Case Study: George Mason University achieves accurate refugee migration forecasting with AnyLogic

Forced Migration of Refugees a Case Study on Migration Forecasting

George Mason University, along with researchers from the University at Buffalo, studied forced migration and refugee flows for the Humanitarian Information Unit at the U.S. State Department. The challenge was that official migration data is often delayed and traditional models struggle to capture fast-changing drivers such as conflict, instability, economic shocks, and social-media signals. AnyLogic software was used to build a system dynamics simulation model to better forecast migration trends.

Using AnyLogic, the team combined real-time open-source data, UNHCR reports, and social media inputs to model how conflict, regime legitimacy, human-rights violations, and other factors affect displacement. The model matched real-world data from 2012 to 2018 and helped identify key patterns, including that increased conflict drives more movement and instability worsens refugee flows. The result was a more accurate forecasting approach that can help governments and aid organizations plan resources and respond faster to migration crises.

George Mason University

Troy Curry

George Mason University