The Database and dashboard covers the regional humanitarian situation including targets, results and funding all as of December 18 2018 for entire Southern and Eastern Africa.
WorldPop produces different types of gridded population count datasets, depending on the methods used and end application.
Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.
A description of the modelling methods used for age and sex structures can be found in
Tatem et al and
Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined
here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
Data for earlier dates is available directly from WorldPop.
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). https://dx.doi.org/10.5258/SOTON/WP00646
The Database and dashboard covers the regional humanitarian situation including targets, results and funding all as of July 2018 for entire Southern and Eastern Africa.
Water Sources in Northern Uganda - based on GPS coordinates of water points (approx >80%) collected (in 2009, 2010, and 2011) by UNOCHA from different stake-holders working in Northern part of Uganda, such as WASH cluster leads, humanitarian partners, and local government. The location of the water points are re-verified by District Water Office (local government) before analysing and publishing Water Coverage and its Accessibility level against national standard.
Education Facility Centres in Northern Uganda - based on GPS coordinates of the centers collected (in 2009, 2010, and 2011) by UNOCHA from different stake-holders working in Northern part of Uganda, such as cluster leads, humanitarian partners, and local government. The location of the education facilities are re-verified by District Education Office (local government) before analysing and publishing Education Service Accessibility level against national standard.
Health Facility Centres in Northern Uganda - based on GPS coordinates of the centers collected (in 2009, 2010, and 2011) by UNOCHA from different stake-holders working in Northern part of Uganda, such as health cluster leads, humanitarian partners, and local government. The location of the health centres are re-verified by District Health Office (local government) before analysing and publishing Health Service Accessibility level against national standard.
IDP Camp locations in Northern Uganda - based on GPS coordinates of IDP locations collected (in 2008 and 2009) by UNOCHA from different stake-holders working in Northern part of Uganda, such as Protection cluster leads, humanitarian partners, and local government. The location of the IDP camps are re-verified by District Office (local government). Note: Almost all IDPs in Uganda already moved to return sites. Please check Protection cluster or concern authority in Uganda for updated info on IDPs.
Road network in Uganda - based on different sources collected (in 2008, 2009, and 2010) by UNOCHA. Agreed to share publicly and authorized by Geo-IM working group network in Uganda chaired by UBOS and UNOCHA as Secretariat.
District Admin Centre locations based on 2006 data provided by Ugandan Bureau of Statistics (UBOS), Government of Uganda. Agreed to share publicly and authorized by Geo-IM Working group chaired by UBOS and UNOCHA as Secretariat.
Landuse in Uganda - extracted from 2006 UBOS provided parish boundaries with land cover information. Agreed to share publicly and authorized by Geo-IM working group network in Uganda chaired by UBOS and UNOCHA as Secretariat.
Uganda County Boundary shape file -Admin Level 3: based on 2006 data provided by Ugandan Bureau of Statistics (UBOS), Government of Uganda. Agreed to share publicly and authorized by Geo-IM Working group chaired by UBOS and UNOCHA as Secretariat.
Instructions: uganda_county2006.zip
Sub-County Boundary shape file - Admin Level 4: based on 2006 data provided by Ugandan Bureau of Statistics (UBOS), Government of Uganda. Agreed to share publicly and authorized by Geo-IM Working group chaired by UBOS and UNOCHA as Secretariat. The dataset has been updated recently as Government of Uganda changed Admin boundaries to create some new districts in 2010.
Greater Horn of Africa Countries (Shapefile and feature layer) shared by ICPAC
Created: April 27, 2016
[COD tag removed by Tom Haythornthwaite 2018 05 02.]
The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al and James et al..
Data for earlier dates is available directly from WorldPop.
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2017. Uganda 1km pregnancies. Version 2.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00486
The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of live births to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age and age-specific fertility rates to map the estimated distributions of births for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al. and James et al..
Data for earlier dates is available directly from WorldPop.
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2017. Uganda 1km births. Version 2.0 2015 estimates of numbers of live births per grid square, with national totals adjusted to match UN national estimates on numbers of live births (http://esa.un.org/wpp/). DOI: 10.5258/SOTON/WP00378