This $148,582 Project Grant award from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) supports the development of computational models and algorithms to analyze and forecast epidemiological trends during and after military conflicts. The project, titled "EAGER: IMPRESS-U: Modeling and Forecasting of Infection Spread in War and Post War Settings Using Epidemiological, Behavioral and Genomic Surveillance Data", is a collaborative effort involving researchers from Georgia State University, the University of Connecticut, and institutions in Ukraine and Poland.
The key products and services to be delivered include: (1) developing epidemiological models tailored for conflict zones that integrate diverse data sources, (2) merging these war-centric epidemiological models with population genetics models within a phylodynamics framework, and (3) creating algorithms for optimized public health resource allocation in war and post-war settings. The University of Connecticut is providing expertise in genomic epidemiology, bioinformatics algorithms, and mathematical modeling of infectious diseases through a subaward. The overarching goal is to create a comprehensive modeling and optimization framework to enable accurate epidemiological forecasting and actionable public health guidance for military conflicts and post-conflict scenarios.