Baseline Assessment

Mobility Tracking is a DTM methodology which aims to quantify the presence of population categories as well as the populations’ reasons for displacement, length of displacement and needs. Mobility tracking relies on key informant interviews (KIIs) to estimate the size, priorities and mobility dynamics of a given population. For more information on the DTM methodology, see the DTM Methodological Framework.

The second round of data collection was deployed in 2023 to understand changes in the mobility dynamics induced by prolonged drought and the recovery phase, as well as updates on mobility trends and the most urgent sectoral needs of the target mobile population groups and host communities, to assess changes since the 2022 data collection.

Key findings included:

• Displacement reportedly increased by an approximate 200% in the past 4 years:
  • 12 per cent of arrivals arrived in their location of displacement in 2020, 61 per cent arrived between 2020 and 2022 and 27 per cent arrived in 2023.
  • In nearly all the assessed sub-locations (99%) informants reported the presence of pastoralist dropouts. Across all the sub-locations, 88 per cent of pastoral dropouts happened before 2023, and dropout rates increased most drastically during the 2020-2022 drought period.
  • All arrival households (100% or 15,299 households) arrived at sub-locations that already struggled with the severe effects of drought, resource-based conflict, and ethnic clashes.[1]
• Between September 2022 and May 2023, the reported primary driver of forced displacement was drought. As of May 2024, the primary driver of displacement was floods with 23, 511 households displaced across Kenya.
• 81 per cent of returnees temporarily resided in Kenya, and 16 per cent temporarily resided in Somalia. Of those who temporarily resided in Kenya, 57 per cent were temporarily located in a location outside their immediate area of origin in Garissa County, suggesting prevalent internal migration within the county and cross-border movement dynamics.
• 10,158 child-headed households were identified in Garissa. Of these, 2,954 (29%) had no relatives or community members living near them and were separated from their legal or customary guardians and 8,181 children (81%) were reported as without permanent sources of support.
• In 33 per cent of Garissa sub-locations, shelters were reportedly not stable enough to withstand environmental hazards or security threats.
• Key informants reported 17,568 student dropouts (22% of the estimated number of students), despite concurrent reports that educational institutions were active in 96 per cent of sub-locations. The discrepancy between these figures’ warrants updated, additional investigation.
• Open defecation was reported in 66 sub-locations (44%).  [DI1] The most reported drivers for people to practice open defecation was the non-functionality of latrines (40%), difficulty in accessing the latrines (39%), lack of privacy as there was no reported partition for male and female cubicles (35%), and insecurity when accessing the latrines (11%).
  • Insecurity-related latrine issues were reported by key informants in Balambala (9 sub-locations), Dadaab (3 sub-locations), Lagdera (3 sub-locations) and Hulugho (1 sub-locations).
• Key informants reported that only 52% of the sublocations host a health facility. Furthermore, in 95% of the sub locations with a health facility, there was a reported absence of medicine and commodities
• Most respondents in sub-locations reported that the top three sources of drinking water were: motorized borehole (16%), rainwater (15%) and river water (10%).

[1] Household reportedly arrived in their new sublocation at the following time periods: 12 per cent before 2020, 61 per cent between 2020 and 2022 and 27 per cent in 2023.

 [DI1]Figures are correct, however in the dataset I can see Bush instead of open defecation, which has 0.

In the analysis shared I see that it is Bush (open defecation) under the WASH tab. However in the data table I cannot see such category.

When uploading the data to the website let’s make sure that categories have the same labels in the reporting and in the dataset

Ce tableau de bord présente les principaux résultats de suivi des mouvements de populations dans la province du Nord-Kivu à l’issue du onzième round d’évaluation conduit par l’unité de la Matrice de Suivi des Déplacements (Displacement Tracking Matrix, en anglais (DTM)) de l’Organisation Internationale pour les Migrations (OIM). Ces évaluations ont été réalisées à travers un exercice de collecte de données conduit du 26 mars au 15 mai 2024, en collaboration avec l’ONG locale, Promotion de Développement Humain et Protection de l’Environnement Social (PDHPES), et la Division Provinciale des Affaires Humanitaires (DIVAH) du Nord-Kivu. Lors de ce cycle, un total de 5 541 villages, couvrant 34 zones de santé (ZS), ont été évalués à travers des consultations avec 16 612 informateurs clé.

On 24 March 2024, East Sepik province in Papua New Guinea, experienced an earthquake and preceding flooding which affected an estimated 11,269 individuals from 2,204 households and as well, left an estimated 2,436 individuals from 523 households displaced. 

The affected population are within their community of origin. This displacement profile presents findings from the Displacement Tracking Matrix (DTM) assessment conducted in communities of East Sepik from 14 – 21 of June 2024. 

