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Posted: peterb on  Apr 15 10:08:57 AM
Title: Process-Based Forecasting of Infectious Disease Outbreaks  
Jeffrey Shaman
Professor, Department of Environmental Health Sciences and Director of the Climate and Health Program, Columbia University Mailman School of Public Health
Sponsor: Carnegie Mellon University  >  College of Humanities and Social Sciences  >  Department of Statistics
Series: Carnegie Mellon Statistics and Data Science Seminar
Date: Apr 15, 2019 4:30 PM - 5:30 PM
Location: B-103 Hamerschlag Hall
Groups Posted: Big Data Computational/Systems Biology, Bioinformatics Intelligent Systems Program 

Refreshments: 4:00-4:30 p.m., outside Baker Hall 232M

Abstract:  Dynamic models of infectious disease systems are often used to study the epidemiological characteristics of disease outbreaks, the ecological mechanisms 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.  Here I describe efforts within my own group developing model systems and combined model-inference frameworks designed for the simulation and forecast of disease outbreaks.  Methodological advances and operational forecasting for a number of diseases, including influenza, Ebola and West Nile virus, are presented, as well as ongoing efforts to validate and improve forecast accuracy.

Bio: 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.  His research interests include study of the survival, transmission and ecology of infectious agents, including the effects of meteorological and hydrological conditions on these phenomena. He uses mathematical and statistical models to describe, understand, and forecast the transmission dynamics of infectious disease systems, and to investigate the broader effects of climate and weather on human health.


Interest Area: Computer & Information Science & Engineering, Mathematical & Physical Sciences, Social, Behavioral & Economic Sciences
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