratifying the Kenyan population by region and population density, sampling points (SPs) were determined. SPs were then randomly selected within each stratum. In the second stage, using the random route method, dwellings were selected within each SP. The random route method involves selecting an address in each SP at random as a starting point. Each interviewer was given instructions to identify additional dwellings by taking alternate left and right turns and stopping at every Nth dwelling. The third and final stage involved selecting actual participants - for each selected dwelling, individual respondents were chosen using a Kish grid. In a Kish grid, prior to beginning the interview, the interviewer first asks for the ages and genders of every household member (only persons aged 18 or older were eligible for selection). The individual to be interviewed was then chosen based on a random number in the grid.

Once the national survey was completed, B&A analyzed the results to determine the areas of concentration of the remittance recipient population, after which the second phase of the project was conducted. This phase included a targeted survey of the remittance recipient population in Kenya. Sampling Points were established based on B&A's analysis of the national survey data and the identification of areas of the country that showed concentrations of international remittance receivers in proportion to the sample size of all areas surveyed. Once again, local field experts were hired to conduct the interviews and B&A conducted all training and supervision of field operations. Interviews were conducted in English or Swahili depending on respondent preference and all interviews were conducted in person using the PAPI method. A total of 401 interviews with regular international remittance recipients were conducted in Kenya during August and September of 2010. The margin of error for the surveys is approximately ±5 percentage points and the 95 percent level of confidence.

Mode of data collection

Face-to-face [f2f]

Research instrument

Phase 1:

This survey consisted of 12 questions that were aimed at helping to identify some of the basic characteristics of the remittance recipient population in each country. Some of the variables included in this survey were - location, age, gender, amount of money received, method of receipt, origin of remittance, etc.

Phase 2:

The survey instrument for Phase 2 consisted of approximately 35 questions and included a number of variables aimed at obtaining greater detail about the remittance receiving process including costs, amounts received, information about the sender and the relationship between sender and receiver. Additionally, the survey measured interest in various financial products.

Response rate

Every effort was made to achieve the maximum possible coverage, taking cost, timing and other factors into account. A coverage rate of 85% was achieved in the national survey and the 15% of the country that was not covered consisted of areas that were either very remote (and difficult to travel to) or that had extremely small populations.

Sampling error estimates

The margin of error is approximately ±5 percentage points and the 95 percent level of confidence.

The GRID3 settlement extents characterizes building density into three (3) classes: built-up areas (bua_extents), small settlement areas (ssa_extents), and hamlets (hamlet_extents) (Inuwa 2014). These three classes of settlement agglomerations are presented below:Built-up areas (BUAs) are generally areas of urbanization with moderately-to-densely-spaced buildings and a visible grid of streets and blocks. Built-up areas are characterized as polygons containing 13 or more buildings across an area greater than or equal to 400,000 square meters. Small settlements (SSAs) are settled areas of permanently inhabited structures and compounds of roughly a few hundred to a few thousand inhabitants. The housing pattern in SSAs is an assemblage of family compounds adjoining other similar habitations. Small settlement areas are characterized as polygons containing 50 or more buildings across an area less than 400,000 square meters. Hamlets are collections of several compounds or sleeping houses in isolation from small settlements or urban areas. Hamlets are characterized as polygons containing between 1 and 49 buildings across an area less than 400,000 square meters.For full methodological details please explore the data release statement available for download here.Population AttributesThe associated population estimates for the Settlement Extents datasets are derived from two WorldPop high resolution data sources. The WorldPop Top-down constrained population estimates 2020 (Population) uses, for each country, the highest admin level official population totals of the 2000 and 2010 census rounds, that are publicly available and can be mapped to associated boundaries, and projects them to 2020. These projected values then disaggregated statistically to 100x100m resolution using a set of detailed geospatial datasets to disaggregate them to grid cell-based counts. The estimates are constrained to settlements based on the satellite-derived building footprint data from Maxar/ecopia for the 51 African countries, and based on a built settlement growth model of WorldPop for the remaining countries. The Population Counts / Constrained Individual countries 2020 UN adjusted (100m resolution) population estimates (Pop_UN_adj) recognizes that the United Nations produce their own estimates of national population totals. WorldPop, in order to provide flexibility to users, adjusted the number of people per pixel of its top-down constrained population estimates nationally to match the corresponding official United Nations population estimates (i.e. 2019 Revision of World Population Prospects). "Population Counts / Constrained Individual countries 2020 (100m resolution)" & "Population Counts / Constrained Individual countries 2020 UN adjusted (100m resolution)" derived from WorldPop.orgThe GRID3 population estimates (pop_wp1_2) are based on the most recent and best available data of that country and were calculated using the random forest-based dasymetric mapping approach, using the random forest algorithm, to produce a gridded population density data set. This weighting layer was subsequently used to dasymetrically disaggregate population counts from district level totals into grid cells, based on those grid cells which were deemed “settled”. District level population totals from the 2017 Census were downloaded from INE’s website (https://www.ine.gov.mz/iv-rgph-2017). Please, read the relevant data documentation on the WorldPop open Data Repository (https://wopr.worldpop.org/?MOZ/Population).For more information about WorldPop's methods, see:● WorldPop: Methods for Gridded Population Estimate Datasets● WorldPop: Top-down estimation modelling: Constrained vs Unconstrained Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Burkina Faso Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-d023-ws42 . Accessed DAY MONTH YEAR

