Past Event

COPSS-NISS COVID-19 Data Science Webinars: Transmission Dynamics of SARS-CoV-2: Inference and Projection

January 21, 2021
12:00 PM - 1:00 PM
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The COPSS-NISS COVID-19 Data Science webinar series is co-organized by the Committee of the Presidents of Statistical Societies (COPSS) and its five charter member societies (ASAENARIMSSSC, and WNAR), as well as NISS. This bi-weekly seminar features the latest research that is positioned on the cusp of new understanding and analysis of COVID-19 pandemic data, and promotes data-driven research and decision making to combat COVID-19. Find out more about this series and view all the previous sessions on the Webinar Series page.

Dynamic models of infectious disease systems are often used to study the epidemiological characteristics of disease outbreaks, the ecological mechanisms and environmental conditions affecting transmission, and the suitability of various mitigation and intervention strategies. In recent years these same models have been employed to generate probabilistic forecasts of infectious disease incidence at the population scale. In this webinar, Dr. Jeffrey Shaman, Professor in the Department of Environmental Health Sciences and Director of the Climate and Health Program at Columbia University Mailman School of Public Health, will present research from his group describing application of model systems and combined model-inference frameworks to the study of SARS-CoV-2.



Jeffrey Shaman, Professor
Environmental Health Sciences (in the International Research Institute for Climate and Society/Earth Institute)
Director, Climate and Health Program
Columbia University

Jeffrey Shaman is a Professor in the Department of Environmental Health Sciences and Director of the Climate and Health Program at the Columbia University Mailman School of Public Health. He studies the survival, transmission and ecology of infectious agents, including the effects of meteorological and hydrological conditions on these processes. Work-to-date has primarily focused on mosquito-borne and respiratory pathogens. He uses mathematical and statistical models to describe, understand, and forecast the transmission dynamics of these disease systems, and to investigate the broader effects of climate and weather on human health.


Roni Rosenfeld, Professor and Head
Machine Learning Department, School of Computer Science
Carnegie Mellon University


Lily Wang, Professor
Department of Statistics
Iowa State University

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