Providing data-driven insights to mitigate the spread of infectious diseases

When or where the next pandemic will start is unknown. But when it does, we want to be sure that we will have the means to stop it. One way to achieve that is being ahead of it. Knowing where and when is going to hit next and the extension of the outbreak is key.

The GLEAM (Global Epidemic and Mobility) Project provides data-driven insights powered by big data and elaborate stochastic infectious disease models that have been validated over the years. Through the different branches of the framework we advance the field of epidemic modeling and forecast that can be used, ultimately, to fight the next pandemic.

Our approach

GLEAM is based on a multidisciplinary approach that combines mathematical modeling and computational science with real-world data and sophisticated user interface design.


We use elaborate stochastic infectious disease models to supports a wide range of epidemiological studies, covering different types of infections and intervention strategies.

Real-world data

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.
Learn more about the data

Computational thinking

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.

Tools development

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.
Learn more about the tools