As of 2023, Eastern Africa was the region with the largest population in Africa, with around 485 million inhabitants. On the contrary, Southern Africa was the least populous area and counted approximately 69 million people. In 2021, the total population of the African continent exceeded 1.36 billion.

This dataset presents a fine-grained population map of Rwanda with a resolution of 100 meters for 2020, generated using the POMELO super-resolution technique that is based on deep learning. Please refer to our Nature Scientific Reports publication for more details.

Background: Traditionally, many countries, including those in sub-Saharan Africa, rely on aggregated census data over expansive spatial units, which are not always timely or accurate. The need for detailed population maps is paramount in several sectors, including urban development, environmental supervision, public health, and humanitarian initiatives. Addressing this gap, the POMELO methodology leverages coarse census data in conjunction with open geodata to produce high precision population maps.

Key Features: Resolution: The map offers a granular view with a 100m ground sampling distance, providing intricate details about population distributions in Rwanda. Data Sources: Utilizing a combination of projected admisistrative census data (UN), and supplementing it with open geodata. Reliability: In comparative experiments conducted in sub-Saharan Africa, POMELO's ability to disaggregate coarse census counts achieved R2 values of 85-89%. Furthermore, its potential to predict population numbers without any census data reached accuracy levels of 48-69%.

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

This dataset provides values for CORRUPTION RANK reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

In 2023, Burundi and Niger had the highest share of their populations living in rural areas in Africa, with approximately 85 percent and 83 percent, respectively. Rwanda and Malawi followed, each with around 82 percent. In contrast, Gabon and Libya were the countries with lowest share of rural inhabitants on the continent.

In 2022, the population density in Central African Republic remained nearly unchanged at around 8.18 inhabitants per square kilometer. In comparison to 2021, the population density decreased not significantly by 0.03 inhabitants per square kilometer (-0.37 percent). Population density refers to the number of people living in a certain country or area, given as an average per square kilometer. It is calculated by dividing the total midyear population by the total land area.Find more key insights for the population density in countries like Republic of the Congo and Cameroon.

Abstract

The Future of African Remittances (FAR) team conducted research on remittance flows to measure and understand the remittance process in sub-Saharan Africa. This ambitious and important research is initially focused on three countries in East Africa - Ethiopia, Kenya and Uganda.

In order to glean insights into the remittance process in the three designated countries, the World Bank designed a two-phase survey process. Phase 1 involved conducting a national survey in each of the three countries. The purpose of the first phase of research was to collect a large representative sample of the adult population in each country. The national surveys provide important baseline data about international remittance flows including: an estimate of the percent of the total adult population that regularly receives remittances, the average amount of each remittance received, most common methods of receipt and top sending countries. Additionally, through the analysis of the national survey results, World Bank was able to identify areas of each country that have high concentrations of international remittance recipients. This important piece of information guided Phase 2 of the research - surveys of remittance receivers in each country. Whereas the national surveys aimed to collect general data about the remittance process, the surveys of remittance recipients allowed for the collection of more detailed data about the remittance process itself, how remittances are used, the relationship between sender and receiver, and interest in various financial products.

