GLEAM is based on a multidisciplinary approach that combines mathematical modeling and computational science with real-world data and sophisticated interface design.
We use elaborate stochastic infectious disease models to supports a wide range of epidemiological studies, covering different types of infections and intervention scenarios.
We use real-world data on population and mobility networks and integrate those in structured spatial epidemic models to generate data driven simulations of the worldwide spread of infectious diseases.
The computer is our laboratory. GLEAM runs on high performance computers to create in-silico experiments that would be hardly feasible in real systems and to guide our understanding of typical non-linear behavior and tipping points of epidemic phenomena.
We provide a suite of computational tools to help modeling the spread of a disease, understanding observed epidemic patterns, studying the effectiveness of different intervention strategies. The tools are available to researchers, health-care professionals and policy makers.