Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through integrating census, survey, satellite and GIS data sets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. Uganda data available from WorldPop here.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Uganda: (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).

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

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

This map shows the average household size in Uganda in 2023, in a multiscale map (Country, Region, and District). Nationally, the average household size is 4.5 people per household. It is calculated by dividing the household population by total households.The pop-up is configured to show the following information at each geography level:Average household size (people per household)Total populationTotal householdsCounts of population by marital status The source of this data is Michael Bauer Research. The vintage of the data is 2023. This item was last updated in October, 2023 and is updated every 12-18 months as new annual figures are offered.Additional Esri Resources:Esri DemographicsThis item is for visualization purposes only and cannot be exported or used in analysis.We would love to hear from you. If you have any feedback regarding this item or Esri Demographics, please let us know.Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

The dataset provides information on the distribution of population by disagregatd down to Sub-County level as per the National Census conducted by the Uganda Bureau of Statistics (UBOS) in August 2014. By then Uganda had a total population of 34,856,813 people and was growing at a rate of 3.3% per annum.

Table content - Year - Indicator - Sex - District - Value - Flag - Unit

Population Growth Rate 2002

GAFSP funds in Uganda support the Agriculture Sector Development Strategy and Investment Plan (DSIP). Specifically, the funds will target vulnerable smallholder households to help increase and diversify production of nutritious foods, improve nutrition knowledge and practices (especially in the "critical window" of conception through 23 months), and strengthen coordination mechanisms between agriculture, health, and education sectors to address cross-cutting nutrition issues at national and local government levels. This interactive map of Uganda highlights the districts targeted by the project. This map overlays sub-national poverty data and demographic indicators relevant to the project. The project will target the poorest sub-counties in 15 districts, based on high stunting and low dietary diversity. For the first phase of implementation five districts were selected: Bushenyi, Nebbi, Ntugamo, Maracha and Namutumba. For the second phase of implementation 10 more districts will be selected from the following list of priority districts: Isingiro, Yumbe, Arua, Bigiri, Iganga, Kygegwa, Kiryandongo, Kamwenge, Masindi, Kyenjojo, Kabarole, Kabale, Hoima, Kibale and Kaese. Synergies between the project and the Agriculture Cluster Development Project will ensure greater coverage of beneficiaries and will provide a scalable model integrating the two projects. Data Sources:Uganda Multisectoral Food Security and Nutrition Project priority districts.Source: World Bank and GAFSP Documents. Poverty (Proportion of population below the poverty line) (2012-2013): Proportion of the population living on less than UGX 1,387 per adult per day. Source: Uganda Bureau of Statistics UBOS. "Uganda National Household Survey 2012/13" Malnutrition (Proportion of underweight children under 5 years) (2011): Prevalence of severely underweight children is the percentage of children ages 0-59 months whose weight for age is less than minus 3 standard deviations below the median weight for age of the international reference population.Source: Uganda Bureau of Statistics UBOS. "Uganda Demographic and Health Survey 2011". MEASURE DHS (Demographic and Health Surveys) Project is responsible for collecting and disseminating accurate, nationally representative data on health and population in developing countries. The project is implemented by Macro International, Inc. and is funded by the United States Agency for International Development (USAID) with contributions from other donors such as UNICEF, UNFPA, WHO, UNAIDS. Population: (Total population) (2014): Total 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. Source: Uganda Bureau of Statistics UBOS. “National Population and Housing Census 2014 - Provisional Results Nov 2014”. Population Density (Persons per square kilometer) (2014): Total population divided by land area in square kilometers.Source: Uganda Bureau of Statistics UBOS. “National Population and Housing Census 2014 - Provisional Results Nov 2014”. Market Centers: Key market centers for retail, assembly and/ or wholesale of agricultural products. FEWS NET Reference markets.Source: FEWS Net. The Famine Early Warning Systems Network (FEWS NET) is a USAID-funded activity that collaborates with international, regional and national partners to provide timely and rigorous early warning and vulnerability information on emerging and evolving food security issues. Geographic boundaries.

The maps displayed on the GAFSP web site are for reference only. The boundaries, colors, denominations and any other information shown on these maps do not imply, on the part of GAFSP (and the World Bank Group), any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.

Uganda Region Boundaries provides a 2023 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online.The 2023 boundaries are provided by Michael Bauer Research GmbH. These were published in October 2023. A new layer will be published in 12-18 months. Other administrative boundaries for this country are also available: Country District

the population per subcounty in 2002 taken from the Census

Age and sex structures: WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Tatem et al and Pezzulo et al. The 'Global per country 2000-2020' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020 structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The 'individual countries' datasets represent older efforts to map population age and sex counts for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The 'whole continent' datasets are mosaics of the individual countries datasets. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076).

