This report, based on a questionnaire administered through a Kobo toolbox, provides insights into the profiles, experiences, needs, routes travelled and intentions of migrants transiting through Montenegro. Data was collected from 1 April to 30 June 2024. IOM surveyed 397 migrants in Reception Centers Božaj and Spuž, and active transit locations such as bus stops or at key entry and exit locations (Rožaje and Pljevlja) throughout the country.

This report provides insights into the profiles, experiences, needs, routes travelled and intentions of migrants transiting through the Western Balkans. IOM surveyed 822 migrants from 1 June to 30 June 2024 in Albania, Bosnia and Herzegovina, Montenegro, North Macedonia, Serbia and Kosovo*.

References to Kosovo* shall be understood in the context of UN Security Council Resolution 1244 (1999).

The General Population Needs and Vulnerability Assessment (GPS) is the quarterly representative survey assessing the situation of the local population of the Republic of Moldova and is conducted to identify changes and trends in their vulnerabilities, needs, and intentions over time. The study is a joint initiative of IOM and the World Food Programme (WFP) with inputs to the questionnaire from the Ministry of Labour and Social Protection (MoLSP). The key findings include:

• 19% of the households (HH) are food insecure, while 37% reported having used crisis and emergency coping strategies to respond to their food needs.
• 12% of HH had to borrow money or rely on friends to afford food while 22% had to reduce the number of meals per day.
• 32% per cent of the respondents reported having at least one chronically ill person in their household, 18% reported the presence of a person with disabilities.
• 85% of the respondents were employed. 54% of the HH had more than one adult member earning an income.
• 19% of HH received social assistance. Among them, 56% reported that the social assistance they received was not sufficient or barely sufficient to cover their households’ basic needs.

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%).

 

 

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[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.

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 [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

Based on findings from Mobility Tracking Round 2 conducted in Turkana, the infographic presents "key findings,"- those most surprising, concerning or informative form the overall assessment findings.

As of June 2024, a total of 13 Flow Monitoring Points (FMPs) were operational, monitoring both internal movements and cross-border travel with neighboring countries such as Uganda (UGA), the Democratic Republic of Congo (DRC), Sudan (SDN), Ethiopia (ETH), Kenya (KEN), and the Central African Republic (CAR).
The figures provided are indicative of trends observed among respondents at the active FMPs only since DTM's coverage does not encompass all cross-border or internal flows. Participation in the survey is voluntary and anonymous, with groups of individuals traveling together often surveyed collectively, typically representing a household. 

The IOM Afghanistan’s DTM Flow Monitoring activity is designed to provide insights into the mobility patterns at Afghanistan’s border points with the Islamic Republic of Iran and Pakistan. The activity involves two interlinked exercises: the Flow Monitoring Counting (FMC), a headcount of individuals crossing the border, and the Flow Monitoring Surveys (FMS), which collect data on the profiles and intentions of randomly selected Afghan nationals. DTM FM is operational at four main crossing points (connected to Afghanistan’s National Highway) as well as seven other crossing points with Islamic Republic of Iran and Pakistan. This weekly snapshot combines information from the FM activity and various IOM sources related to cross-border movement. For a detailed explanation of the methodology used in gathering this data, the report directs readers to the section titled “IOM INFLOW DATA” on the last page.

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.

Monthly Overview of:

• Arrivals in the Western Balkans
• Top three nationalities at arrivals in the reporting month
• Migrants presence in reception facilities
• Assisted Voluntary Returns and reintegration

Monthly Overview of:

• Arrivals in the Western Balkans
• Top three nationalities at arrivals in the reporting month
• Migrants presence in reception facilities
• Assisted Voluntary Returns and reintegration