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

IOM conducted rapid representative surveys of the general population in Ukraine to gather initial insights into internal displacement and mobility flows, and to assess local needs. While Displacement Tracking Matrix tools are being established, this general population survey will serve as a preliminary source to identify areas with high humanitarian needs and to inform the targeting of response aiming to assist the conflict-affected population. The geographical scope of the survey covers all five macro-regions (West, East, North, Center, South, and the city of Kyiv). The probabilistic sample, representative at macro-region level, was constructed through a random‐digit‐dial (RDD) approach, and 2,000 respondents aged 18 and over were interviewed using the computer assisted telephone interviewing (CATI) method. Those currently outside Ukraine were not interviewed. Population estimates assume that children travel together with their adult guardians. The estimates rely on the UNFPA population data for Ukraine, agreed upon as the common population baseline by the humanitarian community.

A village assessment survey (VAS) is a sub-component of mobility tracking. It collects data on returning IDPs, IDPs, returned migrants and host community members. VAS evaluates the absorption capacity of villages to receive returning IDPs with a focus on accessibility of services, livelihoods and reintegration.

The dataset has IDPs households and individuals with age and gender disaggregated data at sub national 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 number of IDPs, Returnees (households and individuals) at sub national levels.

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

The data contains number of IDPs dis-aggregated by gender, age at village level.

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 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 IDPs at sub national level displaced by Cyclone Kenneth

Large-scale flooding and landslides have been triggered in several districts across Nepal following heavy rainfalls in July 2020. From the onset of monsoon on 12 June until 25 July, 130 people lost their lives, 115 were injured and 51 went missing due to floods and landslides according to the National Disaster Risk Reduction and Management Authority.

List of urban and rural settlements in Somalia collected through DTM Baseline 2 (B2) exercise. B2 is a component of the Mobility Tracking which aims to quantify presence of population categories, reasons for displacement, length of displacement and needs within defined locations at a given time. The settlement location is collected through GPS devices. Disclaimer: information on settlement type is still being verified. Settlements in Galmudug and Banadir regions may be revised in the coming months due to final data checks.

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

The dataset contains IDPs and it's 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.

Following the passage of tropical storm Ana across southern Malawi, the districts of Chikwawa, Mulanje, Nsanje and Phalombe have been severely hit by torrential and persistent rains, although there are reports of other districts also been affected by the onset, such as Mulanje, Chiradzulu and Neno. Situational overviews conducted by the United Nations Satellite Centre (UNOSAT) reported a flooded area of 20Km2 in the districts of Balaka, Blantyre, Neno and Zomba, where 5,400 people are potentially exposed or living close to flooded areas. Also, the Malawian government agency of Department of Disaster Management Affairs (DoDMA) reported several blocked roads in the Phalombe district, which negatively affects the daily lives of several households whom are relegated to camps and obstructing their access to essential services, such as health facilities.

DTM in Yemen includes the monitoring of key migrant and return locations on Yemen's northern border with Saudi Arabia and southern coastal border. DTM monitors the arrivals of migrants and Yemeni nationals in order to identify different patterns and types of migration. IOM estimates that 6,589 migrants entered Yemen in addition to 2,819 Yemeni returns from Saudia Arabia during November 2019 bringing the number of migrants who have arrived in Yemen in 2019 to ‭127,275‬‬ and the number of Yemeni returnees to 44,777

This datasets has IDPs, Household & Returnees data at Admin3 level gathered through DTM Mobility Tracking Assessment.

The dataset contains number of IDPs at sub national level.

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

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.

This is the 2021 multisector needs analysis data (MSNA) - a comprehensive household-level analysis covering all states in Sudan.