The UNHCR Results Monitoring Surveys (RMS) is a household-level survey on people with and for whom UNHCR works or who benefit from direct or indirect assistance provided by UNHCR, including refugees and asylum seekers, internally displaced persons, returnees, stateless and others of concern. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR's multi-year strategies to key stakeholders. This RMS took place in Peru from April 2023 to May 2023 at national level.

The UNHCR Results Monitoring Surveys (RMS) is a household-level survey on people with and for whom UNHCR works or who benefit from direct or indirect assistance provided by UNHCR, including refugees and asylum seekers, internally displaced persons, returnees, stateless and others of concern. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR's multi-year strategies to key stakeholders. This RMS took place in Guatemala in July 2022 at national level.

The UNHCR Results Monitoring Surveys (RMS) is a household-level survey on people with and for whom UNHCR works or who benefit from direct or indirect assistance provided by UNHCR, including refugees and asylum seekers, internally displaced persons, returnees, stateless and others of concern. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR's multi-year strategies to key stakeholders. This RMS took place in Trinidad and Tobago from October 2022 to November 2022 at national level.

The UNHCR Results Monitoring Surveys (RMS) is a household-level survey on people with and for whom UNHCR works or who benefit from direct or indirect assistance provided by UNHCR, including refugees and asylum seekers, internally displaced persons, returnees, stateless and others of concern. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR’s multi-year strategies to key stakeholders. This RMS took place in Brazil from September 2022 to November 2022 at national level.

The UNHCR Results Monitoring Survey (RMS) has the objective of monitoring the impact and outcome of UNHCR's assistance on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR’s multi-year strategies to key stakeholders. UNHCR Iraq has authorized IMPACT to undertake a Results Monitoring Survey targeting IDP/returnee and refugee families, including beneficiaries and non-beneficiaries, throughout Iraq in 2022 to assist in internal monitoring of results and impact indicators. This survey will help UNHCR create and execute successful interventions for Iraqi IDP/returnee and refugee families by providing vital information on their well-being and living situations.

The UNHCR Results Monitoring Survey (RMS) is a household-level survey covering people who are directly or indirectly assisted by UNHCR, including refugees and asylum seekers, internally displaced persons, returnees, stateless and others of concern. Additionally, in the Republic of Korea the survey covered rejected Asylum-Seekers. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR’s multi-year strategies to key stakeholders. The RMS can be implemented in any operational context. A standard structured questionnaire has been developed for the RMS, which can be conducted as a stand-alone survey or flexibly integrated with other data collection exercises. The questionnaire was adapted to the Korean context and programme objectives by removing, e.g. questions related to camp settings. Questions related to the rejected asylum seekers in need of protection and family members abroad were added. The data includes indicators collected at both the household and individual (household-member) level. The survey covered 424 household amounting to 950 individuals.

