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 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

The effect of eviction moratoria on the transmission of SARS-CoV-2

Anjalika Nande, Justin Sheen, Emma L. Walters, Brennan Klein, Matteo Chinazzi, Andrei H. Gheorghe, Ben Adlam, Julianna Shinnick, Maria Florencia Tejeda, Samuel V. Scarpino, Alessandro Vespignani, Andrew J. Greenlee, Daniel Schneider, Michael Z. Levy & Alison L. Hill
Nature Communications
April 15, 2021

Recent publications

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

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

The effect of eviction moratoria on the transmission of SARS-CoV-2

Anjalika Nande, Justin Sheen, Emma L. Walters, Brennan Klein, Matteo Chinazzi, Andrei H. Gheorghe, Ben Adlam, Julianna Shinnick, Maria Florencia Tejeda, Samuel V. Scarpino, Alessandro Vespignani, Andrew J. Greenlee, Daniel Schneider, Michael Z. Levy & Alison L. Hill
Nature Communications
April 15, 2021
View more

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