The dataset contains information on IDPs and returnees at the subnational level.

The Registered IDP Area Baseline Assessment provides regular data on the number and geographic location of officially registered internally displaced people (IDPs). The data collected for the Area Baseline Assessment Round 39 reflects the officially registered internally displaced population (IDP) displaced since 24 February 2022, as of 31 December 2024, across 23 oblasts and Kyiv City, as recorded by IOM.

The dataset contains IDPs, Returnees and Refugees at sub national level with information on IDPs in camps and host communities. IOM set up and rolled out the first round of the DTM in November 2015 with the objective of providing regular, accurate and updated information on displaced populations within the Far North region of Cameroon to better support the response of the Government of Cameroon and the humanitarian community.

The dataset contains IDPs individuals and households at admin2 level. IOM has been developing a Displacement Tracking Matrix (DTM) since May 2015 aimed at effectively monitoring and evaluating the flows of Burundian IDPs and providing accurate information on the current IDP situation. The DTM in Burundi has been successfully used in 2014, upon the request of the humanitarian community and the GoB when some areas of Bujumbura were flooded, which caused displacement. This tool allowed registering IDPs in four IDP sites and in host families in four locations and identifying their humanitarian needs. The dataset includes returnees from abroad who are still displaced in the country. They are categorized as IDPs due to their continued displacement within the country.

The dataset contains number of migrants in Libya at sub national level. The dataset also contains nationality of the migrants and their needs.

A baseline assessment is a sub-component of mobility tracking. It aims to collect data on IDP, migrant or returnee population presence in a defined administrative area of the country.

The dataset contains number of people displaced and returnees at village level in North Kivu province. The dataset also contains needs of the displaced and returned people, reason and time of displacement.

The dataset contains IDPs, returnees at sub national level. The dataset also has reason of displacement, origin and dates of multiple displacements. The context of displacement in Mali remains complex and fluid. Movements of IDPs currently residing in the southern regions to the northern regions continue to be reported. While some have indicated that they have returned definitively, other IDPs say they travel back and forth between the place of travel and the place of origin.

The dataset contains number of IDPs and Households at quartier level.

The increase of security incidents in northern Mozambique since 2017 resulted in population displacement as well as subsequent humanitarian needs in virtually every humanitarian sector. To better understand the scope of displacement and needs of displaced populations, and in light of the intensification of the situation, the International Organization for Migration (IOM) activated its Displacement Tracking Matrix (DTM) in the Cabo Delgado province in February 2019.

The dataset contains IDPs, Returnees and host community at sub-national level.

The datasets cover the period of 21 June - 30 December and includes the states mostly affected by displacement including Benue,Nasarawa, Kaduna, Kano, Katsina, Plateau, Sokoto and Zamfara.

The data collection exercise conducted in the villages of Aru, Djugu, Irumu, Mahagi and Mambasa territories. It contains number of IDPs, returnees and theri needs.

This Data is about IDP, returnees from CAR (previous IDP) and returnees from other countries repartition by origin and period of displacement and between 2013 and the date of assessment. Evaluation has been run in 6 prefectures (admin1), 16 sub-prefectures (admin2) and 367 localities.

The dataset contains number of people displaced and returnees at village level in South Kivu province. The dataset also contains needs of the displaced and returned people, reason and time of displacement.

The dataset contains number of people displaced and returnees at village level in Tanganyika province. The dataset also contains needs of the displaced and returned people, reason and time of displacement.

The dataset aims to collect data on population presence, living conditions and needs in a particular displacement location or community.

The dataset contains IDPs, returnees at sub national level.

This datasets has IDPs, Household & Returnees data at Admin3 level gathered through DTM Mobility Tracking Assessment. In the context of the political instability that has prevailed since the uprising in Libya (October 2011) and culminated in the collapse of a fragile central authority accompanied by fragmentation and infighting among myriads of militias, with continued fighting since the mid-2014 escalations, estimates indicate that the number of Internally Displaced Per-sons (IDPs) in Libya has exceeded 400,000 individuals, some eight percent of the total population (HNO, September 2015). While the country struggles to achieve and maintain stability, thousands of migrants are also taking journeys to and through Libya in a desperate bid to seek a better life in Europe. These migrants are exposed to risks of being trafficked and exploited while traveling through dangerous routes in deserts and territories controlled by different armed groups, as well as dying during attempts to cross the Mediterranean Sea. However, there has been no standardized mechanism in place to verify and regularly update IDP and migrant numbers. Given that most humanitarian and international organizations operate remotely from Tunis since mid-July 2014 due to the deteriorating security situation, maintaining access to reliable and updated data on the humanitarian situation in Libya has been challenging.

The dataset contains number of people displaced and returnees at village level in Kasai Central province. The dataset also contains needs of the displaced and returned people, reason and time of displacement.

Data set has IDPs, Households, geographic locations and reasons of displacement etc. In response to the need for accurate information on internally displaced persons (IDPs) in Nigeria, the International Organization for Migration (IOM) began implementing the Displacement Tracking Matrix (DTM) project in July 2014. The project is supporting the Government of Nigeria and other humanitarian response partners to conduct IDPs assessments in a systematic way as well as to establish a profile of the IDP population.

Dataset has IDPs, Households, challenges faced by IDPs etc. On 11-13 April, severe flooding and landslides caused by heavy rainfall affected southern and south-eastern South Africa. In response to the need for accurate information on internally displaced persons (IDPs) in South Africa, the International Organization for Migration (IOM) in partnership with the South Africa Red Cross Society and in coordination with provincial and local authorities, deployed teams from June 2022 to conduct baseline assessments at ward level. The project is supporting the Government of South Africa and other humanitarian response partners to conduct IDPs assessments in a systematic way as well as to establish a profile of the IDP population.

The dataset contains number of IDPs, Returnees (households and individuals) at sub national levels.

The dataset contains number of IDPs, Returnees and host communities and their needs at sub national level.

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