Researchers built a simulation method to test whether the physical layout of refugee and internally displaced person (IDP) camps can reduce the spread of disease. They used a detailed, individual-based epidemic model to create virtual camps, place shared facilities in different patterns, and run outbreak scenarios. The work is presented as a proof of concept and a framework for further study, not as a final policy prescription.

The team adapted the JUNE agent-based epidemic model. An agent-based model means the computer simulates many individual people (“agents”), their homes, and the places they visit. The researchers created virtual camps out of square region building blocks and generated a synthetic population sampled from the real Zaatari camp in Jordan. They tested two sizes: a 4-region camp with about 58,860 people and a 16-region camp with about 241,957 people. Each region was represented as extending 0.81 km2 in the experiments.

For each virtual camp they fixed how many shared venues there should be based on baseline per-person rates. They then placed those venues using four schemes: even (regular grid), uniform (randomly across the camp), middle (along the camp’s middle axes), and boundary (around the camp edges). The model assigned each person a small pool of nearby venues and then ran 120-day simulations of COVID-19 spread. The simulations assumed no containment measures such as social distancing.

Results from these prototype tests showed layout can matter. In the smaller 4-region camps the infection curves were similar across placement schemes. In the larger 16-region camps, placing venues along the boundary produced a substantially lower infection peak than concentrating them in the middle. The even and uniform placements produced similar results to each other. The team also tracked how disease moved between regions and found that in the larger camp, different regions peaked at different times instead of all peaking together.