Network epidemiology

modeling spread of disease and risky behaviors through populations

This work focuses on modeling disease spread, contagion and diffusion processes across social and technical spaces in living systems. The goal is to develop mechanistically realistic predictive models of human disease and mobility at the meta-population level. Models are used to forecast spreading of infectious agents to determine risk threat such as thresholds of disease, containment strategies, and effectiveness of targeted interventions. Results from these projects are reported to the WHO and CDC who use our recommendations to set protocols and policies.

Featured publications

Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy

Brennan Klein, Nicholas Generous, Matteo Chinazzi, Zarana Bhadricha, Rishab Gunashekar, Preeti Kori, Bodian Li, Stefan McCabe, Jon Green, David Lazer, Christopher R. Marsicano, Samuel V. Scarpino, and Alessandro Vespignani
PLOS Digit Health
June 23, 2022

Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas

Alberto Aleta, David Martın-Corral, , Michiel A. Bakker, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova, Matteo Chinazzi, Natalie E. Dean, M. Elizabeth Halloran, Ira M. Longini Jr., Alex Pentland, Alessandro Vespignani, Yamir Moreno, Esteban Moro
PNAS
June 13, 2022

Recent publications

Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy

Brennan Klein, Nicholas Generous, Matteo Chinazzi, Zarana Bhadricha, Rishab Gunashekar, Preeti Kori, Bodian Li, Stefan McCabe, Jon Green, David Lazer, Christopher R. Marsicano, Samuel V. Scarpino, and Alessandro Vespignani
PLOS Digit Health
June 23, 2022

Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas

Alberto Aleta, David Martın-Corral, , Michiel A. Bakker, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova, Matteo Chinazzi, Natalie E. Dean, M. Elizabeth Halloran, Ira M. Longini Jr., Alex Pentland, Alessandro Vespignani, Yamir Moreno, Esteban Moro
PNAS
June 13, 2022

Forecasting hospital-level COVID-19 admissions using real-time mobility data

Brennan Klein, Ana C. Zenteno, Daisha Joseph, Mohammadmehdi Zahedi, Michael Hu, Martin Copenhaver, Moritz U.G. Kraemer, Matteo Chinazzi, Michael Klompas, Alessandro Vespignani, Samuel V. Scarpino, Hojjat Salmasian
medrxiv
June 8, 2022

Collaborative Hubs: Making the Most of Predictive Epidemic Modeling

Nicholas G. Reich, Justin Lessler, Sebastian Funk, Cecile Viboud, Alessandro Vespignani, Ryan J. Tibshirani, Katriona Shea, Melanie Schienle, Michael C. Runge, Roni Rosenfeld, Evan L. Ray, Rene Niehus, Helen C. Johnson, Michael A. Johansson, Harry Hochheiser, Lauren Gardner, Johannes Bracher, Rebecca K. Borchering, and Matthew Biggerstaff
American Journal of Public Health
April 14, 2022
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Featured news coverage

Featured project

The Global Epidemic and mobility (GLEAM) project has developed new computational techniques and software for the simulation of emerging infectious diseases spreading across the world. The team uses a network approach to map complex human mobility patterns that account for social interaction behaviors, travel patterns (eg, commuting routes), and transportation infrastructures (eg, metro and airline connections). The simulation interface provides a dynamic visualization of spatial contagion across geographical census areas, and quantitatively evaluates the geo-temporal evolution of the disease.

Major funders

NIH/Fred Hutchinson Cancer Research, IARPA, Metabiota, WHO, CDC, ISI Foundation