The results of this research will not only provide estimates of total annual amounts of remittances for each country, but also will tell us the percentage of the population in each country that is involved in the international remittance process. Furthermore, it will offer insights as to the degree to which Ethiopians, Kenyans and Ugandans depend on international remittances and how the money is used, saved and/or invested. Results will also measure interest in financial products that, if utilized, can significantly impact the financial well-being of the population and the overall economic stability of each country.

Geographic coverage

National Coverage

Analysis unit

Households Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

General:

The total samples were compiled utilizing multi-stage stratified random sampling through respondent selection. Multi-stage random sampling ensured that a random sample of adults was collected in each country. First, after stratifying the population of each country by region and population density, sampling points (SPs) were determined. SPs were then randomly selected within each stratum. At each SP, respondents were randomly selected to participate in the survey.

Phase 1:

The first phase consisted of national surveys of the adult population of each country. The three survey samples were designed to be representative of the adult populations of these three countries. World Bank coordinated and oversaw all aspects of the sampling and interviewing process. A team of local field experts was hired in each country to conduct the actual interviews. All interviewers were professionally trained and supervised by research personnel. In this phase of the research, a total of 2011 Ugandan adults were interviewed.

Phase 2:

Once the national surveys were completed, the results were analyzed to determine the areas of concentration of the remittance recipient population, after which the second phase of the project was conducted. This phase of the project included a targeted survey of the remittance recipient population of each of the three East African countries. Sampling Points were established based on the analysis of the national survey data and the identification of areas within each country that showed the highest concentrations of remittances received from relatives abroad in proportion to the sample size of all areas surveyed. Once again, local field experts were hired in each country to conduct the interviews, training and supervision of field operations. Languages of interviews were the same as those employed in Phase 1 and, again, all interviews were conducted in person using the PAPI method. A total of 400 interviews with regular international remittance recipients were completed in each country during August and September of 2010. The margin of error for all three surveys is approximately ±5 percentage points and the 95 percent level of confidence.

Mode of data collection

Face-to-face [f2f]

Research instrument

Phase 1:

This survey consisted of 12 questions that were aimed at helping to identify some of the basic characteristics of the remittance recipient population in each country. Some of the variables included in this survey were - location, age, gender, amount of money received, method of receipt, origin of remittance, etc.

Phase 2:

The survey instrument for Phase 2 consisted of approximately 35 questions and included a number of variables aimed at obtaining greater detail about the remittance receiving process including costs, amounts received, information about the sender and the relationship between sender and receiver. Additionally, the survey measured interest in various financial products.

Sampling error estimates

The margin of error is approximately ±5 percentage points and the 95 percent level of confidence.

In 2021, there were around 207 million children aged 0-4 years in Africa. In total, the population aged 17 years and younger amounted to approximately 650 million. In contrast, only approximately 48 million individuals were aged 65 years and older as of the same year. The youngest continent in the world Africa is the continent with the youngest population worldwide. As of 2023, around 40 percent of the population was aged 15 years and younger, compared to a global average of 25 percent. Although the median age on the continent has been increasing annually, it remains low at around 20 years. There are several reasons behind the low median age. One factor is the low life expectancy at birth: On average, the male and female population in Africa live between 61 and 65 years, respectively. In addition, poor healthcare on the continent leads to high mortality, also among children and newborns, while the high fertility rate contributes to lowering the median age. Cross-country demographic differences Africa’s demographic characteristics are not uniform across the continent. The age structure of the population differs significantly from one country to another. For instance, Niger and Uganda have the lowest median age in Africa, at 15.1 and 16.1 years, respectively. Not surprisingly, these countries also register a high crude birth rate. On the other hand, North Africa is the region recording the highest life expectancy at birth, with Algeria leading the ranking in 2023.