These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) project funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom’s Department for International Development (OPP1182408). Project partners include WorldPop at the University of Southampton, 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. The Zambia Statistics Agency supported and facilitated this work, and provided the household survey datasets. The modelling work was led by Claire A. Dooley with support from Douglas R. Leasure. Geospatial data processing was carried out by Heather R. Chamberlain, Claire A. Dooley and Oliver Pannell. Coordination and stakeholder engagement was led by Heather R. Chamberlain and Claire A. Dooley with support from Polly Marshall. Oversight was provided by Andrew J. Tatem and Attila N. Lazar. Note, these data are operational population estimates and are not official government statistics For further details, please, read ZMB_population_v1_0_README.pdf Recommended citation WorldPop (School of Geography and Environmental Science, University of Southampton). 2020. Bottom-up gridded population estimates for Zambia, version 1.0. https://dx.doi.org/10.5258/SOTON/WP00662

These data were produced by the WorldPop Research Group at the University of Southampton. This work was funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom's Department for International Development (OPP1182408). The primary intended use of these data was aiding the BMGF field teams. The modelling work was led by Claire Dooley with support from Chris Jochem and oversight by WorldPop director Andy Tatem and GRID3 lead Attila Lazar. The support of the whole WorldPop group is acknowledged, as well as the our GRID3 partners (UNFPA, Columbia University and Flowminder). We thank the teams at IOM and ACLED for their excellent work in collecting data and making it freely available. This work was supported with funding from the Bill & Melinda Gates Foundation (BMGF) and the United Kingdom’s Department for International Development (DFID). These data may be distributed using a Creative Commons Attribution Share-Alike 4.0 License. DATA DESCRIPTION This dataset provides population estimates for each settled 100m grid square in South Sudan. The grid square values were derived using the National Bureau of Statistics’ 2019 population projection estimates that were adjusted to account for displacement of people. The locations people have been displaced to were directly obtained from IOM’s Displacement Tracking Matrix (DTM). The locations people have been displaced from were derived using DTM and the Armed Conflict Locations and Events Database (ACLED). Numbers of displaced people per location were calculated using recorded numbers of international refugees and internally displaced persons. For further details, please, read SSD_population_v1_0_README.pdf Recommended citation WorldPop (School of Geography and Environmental Science, University of Southampton). 2020. South Sudan 2019 gridded population estimates from census projections adjusted for displacement, version 1.0. https://dx.doi.org/10.5258/SOTON/WP00659

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 (OPP1182408). 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. Oliver Pannell (WorldPop) supported the generation of inputs for the application of the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). The disaggregation was done by Maksym Bondarenko (WorldPop), using the Random Forests population modelling R scripts (Bondarenko et al., 2020), with oversight from Alessandro Sorichetta (WorldPop). Doug Leasure (WorldPop) prepared the mastergrid, tiles, and SQLite database. The sections-level administrative boundaries were provided by Jolynn Schmidt and Eniko Kelly-Voicu (CIESIN). The whole WorldPop group and GRID3 partners are acknowledged for overall project support. This dataset is jointly owned between University of Southampton and Statistics Sierra Leone. These data may be distributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) license. For further details, please, read SLE_population_v1_0_README.pd Recommended citation WorldPop and Statistics Sierra Leone. 2020. Census disaggregated gridded population estimates for Sierra Leone (2015), version 1.0. University of Southampton. doi:10.5258/SOTON/WP00668

This data release includes gridded population estimates (~100 m grid cells) with national coverage for Nigeria, along with estimates of the number of people belonging to individual age-sex groups. These population estimates represent the time period 2016 to 2017 corresponding to when the household surveys were conducted. Populations were mapped into areas where residential settlements were detected based on satellite imagery mostly from 2014. The 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 (OPP1182408). Project partners included the United Nations Population Fund, Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation. Statistical modellingwas led by Doug Leasure and Chris Jochem with oversight from Andy Tatem. In-country implementation was led by Tracy Adole. Oak Ridge National Laboratories (ORNL), eHealth Africa, and the Bill and Melinda Gates Foundation collected microcensus data and produced the settlement map used as inputs for this work. The whole WorldPop group and GRID3 partners are acknowledged for overall project support. RELEASE CONTENT NGA_population_v1_2_gridded.zip NGA_population_v1_2_admin.zip NGA_population_v1_2_sql.sql NGA_population_v1_2_mastergrid.tif NGA_population_v1_2_tiles.zip NGA_population_v1_2_agesex.zip NGA_population_v1_2_methods.zip LICENSE These data (1-6) may be redistributed using a Creative Commons Attribution Share-Alike 4.0 License. The methods documentation (7) may be redistributed using a Creative Commons Attribution 4.0 License. Recommended citations WorldPop. 2019. Bottom-up gridded population estimates for Nigeria, version 1.2. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00655 WorldPop. 2020. Bottom-up gridded population estimates for individual age-sex groups in Nigeria, version 1.2.1. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00661 Leasure DR, Jochem WC, Weber EM, Seaman V, Tatem AJ. 2020. National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty. Proceedings of the National Academy of Sciences. doi:10.1073/pnas.1913050117 For further details, please, read NGA_population_v1_2_README.pdf

