Based within the Department of Environmental Health Sciences at Mailman School of Public Health, Columbia University, our group studies the environmental, social, and ecological determinants of infectious diseases using mathematical and statistical techniques. We develop mathematical models and computational tools to advance surveillance, forecasting, and control of both seasonal and emerging infectious agents, with a focus on respiratory viruses and antimicrobial-resistant pathogens.

Postdoctoral Research Scientist Position

Our group is looking for a Postdoctoral Research Scientist interested in infectious disease modeling, data analytics and computational methods in public health research. The Postdoctoral Research Scientist will work on a project focusing on human behavior and modeling of respiratory diseases such as COVID-19 and influenza, with applications to disease surveillance, forecasting and control. The Postdoctoral Research Scientist will join an interdisciplinary research team with expertise in behavior science, infectious disease modeling, Bayesian inference, network science and data science. Please apply using this link.

Special Issue

We organized a special issue on Mathematical Models and Computational Tools of Infectious Diseases in the journal Mathematical Biosciences and Engineering published by American Institute of Mathematical Sciences. Welcome to submit your research on infectious disease modeling and analysis to this special issue before December 31, 2022.

Latest News

  • 08/15/2022 Our project on behavior-driven disease forecasting is funded by NSF (co-funded by the U.S. Centers for Disease Control and Prevention’s Center for Forecasting and Outbreak Analytics). We will infuse behavior data into epi models and develop predictive tools for operational use in NYC.
  • 05/10/2022 I will serve as the Associate Editors for Microbiology Spectrum published by the American Society for Microbiology and Frontiers in Physics published by Frontiers.
  • 03/31/2022 Our study on hurricane evacuation and COVID-19 published in GeoHealth in 2020 is selected as a top cited article of the journal.
  • 09/22/2021 New study quantifying the impact of COVID-19 non-pharmaceutical interventions on influenza transmission in the United States is published online in The Journal of Infectious Diseases. The study is featured on the cover of the journal.
  • 09/09/2021 Our study on MRSA transmission is highlighted by Nature's Research Highlight.
  • 09/07/2021 We developed a computational method to identify asymptomatic spreaders of antimicrobial-resistant pathogens in hospital settings and applied it to a network of healthcare facilities in Sweden. Check out the paper published in PNAS.
  • 09/07/2021 Our paper on the burden and characteristics of COVID-19 in the US is highlighted in the NIH Director's Blog.
  • 08/26/2021 Our study on the overall burden and characteristics of COVID-19 in the United States during 2020 is published online in Nature.
  • 06/14/2021 Our collaborative study with colleagues at Yale on the role of meteorological factors in the transmission of SARS-CoV-2 is published in Nature Communications.
  • 04/01/2021 I will join the Department of Environmental Health Sciences at Mailman School of Public Health, Columbia University as a tenure-track assistant professor in fall 2021.
  • 02/09/2021 Our early work on undetected infections of SARS-CoV-2 is selected as one of the seven finalists of the AAAS Newcomb Cleveland Prize.
  • 01/29/2021 Our letter to editor "Social distancing remains key during vaccinations" is published online in Science.
  • 01/11/2021 New paper out in Nature Communications. Lack of a widespread surveillance network hampers accurate infectious disease forecasting. Here we provide a framework to optimize the selection of surveillance site locations and show that accurate forecasting of respiratory diseases for locations without surveillance is feasible.
  • 01/04/2021 Our paper "Multiscale mobility explains differential associations between the gross domestic product and COVID-19 transmission in Chinese cities" is published in Journal of Travel Medicine. In this letter, we find a Simpson’s paradox in the association between GDP and COVID-19 transmission in Chinese cities stratified by location. The differential associations in cities within and outside Hubei province can be explained by different patterns of short-range and long-range multiscale mobility from Wuhan to other cities.
  • 11/06/2020 Our study exploring the effect of non-pharmaceutical intervention on COVID-19 transmission in the US appears in Science Advances.
  • 08/28/2020 Our work on information diffusion "Realistic modelling of information spread using peer-to-peer diffusion patterns" is published online in Nature Human Behaviour. In this work, we develop a more realistic information cascade model that reproduces key structures of real-world diffusion trees in distinct social platforms by combining a peer-to-peer diffusion pattern with a correction for observational bias.
  • 04/23/2020 Together with colleagues at Mailman, we have developed three online tools to allow users to visualze the updated weekly projections of new COVID-19 cases, new infections, and available critical care beds in states and counties across the United States under a variety of social distancing and hospital response scenarios over a six-week period: (1) a data visualization tool that graph projections over time, (2) a mapping tool that charts county-level projections, and (3) animated maps.
  • 03/20/2020 The New York Times publishes an article "Without Urgent Action, Coronavirus Could Overwhelm U.S., Estimates Say" reporting our model projections of the COVID-19 outbreak in the US. Our results indicate that stringent control measures are required to reduce massive infections and flatten the epidemic curve.
  • 03/16/2020 Our research on the transmission dynamics of COVID-19 reveals that substantial undocumented infection fuels rapid spread of coronavirus in China. This study is published online in Science on March 16.