These data consist of modelled gridded population estimates produced at a spatial resolution of approximately 100m across the Haut-Katanga, Haut-Lomami, Ituri, Kasaï, Kasaï-Oriental, Lomami and Sud-Kivu provinces in the Democratic Republic of the Congo (DRC). The estimates comprise total population counts created using a Bayesian statistical model and post-hoc breakdowns in 40 age and sex groups. The main input data were derived from a dedicated microcensus survey carried out in the targeted provinces throughout March and April 2021. The microcensus was led by the Flowminder Foundation, the École de Santé Publique de Kinshasa, the WorldPop Research Group at the University of Southampton and the Bureau Central du Recensement, which is part of the Institut National de la Statistique of the DRC. Other essential input data include metrics derived from building footprints, which were automatically delineated by Ecopia.AI in 2021 using satellite imagery collected by Maxar Technologies between 2010 and 2021. The modelled population estimates represent the period of the microcensus but their consistency may be impacted by the accuracy of the building footprints, particularly in the areas where the satellite imagery used for automatic delineation was outdated. These data were produced by the WorldPop Research Group at the University of Southampton as part of the GRID3 Mapping for Health Project. This project was delivered under the leadership of the Ministry of Public Health, Hygiene and Prevention of the DRC and funded by Gavi, the Vaccine Alliance (RM 867204 20A2). The project was led by the Flowminder Foundation and the Center for International Earth Science Information Network (CIESIN) at Columbia University, in collaboration with the WorldPop Research Group at the University of Southampton and national partners including, but not limited to, the École de Santé Publique de Kinshasa and both the Bureau Central du Recensement and the Institut National de la Statistique. This work was a continuation of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) programme funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom’s Foreign, Commonwealth & Development Office (INV 009579, formerly OPP 1182425). The study was approved by the Faculty Ethics Committee of the University of Southampton (ERGO II 62716). The production of these data was led by Gianluca Boo (WorldPop](https://www.worldpop.org/) ) with support from Roland Hosner (Flowminder Foundation), Pierre Z Akilimali (École de Santé Publique de Kinshasa), Edith Darin (WorldPop), Heather R Chamberlain (WorldPop), Warren C Jochem (WorldPop), Patricia Jones (WorldPop), Roger Shulungu Runika (Institut National de la Statistique), Henri Marie Kazadi Mutombo (Bureau Central du Recensement), Attila N Lazar (WorldPop) and Andrew J Tatem (WorldPop). The authors acknowledge the support of their respective institutions in the completion of this work. Recommended citation: G Boo, R Hosner, PZ Akilimali, E Darin, HR Chamberlain, WC Jochem, P Jones, R Shulungu Runika, HM Kazadi Mutombo, AN Lazar and AJ Tatem. 2021. Modelled gridded population estimates for the HautKatanga, Haut-Lomami, Ituri, Kasaï, Kasaï-Oriental, Lomami and Sud-Kivu provinces in the Democratic Republic of the Congo (2021), version 3.0. WorldPop, University of Southampton, Flowminder Foundation, École de Santé Publique de Kinshasa, Bureau Central du Recensement and Institut National de la Statistique. doi:10.5258/SOTON/WP00720

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 Foreign, Commonwealth & Development Office (INV 009579, formerly OPP 1182425). Project partners included the United Nations Population Fund, Center for International Earth Science Information Network in the Columbia Climate School at Columbia University, and the Flowminder Foundation. Thomas Abbott (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Heather Chamberlain, Sarchil Qader, and Attila N Lazar advised on the modelling procedure. The Institut National de la Statistique du Niger (INS) released the census-based total population projection using the results of the 2012 census of population and digital Commune boundaries. Engagement with INS was lead by Mathias Kuepie (UNFPA). The work was verseen by Attila N. Lazar and Andy J Tatem. For further details, please, read NER_population_v1_0_README.pdf

This data release provides gridded population estimates (spatial resolution of 3 arc-seconds, approximately 100 m grid cells) with national coverage for Nigeria, along with estimates of the number of people belonging to various age-sex groups. Version 2.0 is an update to the previous version 1.2 gridded population estimates and is based on more recent and detailed settlement information and a different regional boundary definition. These model-based population estimates most likely represent the time period around 2019, corresponding to the period when the satellite imagery was processed to generate building footprints. Populations are mapped only into areas where residential settlements are predicted. These data were produced by the WorldPop Research Group at the University of Southampton in collaboration with the National Population Commission of Nigeria. This work was part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3 ) programme with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Foreign, Commonwealth & Development Office (INV 009579, formerly OPP 1182425). Project partners included the United Nations Population Fund, Center for International Earth Science Information Network (CIESIN), a center within the Columbia Climate School at Columbia University, and the Flowminder Foundation. Statistical modelling was led by Chris Jochem and Doug Leasure additional support and oversight from Attila Lazar and Andy Tatem. Chris Lloyd provided the residential building classification. The microcensus data were originally collected by eHealth Africa and Oak Ridge National Laboratory with support from the Bill and Melinda Gates Foundation. The WorldPop grou and GRID3 partners are acknowledged for their project support. RELEASE CONTENT NGA_population_v2_0_gridded.zip NGA_population_v2_0_admin.zip NGA_population_v2_0_sql.sql NGA_population_v2_0_mastergrid.tif NGA_population_v2_0_tiles.zip NGA_population_v2_0_agesex.zip LICENSE These data (1-6) may be redistributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License. Recommended citations WorldPop and National Population Commission of Nigeria. 2021. Bottom-up gridded population estimates for Nigeria, version 2.0. WorldPop, University of Southampton. doi: 10.5258/SOTON/WP00729. For further details, please, read NGA_population_v2_0_README.pdf

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. 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