These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) project funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom Foreign, Commonwealth & Development Office (OPP1182425). Project partners include WorldPop at the University of Southampton, 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. This work provides an estimate of the geographic distribution of the population of Mozambique in 2017. The outputs are intended as an interim population product to support ongoing development and operations work until such time as the official 2017 Population and Housing Census results are available in a spatial gridded format. At that time, this interim gridded population layer will be superseded and users will be advised to use the official gridded population release from INE. For further details, please, read MOZ_population_v1_1_README.pdf Recommended citation Bondarenko M, Jones P, Leasure D, Lazar AN, Tatem AJ. 2020. Census disaggregated gridded population estimates for Mozambique (2017), version 1.1. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00672

These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) project funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom Foreign, Commonwealth & Development Office (OPP1182425). Project partners include WorldPop at the University of Southampton, 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. The modelling work was led by Gianluca Boo and Edith Darin with the support from Douglas R. Leasure and Claire A. Dooley. Coordination was provided by Heather R. Chamberlain and oversight by Andrew J. Tatem and Attila N. Lazar. The support of the whole WorldPop Research Group is acknowledged. The UCLA-DRC Health Research and Training Program, the Kinshasa School of Public Health (KSPH), and the Bureau Central du Recensement (BCR) coordinated and conducted the two microcensus rounds. The Oak Ridge National Laboratory contributed to the first round of microcensus. We acknowledge the contribution of the many individuals within these institutions. Recommended citation: Boo G, Darin E, Leasure DR, Dooley CA, Chamberlain HR, Lazar AN, Tatem AJ. 2020. Modelled gridded population estimates for the Kinshasa, Kongo-Central, Kwango, Kwilu, and Mai-Ndombe provinces in the Democratic Republic of the Congo, version 2.0. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00669

These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) project funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom Foreign, Commonwealth & Development Office (OPP1182425). Project partners include WorldPop at the University of Southampton, 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. The Burkina Faso Institut National de la Statistique et de la Démographie supported, facilitated this work, reviewed the results and provided the census database. The modelling work, geospatial data processing, and stakeholder engagement was led by Edith Darin. Support for the statistical modelling was provided by Gianluca Boo, Claire A. Dooley, Douglas R. Leasure and Chris W. Jochem. Support for the engagement work and review of the methods was offered by Mathias Kuépié. Oversight was done by Andrew J. Tatem and Attila N. Lazar. Recommended citation: WorldPop and Institut National de la Statistique et de la Démographie du Burkina Faso. 2021. Census based gridded population estimates for Burkina Faso (2019), version 1.0. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00687

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) programme in Mauritius. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Mauritius Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-mzqk-th30. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) programme in Cabo Verde. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Cabo Verde Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-v430-5w77. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) programme in Angola. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 South Africa Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-g5mw-3b13. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Seychelles. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Seychelles Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-zpeq-3995. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in São Tomé and Príncipe. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 São Tomé and Príncipe Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-nc1k-4z96. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Malawi. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Malawi Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-n4yb-5a62. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Madagascar. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Madagascar Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-t9xn-k215. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Gabon. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Gabon Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-hay7-2n57. Accessed DAY MONTH YEAR

This is an updated version of the previous V01 Alpha release. This update was made to increase the buffer size around the hamlets to align with the population grid and be consistent with the other settlement extents published by GRID3. This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative inMozambique. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Data Set Citation : Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Mozambique Settlement Extents, V02 Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building footprints “Digitize Africa data © 2020 Maxar Technologies, Ecopia.AI". DOI: https://doi.org/10.7916/d8-37sa-gy34. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Réunion. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Réunion Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-6np8-f730 . Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Mauritania. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Mauritania Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-hzv3-f435 . Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Senegal. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Senegal Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/doi:10.7916/d8-x8gh-ms26 . Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Togo. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Togo Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-qdxc-0c73 . Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Tanzania. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Tanzania Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-ve7a-dm77 . Accessed DAY MONTH YEAR

The dataset consists of health facility points with name, location, health zone and health area attributes in the provinces of Haut-Lomami and Tanganyika in the Democratic Republic of the Congo (DRC). This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

GRID3 DRC Haut-Lomami and Tanganyika Health Catchment Area Boundaries Version 01 (Beta) dataset consists of two layers: health area boundaries and health zone boundaries. This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Ethiopia. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Ethiopia Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-y936-w110. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Kenya. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Kenya Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-3tn0-1686. Accessed DAY MONTH YEAR