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

Measurability of the epidemic reproduction number in data-driven contact networks

Quan-Hui Liu, Marco Ajelli, Alberto Aleta, Stefano Merler, Yamir Moreno, and Alessandro Vespignani
PNAS
November 21, 2018

Spread of Zika virus in the Americas

Qian Zhang, Kaiyuan Sun, Matteo Chinazzi, Ana Pastore y Piontti, Natalie E. Dean, Diana Patricia Rojas, Stefano Merler, Dina Mistry, Piero Poletti, Luca Rossi, Margaret Bray, M. Elizabeth Halloran, Ira M. Longini Jr., Alessandro Vespignani
PNAS
April 25, 2017

Forecasting Seasonal Influenza Fusing Digital Indicators and a Mechanistic Disease Model

Q, Zhang, N. Perra, D. Perrotta, D. Paolotti, M. Tizzoni, A. Vespignani.
WWW '17
April 3, 2017

Recent publications

Pertussis Epidemiology, Immunology, and Evolution

Pejman Rohani and Samuel Scarpino (editors)
Oxford University Press
December 20, 2018

Charting the Next Pandemic: Modeling Infectious Disease Spreading in the Data Science Age

Ana Pastore y Piontti, Nicola Perra, Luca Rossi, Nicole Samay, Alessandro Vespignani
Springer
December 10, 2018

Epidemic spreading on time-varying multiplex networks

Quan-Hui Liu, Xinyue Xiong, Qian Zhang, and Nicola Perra
Phys. Rev. E
December 3, 2018

Measurability of the epidemic reproduction number in data-driven contact networks

Quan-Hui Liu, Marco Ajelli, Alberto Aleta, Stefano Merler, Yamir Moreno, and Alessandro Vespignani
PNAS
November 21, 2018

Quantifying the risk of local Zika virus transmission in the contiguous US during the 2015–2016 ZIKV epidemic

Kaiyuan Sun, Qian Zhang, Ana Pastore-Piontti, Matteo Chinazzi, Dina Mistry, Natalie E Dean, Diana Patricia Rojas, Stefano Merler, Piero Poletti, Luca Rossi, M Elizabeth Halloran, Ira M Longini Jr and Alessandro Vespignani
BMC Medicine
October 18, 2018

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