Recent displacement trends show that increasing numbers of displaced populations do not reside in camps or designated areas. Mingling with host communities, refugees tend to choose urban or semi-urban areas, where they feel safe and have higher chances to find support from their community and potential livelihood opportunities. While assessing the needs of refugee populations living in camps is relatively simple (population is within a given space, with similar living conditions, access to services, etc.), out-of-camp settings bring a new set of challenges for humanitarian actors, who need new tools to properly assess and understand local dynamics, vulnerabilities and capacities of displaced and host populations in such areas.
To respond to such challenges and enable aid actors to collect consistent and reliable information in out-of-camp refugee contexts and plan aid delivery accordingly, IMPACT and ACTED new joint initiative AGORA has initiated a programme to develop and field test a new methodological approach to data collection in such settings. Funded by the Bureau of Population, Refugees, and Migration (PRM) and in close partnership with UNHCR, this programme will provide aid actors with a toolbox to (1) delineate and understand areas through an area-based approach and (2) identify the best sources of information, or ‘Key Informants,’ within each areas using the Social Network Analysis Theory.
A first pilot of this approach has been conducted between January and May 2017 in the city of Mafraq, Jordan, where more than half of the inhabitants have Syrian origins. Based on the hypothesis that areas relevant to the communities might be different from those delineated by administrative boundaries, a participatory mapping exercise was conducted with a network of Key Informants. Mapping meaningful community boundaries successfully led to 14 well-delineated community-areas, which resulted being very different from the administrative ones. This shows that how the city is structured from an administrative perspective does not reflect the actual structure and boundaries as perceived by its inhabitants.
As a second step, the Social Network Analysis (SNA) Theory was adopted to identify the best informed individuals, showing that, in some cases, the more socially interconnected individuals were indeed those more capable to provide accurate data on their area of knowledge. The SNA Theory also brought a new perspective on the informants’ profiles, revealing how key figures in the community such as imams or mukhtar (community leader), whom many organisations recognise as reliable sources of information, might be less well-informed than shop owners, teachers or reportedly unemployed individuals, who have excellent community connections and thus access to the most updated and accurate data. Findings of this pilot were shared and discussed at local level, with authorities and aid actors. The results were found very interesting and relevant for stakeholders, who recognised the applicability and pertinence of the methodology.
Lessons learned and best practices have been extracted from this first pilot and will be incorporated to improve the toolbox in the upcoming pilots, including in the Diffa region of Niger and in Kabul, Afghanistan. Once all the pilots will be completed in 2018, the refined toolbox will be disseminated among aid actors to allow for accurate understanding of and efficient humanitarian response planning in the increasingly populated out-of-camp settings.
Access detailed findings in Mafraq’s Community Area Profiles and Area-based City Profile.
