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

Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave

Jessica T. Davis, Matteo Chinazzi, Nicola Perra, Kunpeng Mu, Ana Pastore y Piontti, Marco Ajelli, Natalie E. Dean, Corrado Gioannini, Maria Litvinova, Stefano Merler, Luca Rossi, Kaiyuan Sun, Xinyue Xiong, Ira M. Longini Jr, M. Elizabeth Halloran, Cécile Viboud & Alessandro Vespignani
Nature
October 25, 2021

Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil

Lauren A. Castro, Nicholas Generous, Wei Luo, Ana Pastore y Piontti, Kaitlyn Martinez, Marcelo F. C. Gomes, Dave Osthus, Geoffrey Fairchild, Amanda Ziemann, Alessandro Vespignani, Mauricio Santillana, Carrie A. Manore, Sara Y. Del Valle
PLoS Negl Trop Dis
May 21, 2021

Estimating the effect of social inequalities on the mitigation of COVID-19 across communities in Santiago de Chile

Nicolò Gozzi, Michele Tizzoni, Matteo Chinazzi, Leo Ferres, Alessandro Vespignani, Nicola Perra
Nature Communications
April 23, 2021

Recent publications

Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave

Jessica T. Davis, Matteo Chinazzi, Nicola Perra, Kunpeng Mu, Ana Pastore y Piontti, Marco Ajelli, Natalie E. Dean, Corrado Gioannini, Maria Litvinova, Stefano Merler, Luca Rossi, Kaiyuan Sun, Xinyue Xiong, Ira M. Longini Jr, M. Elizabeth Halloran, Cécile Viboud & Alessandro Vespignani
Nature
October 25, 2021

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
medRxiv
October 9, 2021

Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence

Moritz U G Kraemer, Verity Hill, Christopher Ruis, Simon Dellicour, Sumali Bajaj, John T McCrone, Guy Baele, Kris V Parag, Anya Lindström Battle, Bernardo Gutierrez, Ben Jackson, Rachel Colquhoun, Áine O'Toole, Brennan Klein, Alessandro Vespignani, COVID-19 Genomics UK (CoG-UK) consortium; Erik Volz, Nuno R Faria, David Aanensen, Nicholas J Loman, Louis du Plessis, Simon Cauchemez, Andrew Rambaut, Samuel V Scarpino, Oliver G Pybus
Science
July 22, 2021

Association between COVID-19 outcomes and mask mandates, adherence, and attitudes

Dhaval Adjodah, Karthik Dinakar, Matteo Chinazzi, Samuel P. Fraiberger, Alex Pentland, Samantha Bates, Kyle Staller, Alessandro Vespignani, Deepak L. Bhatt
PLOS ONE
June 23, 2021

Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil

Lauren A. Castro, Nicholas Generous, Wei Luo, Ana Pastore y Piontti, Kaitlyn Martinez, Marcelo F. C. Gomes, Dave Osthus, Geoffrey Fairchild, Amanda Ziemann, Alessandro Vespignani, Mauricio Santillana, Carrie A. Manore, Sara Y. Del Valle
PLoS Negl Trop Dis
May 21, 2021
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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