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|Title:||A generalized simulation development approach for predicting refugee destinations|
|Publisher:||Nature Publishing Group|
|Citation:||Scientific Reports, (2017)|
|Abstract:||In recent years, global forced displacement has reached record levels, with 22.5 million refugees worldwide. Forecasting refugee movements is important, as accurate predictions can help save refugee lives by allowing governments and NGOs to conduct a better informed allocation of humanitarian resources. Here, we propose a generalized simulation development approach to predict the destinations of refugee movements in conflict regions. We synthesize data from UNHCR, ACLED and Bing Maps to construct agent-based simulation of refugee movements. We apply our approach to simulate these movements in three major African conflicts, and estimate the distribution of incoming refugees across destination camps, given the expected total number of refugees in the conflict. Our simulations consistently predict more than 75% of the refugee destinations correctly after the first 12 days, and consistently outperform alternative naive forecasting techniques. Using our approach, we are also able to reproduce key trends in refugee arrival rates found in the UNHCR data.|
|Appears in Collections:||Dept of Computer Science Research Papers|
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