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

Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States

Lucas M. Stolerman, Leonardo Clemente, Canelle Poirier, Kris V. Parag, Atreyee Majumder, Serge Masyn, Bernd Resch, Mauricio Santillana
Science Advances
January 18, 2023

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

Spatial scales of COVID-19 transmission in Mexico

Brennan Klein, Harrison Hartle, Munik Shrestha, Ana Cecilia Zenteno, David Barros Sierra Cordera, José R. Nicolas-Carlock, Ana I. Bento, Benjamin M. Althouse, Bernardo Gutierrez, Marina Escalera-Zamudio, Arturo Reyes-Sandoval, Oliver G. Pybus, Alessandro Vespignani, Jose Alberto Diaz-Quiñonez, Samuel V. Scarpino, Moritz U.G. Kraemer
arXiv
January 30, 2023

Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States

Lucas M. Stolerman, Leonardo Clemente, Canelle Poirier, Kris V. Parag, Atreyee Majumder, Serge Masyn, Bernd Resch, Mauricio Santillana
Science Advances
January 18, 2023

Characterizing collective physical distancing in the U.S. during the first nine months of the COVID-19 pandemic

Brennan Klein, Timothy LaRock, Stefan McCabe, Leo Torres, Lisa Friedland, Maciej Kos, Filippo Privitera, Brennan Lake, Moritz U.G. Kraemer, John S. Brownstein, Richard Gonzalez, David Lazer, Tina Eliassi-Rad, Samuel V. Scarpino, Alessandro Vespignani, Matteo Chinazzi
arXiv
December 20, 2022

Identification Of Potent Inhibitors Of Sars-Cov-2 Infection By Combined Pharmacological Evaluation And Cellular Network Prioritization

J.J. Patten, Patrick T. Keiser, Deisy Morselli-Gysi, Giulia Menichetti, Hiroyuki Mori, Callie J. Donahue, Xiao Gan, Italo Do Valle, Kathleen Geoghegan-Barek, Manu Anantpadma, Ruthmabel Boytz, Jacob L. Berrigan, Sarah H. Stubbs, Tess Ayazika, Colin O’leary, Sallieu Jalloh, Florence Wagner, Seyoum Ayehunie, Stephen J. Elledge, Deborah Anderson, Joseph Loscalzo, Marinka Zitnik, Suryaram Gummuluru, Mark N. Namchuk, Albert-László Barabási And Robert A. Davey
iScience
September 16, 2022

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
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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