Du 10 avril au 8 mai 2024, en collaboration avec l’ONG nationale, Réseau d’Action pour le Développement et le Progrès Intégré (RADPI) et la Division Provinciale des Affaires Humanitaires (DIVAH), la DTM a mené des évaluations des mouvements de population dans 5 318 villages, couvrant 34 zones de santé. Selon les informations recueillies, au cours de cette douzième round d'évaluations, auprès de 16 575 informateurs clés, 1 395 604 personnes déplacées et 538 974 personnes retournées sont présentes dans 76 pour cent de la province évaluée.

Ce tableau de bord présente les principaux résultats de suivi des mouvements de populations dans la province du Tanganyika à l’issue du onzième round d’évaluation conduit par l’unité de la Matrice de Suivi des Déplacements (Displacement Tracking Matrix, en anglais (DTM)) de l’Organisation Internationale pour les Migrations (OIM). Ces évaluations ont été réalisées à travers un exercice de collecte de données conduit du 9 avril au 20 mai 2024, en collaboration avec l’ONG locale, Promotion de Développement Humain et Protection de l’Environnement Social (PDHPES), et la Division Provinciale des Affaires Humanitaires (DIVAH). Lors de ce cycle, un total de 5 027 villages, couvrant 11 zones de santé (ZS), ont été évalués à travers des consultations avec 14 261 informateurs clé.

This latest round of Emergency Trends Tracking was initiated in April 2024 to monitor displacements movements during the Gu rainy season. Districts covered in this round include Afgooye, Afmadow, Baardheere, Baidoa, Balcad, Belet Weyne, Belet Xaawo, Dayniile, Doolow, Gaalkacyo, Garoowe, Hodan, Jamaame, Jowhar, Kahda, Kismaayo, Luuq. ETT is a crisis-based tool that tracks sudden displacement triggered by specific events or emerging crises.

The objective of ETT is to help prioritize humanitarian response and to enable partners to deliver rapid assistance. Based on previous shock induced displacement patterns, the humanitarian community expects that people will continue to move toward urban areas in search of humanitarian services. Consequently, the ETT coverage focuses on the main urban centers and surrounding villages for each assessed district. The data is collected through Key Informant Interviews (KIIs) at the location level, from Sunday to Wednesday every week. It includes information on new arrivals, numbers and demographic of IDPs, reasons for displacement, intentions, humanitarian assistance and priority needs among others.

The ETT tool also adapts to regional contexts: because of the very high number of IDP sites in Khada and Daynile districts in Banadir region and in Baidoa district in Bay region, a zonal approach has been adopted for these areas. Each week, KIIs are first conducted at the zone level to indicate to the field teams which locations have received the most new arrivals and which need to be assessed.

To facilitate the joint analysis of the CCCM (Camp Coordination and Camp Management) Cluster’s New Arrivals Tracker (NAT) and ETT data, the assistance and needs indicators are identical in both tools.

On 24 May 2024, a massive landslide engulfed villages in Yambali Ward, Maip Mulitaka Local Level Government of Lagaip-Porgera District, Enga Province of Papua New Guinea. The landslide caused extensive damage to many lives, homes and livelihoods. The extent of the destruction has left an estimated 1,680 individuals displaced, with an estimated 3,979 individuals affected and at risk of displacement. Furthermore; 9,952 individuals are estimated to be directly affected by the landslide. Immediate emergency response and long-term recovery plans are crucial to address the needs of these affected populations and mitigate future risks and vulnerabilities. 

The landslide has not only devastated the Yambali ward but also caused significant instability in the surrounding area. The soil remains highly unstable, with visible cracks indicating imminent threats to lives and properties. Ongoing geo-seismic activities in the vicinity exacerbate the risk, as the land continues to shift. The landslide covered two creeks with debris and boulders, blocking waterways and increasing the likelihood of further slides. The blockage of these creeks poses a critical risk of flooding, which could trigger additional landslides, endangering the already vulnerable community.

The International Organization for Migration (IOM), in collaboration with the Enga Provincial Disaster Response Team and Site Management team, conducted a Displacement Tracking Matrix (DTM) assessment across all affected wards (Yambali, Pokolip, Kuandak, and Yuyango) between June-July 2024. This assessment was carried out by enumerators through field observations, focus group discussions, and key informant interviews with both affected populations and local authorities and as well critical sectoral needs were identified. The assessment also highlighted ongoing risks of displacement in high-risk areas prone to further landslides and environmental hazards. The findings presented in this DTM report emphasize the urgent need for targeted humanitarian assistance to meet these evolving needs and mitigate risks effectively.