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

Cost-effective proactive testing strategies during COVID-19 mass vaccination: A modelling study

Zhanwei Du, Lin Wang, Yuan Bai, Xutong Wang, Abhishek Pandey, Meagan C. Fitzpatrick, Matteo Chinazzi, Ana Pastore y Piontti, Nathaniel Hupert, Michael Lachmann, Alessandro Vespignani, Alison P. Galvani, Benjamin J. Cowling, and Lauren Ancel Meyers
The Lancet Regional Health -Americas;
January 14, 2022

Model-based evaluation of alternative reactive class closure strategies against COVID-19

Quan-Hui Liu, Juanjuan Zhang, Cheng Peng, Maria Litvinova, Shudong Huang, Piero Poletti, Filippo Trentini, Giorgio Guzzetta, Valentina Marziano, Tao Zhou, Cecile Viboud, Ana I. Bento, Jiancheng Lv, Alessandro Vespignani, Stefano Merler, Hongjie Yu & Marco Ajelli
Nature Communications
January 14, 2022

Recent publications

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

Cost-effective proactive testing strategies during COVID-19 mass vaccination: A modelling study

Zhanwei Du, Lin Wang, Yuan Bai, Xutong Wang, Abhishek Pandey, Meagan C. Fitzpatrick, Matteo Chinazzi, Ana Pastore y Piontti, Nathaniel Hupert, Michael Lachmann, Alessandro Vespignani, Alison P. Galvani, Benjamin J. Cowling, and Lauren Ancel Meyers
The Lancet Regional Health -Americas;
January 14, 2022

Model-based evaluation of alternative reactive class closure strategies against COVID-19

Quan-Hui Liu, Juanjuan Zhang, Cheng Peng, Maria Litvinova, Shudong Huang, Piero Poletti, Filippo Trentini, Giorgio Guzzetta, Valentina Marziano, Tao Zhou, Cecile Viboud, Ana I. Bento, Jiancheng Lv, Alessandro Vespignani, Stefano Merler, Hongjie Yu & Marco Ajelli
Nature Communications
January 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