Understanding Movement Patterns of Populations of Internally Displaced Persons in North Kivu, DRC

Aid organizations in conflict zones must be able to respond to large movements of populations and provide support to displaced people on varying time scales. In order to properly allocate resources, these organizations must interpret large amounts of population data. Working in North Kivu, DRC where the internally displaced person (IDP) crisis has been ongoing for over 20 years, we propose to implement new methods of data interpretation and analysis to better inform aid organizations. We will develop and implement our Identity Matching Algorithm that will match individuals across datasets and provide organizations a way to track the origin and movement of individuals, as well as to gain a better estimate of the number of displaced people in a region. In addition, conducting detailed field studies with a team of interviewers will allow us to acquire complementary statistics on displacement trajectories and learn about the temporal and spatial population movement dynamics.