This map shows the purchasing power per capita in Uganda in 2023, in a multiscale map (Country, Region, and District). Nationally, the purchasing power per capita is 2,332,292 Ugandan shilling. Purchasing Power describes the disposable income (income without taxes and social security contributions, including received transfer payments) of a certain area's population. The figures are in Ugandan shilling (UGX) per capita.The pop-up is configured to show the following information at each geography level:Purchasing power per capitaThe source of this data is Michael Bauer Research. The vintage of the data is 2023. This item was last updated in October, 2023 and is updated every 12-18 months as new annual figures are offered.Additional Esri Resources:Esri DemographicsThis item is for visualization purposes only and cannot be exported or used in analysis.We would love to hear from you. If you have any feedback regarding this item or Esri Demographics, please let us know.Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. This dataset provides index values for small spatial units within urban areas in Uganda. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.

Uganda Country Boundary provides a 2023 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online.The 2023 boundaries are provided by Michael Bauer Research GmbH. These were published in October 2023. A new layer will be published in 12-18 months. Other administrative boundaries for this country are also available: Region District

Abstract

The objectives of the UNHS 1996/97 were as follows: - To provide an integrated data set to understand the mechanisms and effects of the various socio-economic programs and policies on a continuous basis. - To test the methodology and procedures of conducting a Labour Force Survey that was scheduled for 1997/98. - To collect some broad statistics and information that served as a guideline to the planning and execution of a Mortality Survey in 1997/98. - To further meet specific data needs of particular institutions like UNICEF, Ministry of Health in the field of child-health and mother-care. - To further consolidate efforts made in building a permanent national survey capability in the Statistics Department.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Design In spite of a number of limitations, the list of Enumeration Areas (EA's) prepared for the 1991 Population Census, along with maps and data on households and population is the only available sampling frame to be used. The sampling design and procedure for selection of the first stage unit (fsu) were as follows: a) Basically, a stratified multi-stage sampling design was adopted. Each district was a sub-stratum with further sub-stratification as district town, other urban areas and rural areas. There were 102 total strata. There was no further sub-stratification. b) In those districts where information of Enumeration Areas (EA's) with mapping exercise had been completed during 1991 Population Census, there was two stage design with EA's as the first-stage units (fsu) and with households as the second or ultimate stage units. In other districts, a three stage sampling design was adopted with a parish as the fsu. LC 1 as second stage unit (ssu) and a household as the third or ultimate stage unit. c) During UNHS 1996/97, all fsu's was selected afresh and practice of selecting common fsu's from earlier surveys was dispensed with. Fsu's from all the strata was selected with probability proportional to the number of households without replacement. d) The total number of fsu's selected in Uganda as a whole was 624.

For districts without Census Maps fsu was a parish. LC 1's in the selected parishes was listed at the field stage and two LC 1's per parish was selected on the basis of simple random sampling without replacement. All the households in the selected LC 1's or EA's where two stage sampling was used and listed. 10 households selected in the basis of simple random sampling and surveyed for both socio-economic and labour force components. Community survey was done in all the LC 1's selected in three stage sampling and one LC 1 per EA in two stage sampling after listing and selecting one LC 1 on the basis of simple random sampling.

Mode of data collection

Face-to-face [f2f]

Research instrument

The UNHS 1996/97 survey was collected using three questionnaires - i) the listing questionnaire; ii) the labour force and socio-economic questionnaire and iii) the community questionnaire. All the three questionnaires put together covered a wide range of inter-related subjects.

The shapefile represents the administrative divisions of Adjumani district in the North of Uganda as of December 2001. The shapefile divides Adjumani district into 1 county. The county is subdivided into 5 subcounties and one town council. These, in turn have 15 subdivisions that are called parishes. The parishes are further subdivided into 73 villages. We digitized the administrative units from paper maps that we have received from Uganda Bureau of Statistics in Entebbe. The associated population size on village level represents the provisional result of the Uganda census 2002.

Nigeria has the largest population in Africa. As of 2025, the country counted over 237.5 million individuals, whereas Ethiopia, which ranked second, has around 135.5 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 118.4 million people. In terms of inhabitants per square kilometer, Nigeria only ranked seventh, while Mauritius had the highest population density on the whole African continent in 2023. 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 Chad, South Sudan, Somalia, and the Central African Republic, the population increase peaks at over 3.4 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. African cities are also growing at large rates. Indeed, the continent has three megacities and is expected to add four more by 2050. Furthermore, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria, by 2035.

This layer shows the purchasing power per capita in Uganda in 2023, in a multiscale map (Country, Region, and District). Nationally, the purchasing power per capita is 2,332,292 Ugandan shilling. Purchasing Power describes the disposable income (income without taxes and social security contributions, including received transfer payments) of a certain area's population. The figures are in Ugandan shilling (UGX) per capita.The pop-up is configured to show the following information at each geography level:Purchasing power per capitaThe source of this data is Michael Bauer Research. The vintage of the data is 2023. This item was last updated in October, 2023 and is updated every 12-18 months as new annual figures are offered.Additional Esri Resources:Esri DemographicsThis item is for visualization purposes only and cannot be exported or used in analysis.We would love to hear from you. If you have any feedback regarding this item or Esri Demographics, please let us know.Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Abstract

