Models of Infectious Disease Agent Study (MIDAS)
Development and Dissemination of Operational Real-Time Respiratory Virus Forecast
Principal Investigator: Jeffrey Shaman, Ph.D., Columbia University Mailman School of Public Health
This research group is expanding the real-time flu forecasting system that built using methods from weather and climate modeling and applying it to additional infectious diseases, including other respiratory viruses and Ebola.
Dynamic Data-Driven Decision Models for Infectious Disease Control
This research team is developing new models of disease spread with the goal of improving infectious disease tracking and optimizing intervention strategies.
Forecasting Tipping Points in Emerging and Re-Emerging Infectious Diseases
This research group focuses on developing modeling methods that could serve as an early warning system for infectious disease outbreaks.
Modeling Contact Investigation and Rapid Response
Modeling Epidemic Infectious Diseases Using Sequence Analysis
Modeling the Effects of the Environment on Enteric Pathogen Dynamics
Models for Synthesizing Molecular, Clinical and Epidemiological Data, and Translation
Predicting Vector-Borne Virus Transmission Dynamics and Emergence Potential
Quantifying Model Uncertainty for Forecasting the Spread of Infectious Diseases
Synthetic Information Systems for Better Informing Public Health Policymakers
This page last reviewed on
10/11/2017 1:58 PM
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