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Research Network

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Centers of Excellence

Center for Communicable Disease Dynamics
Center for Inference and Dynamics of Infectious Diseases
Computational Models of Infectious Disease Threats

Research Groups

Development and Dissemination of Operational Real-Time Respiratory Virus Forecast
Dynamic Data-Driven Decision Models for Infectious Disease Control
Characterization of Temperature-Driven Heterogeneity in Mosquito Populations
Forecasting Tipping Points in Emerging and Re-Emerging Infectious Diseases
Future of Influenza Vaccine Strategies Given Interference and Choice
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
Real-Time Tracking of Virus Evolution for Vaccine Strain Selection and Epidemiological Investigation
Statistical Methods for Real-Time Forecasts of Infectious Disease: Dynamic Time-Series and Machine-Learning Approaches
Synthetic Information Systems for Better Informing Public Health Policymakers

Informatics Resource

MIDAS Informatics Services Group (ISG)

Past Projects

Computational Models of Pathogen Evolution and Vaccination
Containing Bioterrorist and Emerging Infectious Diseases
Modeling Food and Water Borne Disease
Modeling Health System Infectious Disease Data
Modeling of Infectious Disease Agent Study Information Technology Resource
Modeling MRSA in the Community


Centers of Excellence

Center for Communicable Disease Dynam​ics Link to external Web site
Principal investigator: Marc Lipsitch, D.Phil., Harvard School of Public Health

This center applies mathematical and statistical modeling methods to public health problems, with particular focus on the impact of vaccine use on the evolution of pathogens.

Center for Inference and Dynamics of Infectious Diseases Link to external Web site
Principal investigator: M. Elizabeth Halloran, M.D., D.Sc., Fred Hutchinson Cancer Research Center

This center oversees a collaborative effort among eight research institutions across the United States focusing on a multidisciplinary approach to computational, statistical and mathematical modeling of influenza, dengue fever, polio and other infectious diseases. The center also supports training and outreach programs in infectious disease modeling.

Computational Models of Infectious Disease Threats Link to external Web site
Principal investigator: Donald Burke, M.D., University of Pittsburgh

This center focuses on developing innovative software and data resources to build a computational framework for reconstructing and predicting infectious disease dynamics and evaluating interventions.

Research Groups

Characterization of Temperature-Driven Heterogeneity in Mosquito Populations
Principal investigator: Rebecca Christofferson, Ph.D., Louisiana State University A&M College

This research team is examining the effects of temperature on mosquito life history and vector competence, which is included in deciding the model parameters and structure.

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 it 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
Principal investigators: Alison Galvani, Ph.D., Yale University; Lauren Meyers, Ph.D., University of Texas at Austin

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
Principal investigators: John Drake, Ph.D., and Andrew Park, Ph.D., University of Georgia; Matthew Ferrari, Ph.D., Penn State University; Pejman Rohani, Ph.D., and Bogdan Epurean, Ph.D., University of Michigan, Ann Arbor

This research group focuses on developing modeling methods that could serve as an early warning system for infectious disease outbreaks.

Future of Influenza Vaccine Strategies Given Interference and Choice
Principal investigator: Richard Zimmerman, M.D., and Kenneth Smith, M.D., University of Pittsburg

These scientists are developing methods for Markov cohort decision analysis, equation-based dynamic transmission modeling, and agent-based modeling, all aimed at optimization of vaccine selection strategies, streamlining of vaccination schedules, and evaluation and optimization of influenza vaccination policy.

Modeling Contact Investigation and Rapid Response
Principal investigator: Travis Porco, Ph.D., University of California, San Francisco

This research group uses computational models to determine what kinds of information to collect from people exposed to an infectious disease and how to use the data to design effective intervention strategies.

Modeling Epidemic Infectious Diseases Using Sequence Analysis
Principal investigator: Sergei Pond, Ph.D., University of California, San Diego

This research group models the rapidly evolving genetic sequences of pathogens, studies how this information can be used to better understand disease transmission networks within communities and evaluates the impact of control and intervention measures.

Modeling the Effects of the Environment on Enteric Pathogen Dynamics
Principal investigator: Joseph Eisenberg, Ph.D., University of Michigan, Ann Arbor

This research group models the contribution of environmental factors to disease outbreaks, including the movement of pathogens through water, air and food as well as how those pathogens become transmissible.

