InstituteTeamBrigitte Ruesink
Research Projects
Wechselwirkungen zwischen Flüchtlingen und Einheimischen im ländlichen Sambia: Eine dynamische agenten-basierte Modellierungsanwendung

Research Projects

Interrelations between refugee and host communities in rural Zambia: A dynamic agent-based modeling application

© Steven Gronau
Leaders:  Dr. Steven Gronau
Email:  gronau@iuw.uni-hannover.de
Team:  Dr. Steven Gronau, M.Sc. Brigitte Ruesink
Year:  2020
Sponsors:  Leibniz Young Investigator Grant of the Leibniz University Hannover
Lifespan:  01.07.2020 – 30.06.2022
More Link https://www.uni-hannover.de/de/forschung/wiss-nachwuchs/postdocs/bisher-gefoerderte-projekte/

Background

The number of refugees worldwide is on the rise. Whereas media and policy often focus on influxes to Europe and the United States, developing countries actually host the large majority of all refugees, especially Africa. As camps are generally established in remote rural areas close to village communities, the sudden influx and presence of refugees affect host populations in various ways. This concerns for example the labor market, production, trade, price levels, public service provision, crime, natural resource uses, poverty and food security. Scientists indicate a great need for research on the impacts of refugees on their host population.

Project region and objective

The research project focuses on a refugee camp in rural Zambia, where considerable refugee influxes from the neighboring Democratic Republic of the Congo are arriving. The core goal of the project is to investigate the interrelations between refugee and host communities in rural Zambia in the context of the rising number of refugee movements and the corresponding challenge to create long-term solutions. Thereby, the project contributes to the emerging field of refugee-host community research.

Method and Data

Computer-based simulation models, namely agent-based models, are developed and applied for scientific analyses. The innovative approach explores complex systems by modeling agent-environment interactions and enables long-term assessments through predictive simulations/policy scenarios. Evaluations are based on household survey data, participatory research results and geographical information.