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

The effect of human mobility and control measures on the COVID-19 epidemic in China

Moritz U. G. Kraemer, Chia-Hung Yang, Bernardo Gutierrez, Chieh-Hsi Wu, Brennan Klein, David M. Pigott, Open COVID-19 Data Working Group, Louis du Plessis, Nuno R. Faria, Ruoran Li, William P. Hanage, John S. Brownstein, Maylis Layan, Alessandro Vespignani, Huaiyu Tian, Christopher Dye, Oliver G. Pybus, Samuel V. Scarpino
Science
March 25, 2020

Epidemiological data from the COVID-19 outbreak, real-time case information

Bo Xu, Bernardo Gutierrez, Sumiko Mekaru, Kara Sewalk, Lauren Goodwin, Alyssa Loskill, Emily L. Cohn, Yulin Hswen, Sarah C. Hill, Maria M. Cobo, Alexander E. Zarebski, Sabrina Li, Chieh-Hsi Wu, Erin Hulland, Julia D. Morgan, Lin Wang, Katelynn O’Brien, Samuel V. Scarpino, John S. Brownstein, Oliver G. Pybus, David M. Pigott & Moritz U. G. Kraemer
Nature
March 24, 2020

The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak

Matteo Chinazzi, Jessica T. Davis, Marco Ajelli, Corrado Gioannini, Maria Litvinova, Stefano Merler, Ana Pastore y Piontti, Kunpeng Mu, Luca Rossi, Kaiyuan Sun, Cécile Viboud, Xinyue Xiong, Hongjie Yu, M. Elizabeth Halloran, Ira M. Longini Jr., Alessandro Vespignani
Science
March 6, 2020

Recent publications

Assessing changes in commuting and individual mobility in major metropolitan areas in the United States during the COVID-19 outbreak

Brennan Klein, Timothy LaRock, Stefan McCabe, Leo Torres, Filippo Privitera, Brennan Lake, Moritz U. G. Kraemer, John S. Brownstein, David Lazer, Tina Eliassi-Rad, Samuel V. Scarpino, Matteo Chinazzi, and Alessandro Vespignani
March 31, 2020

The effect of human mobility and control measures on the COVID-19 epidemic in China

Moritz U. G. Kraemer, Chia-Hung Yang, Bernardo Gutierrez, Chieh-Hsi Wu, Brennan Klein, David M. Pigott, Open COVID-19 Data Working Group, Louis du Plessis, Nuno R. Faria, Ruoran Li, William P. Hanage, John S. Brownstein, Maylis Layan, Alessandro Vespignani, Huaiyu Tian, Christopher Dye, Oliver G. Pybus, Samuel V. Scarpino
Science
March 25, 2020

Epidemiological data from the COVID-19 outbreak, real-time case information

Bo Xu, Bernardo Gutierrez, Sumiko Mekaru, Kara Sewalk, Lauren Goodwin, Alyssa Loskill, Emily L. Cohn, Yulin Hswen, Sarah C. Hill, Maria M. Cobo, Alexander E. Zarebski, Sabrina Li, Chieh-Hsi Wu, Erin Hulland, Julia D. Morgan, Lin Wang, Katelynn O’Brien, Samuel V. Scarpino, John S. Brownstein, Oliver G. Pybus, David M. Pigott & Moritz U. G. Kraemer
Nature
March 24, 2020

Aggregated mobility data could help fight COVID-19

Caroline O. Buckee, Satchit Balsari, Jennifer Chan, Mercè Crosas, Francesca Dominici, Urs Gasser, Yonatan H. Grad, Bryan Grenfell, M. Elizabeth Halloran, Moritz U. G. Kraemer, Marc Lipsitch, C. Jessica E. Metcalf, Lauren Ancel Meyers, T. Alex Perkins, Mauricio Santillana, Samuel V. Scarpino, Cecile Viboud, Amy Wesolowski, Andrew Schroeder
Science
March 23, 2020

Age profile of susceptibility, mixing, and social distancing shape the dynamics of the novel coronavirus disease 2019 outbreak in China

Juanjuan Zhang, Maria Litvinova, Yuxia Liang, Yan Wang, Wei Wang, Shanlu Zhao, Qianhui Wu, Stefano Merler, Cecile Viboud, Alessandro Vespignani, Marco Ajelli, Hongjie Yu
medRxiv
March 20, 2020

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