Models for Synthesizing Molecular, Clinical and Epidemiological Data, and Translation
Principal investigators: Neil Morris Ferguson, Ph.D., Chistophe Fraser, Ph.D., and Steven Riley, Ph.D., Imperial College London; Simon Cauchemez, Ph.D., Institut Pasteur, Paris

This international research team is developing new machine-learning methods to find patterns of disease transmission; integrate large, complex datasets generated by public health efforts; and derive new ways to improve the validity and predictive ability of infectious disease models.

Predicting Vector-Borne Virus Transmission Dynamics and Emergence Potential
Principal investigator: Christopher Mores, Sc.D., Louisiana State University

This research group develops mathematical models of the spread of mosquito-borne diseases, including dengue fever. The goal of the work is to help researchers better understand how to interrupt transmission to prevent or slow outbreaks.

Quantifying Model Uncertainty for Forecasting the Spread of Infectious Diseases
Principal investigator: Sara Del Valle, Ph.D., Los Alamos National Laboratory

This r​esearch group studies how to model changes in people's behavior in response to an infectious disease outbreak and the impact of uncertainty in the data, such as vaccination rates or number of infected people, on infectious disease models.

Real-Time Tracking of Virus Evolution for Vaccine Strain Selection and Epidemiological Investigation
Principal investigators: Trevor Bedford, Ph.D., Fred Hutchinson Cancer Research Center

This research group is working on making use of extensive and publicly available influenza viral sequence data to predict lineages that have high probability of outbreak in future years.

Statistical Methods for Real-Time Forecasts of Infectious Disease: Dynamic Time-Series and Machine-Learning Approaches
Principal investigators: Nicholas Reich, Ph.D., University of Massachusetts, Amherst

This research group works on developing and disseminating robust statistical models for predicting infectious diseases in real-time.

Synthetic Information Systems for Better Informing Public Health Policymakers
Principal investigator: Stephen Eubank, Ph.D., Virginia Bioinformatics Institute

This research group designs, builds and validates models of disease spread and prediction systems based on activities in a social network. Using mathematical and computational methods, the group is exploring the effects of human contact patterns in urban areas on disease transmission dynamics and the effectiveness of particular response strategies.

Informatics Resource

MIDAS Informatics Services Group Link to external Web site
Principal investigator:
Michael Wagner, Ph.D., University of Pittsburgh

This informatics resource is building a Web-based platform that will allow researchers to access modeling software and data.

Past Projects

Computational Models of Pathogen Evolution and Vaccination
Principal investigators: Robin Bush, Ph.D., University of California, Irvine

This research group developed computational models to study the molecular basis of viral evolution.

Containing Bioterrorist and Emerging Infectious Diseases
Principal investigators: Ira Longini, Ph.D., University of Florida; Elizabeth Halloran, M.D., D.Sc., Fred Hutchinson Cancer Research Center

Drawing on expertise in biostatistics and epidemiological field work, this research group created simulation models for the transmission of infectious diseases such as flu, cholera, dengue fever and tuberculosis.

Modeling Food and Water Borne Disease
Principal investigator: Gary Smith, Ph.D., University of Pennsylvania School of Veterinary Medicine

This research group developed hierarchical models for the spatio-temporal dynamics of infectious disease.

Modeling Health System Infectious Disease Data
Principal investigator: Richard Platt, M.D.

This research group developed space-time models to detect emerging outbreaks before they spread.

Modeling of Infectious Disease Agent Study Information Technology Resource
Principal investigators: Diane Wagener, Ph.D., and Phil Cooley, Research Triangle Institute

This informatics center provided and developed a number of informatics, analytic and statistical tools in a high-performance computational environment. The group also provided programming expertise and data management resources.

Modeling MRSA in the Community
Principal investigators: Diane Lauderdale, Ph.D., University of Chicago; Charles Macal, Ph.D., P.E., Argonne National Laboratory

With substantial expertise on the biology of MRSA, this research group developed models to understand how patterns of contact and behavior among individuals affect MRSA spread. ​​​

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This page last reviewed on March 07, 2017