The general objective of the Uganda CFSVA was to provide a baseline assessment of food insecurity and vulnerability in rural households of Uganda in a non-emergency setting, including the characterization of who are the food insecure, how many are there, where do they live, why are they food insecure and what intervention is appropriate to reduce their food insecurity and vulnerability. The specific objectives of the Uganda CFSVA are to: • provide information on food security and nutritional status in rural Uganda; • document the resources accessible to rural households and their resource allocation, including the livelihood and income-earning activities pursued at the household level; • assess rural communities’ exposure to crises and the coping mechanisms they use; • when possible, examine the evolution of food insecurity and vulnerability over time; • evaluate the context (education, health, social structure) and future risks for food security and livelihoods; • establish a typology and geographic distribution of food-insecure and vulnerable households; and • recommend appropriate food and non-food programme interventions to address both contextual and structural problems that affect food security in rural Uganda.

Geographic coverage

Rural national coverage with the exception of Kampala by sub-region

Analysis unit

• Household
• Mother
• Child aged 0-59 months
• Community

Universe

The sample universe for this study was all rural households of Uganda.

Kind of data

Sample survey data [ssd]

Sampling procedure

A multi-stage sampling procedure was used to select households within each stratum. Because a large number of strata were defined (13) and because those strata were designed to be homogeneous, within each stratum, one third of the districts, with a minimum of two districts per stratum, was sampled proportionate to population size using 2002 census data. Figure 1.4-1 presents a map of the resulting 14 strata. The hatch marks highlight the districts that were sampled. The sampling procedure was logistically sounder than a simple random sampling of villages. Strata 14 (Kampala) was not surveyed, as this exercise focused on rural households. Within the selected districts and for each stratum, 20 rural sub-counties were randomly selected proportionate to size. No population data were available at a lower-aggregated level (e.g., villages), so within each sub-county, one village (or camp, where applicable) was randomly selected from a comprehensive list of villages and camps. Annex 3 presents the list of sub-counties and villages that were sampled.

Because comprehensive lists of all the households were not systematically available, interviewers were randomly assigned to “zones” of relative size within the villages or camps, as identified by village or camp leaders. The interviewers were directed to the center of each zone, where they randomly selected a direction in which to walk, and then selected every other household within that area. In each selected household, one adult (at least 15 years or older) was selected to be interviewed. When a selected household or individual was unable to participate, the next available household, or another individual within the selected household, was selected.

The minimum target sample size for each stratum was 200, for a total of 2,600 households. Sample size was determined using the difference-in-proportion formula and was adjusted for design effect due to stratification and multi-stage cluster sampling, using a of 5%, a level of precision of 10% and a design effect of 2. The assumed power was .80. During the data collection, 838 households were empty or refused to participate. Data collection took place from July 29, 2005, to August 29, 2005. The final sample size obtained was 2,987 households. Using the complex sample module of EpiInfo, the average design effect was estimated at 1.5, and the margin of error was within 3%.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two different instruments were used during primary data collection: a household questionnaire and a community questionnaire: 1. The household questionnaire was designed to collect quantitative data in 11 areas: (1) demographics, (2) contextual information, (3) housing and facilities, (4) assets, (5) income, (6) expenditures, (7) food sources and consumption, (8) shocks and food security, (9) HIV/AIDS, (10) maternal health and nutrition (11) child health and nutrition. The instrument was a structured questionnaire using openended questions. Response options were provided to the enumerators but were not read to the respondents. For several questions, respondents were allowed to provide more than one response.

1. Measurements of the height and weight of mothers and children were included in the household questionnaire to assess nutritional status. Standard locally produced height boards for adults and children were used to measure height. UNICEF SECA 890 electronic scales were used to weigh mothers and children.

2. The community questionnaire was structured, open ended and designed to collect qualitative information on (1) demographics, (2) migration, (3) transportation, (4) water and sanitation, (5) education, (6) health, (7) market information, (8) agriculture and animal husbandry, (9) livelihoods, and (10) assistance and food aid. The community questionnaire was intended to contextualize the information collected at the household level. The resulting instrument was a structured, open-ended questionnaire. Response options were not systematically provided to the enumerators. Rather, the enumerators were asked to record exactly what respondents had to say.

The questionnaires were designed in a participatory manner that involved representatives from various agencies active in food security in Uganda. Because of the multiplicity of languages in Uganda, the instruments were not translated into the local languages. Proficiency in both English and the local language of the area being surveyed was one of the criteria for the selection of enumerators. While this may be considered a limitation to the study (e.g., different interviewers may translate the same question in a different way), the relative simplicity of the questions limited the risk of misinterpretation. Prior to the launch of the survey, the instruments were piloted among local experts, randomly selected individuals and a random sample of participants in a non-study site. Necessary revisions were made after each pilot stage.

Cleaning operations

Data entry for the household and community questionnaires was operated by Makerere University. Double data entry was used for the household questionnaire. Data entry used an Access database developed by WFP.

Summary of cassava production across surveyed sites in Uganda.