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Research Network

Centers of Excellence

Research Groups

Informatics Resource

Past Projects


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

  • A Three-population Three-scale Social Network Model to Assess Disease Dispersion
    Principal investigators: Ling Bian, Ph.D., State University of New York at Buffalo, and Cynthia Chen, Ph.D., University of Washington

    This research team is working on constructing a contact network model for the Buffalo, NY metro area by fusing multiple data sources including mobile phone data from local carrier in order to capture daily patterns of interpersonal contacts and use these to model infectious disease dispersion.
  • 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.
  • Collaborative Research: A Mathematical Theory of Transmissible Vaccines
    Principal investigator: Scott Nuismer, Ph.D., University of Idaho

    This research group is working to develop a mathematical model for the evolution of transmissible vaccines. This team is also testing the results using an experimental viral system.
  • Computational Studies of Virus-host Interactions Using Metagenomics Data and Applications
    Principal investigators: Fengzhu Sun, Ph.D., University of Southern California; and Nathan Ahlgren, Ph.D., Clark University

    This research group is working on the development of statistical and computational methods to identify viral sequences and virus-host interactions from metagenomics sequencing data and to investigate the effect of viruses on complex diseases.
  • Computational Discovery of Effective Hepatitis C Intervention Strategies
    Principal investigators: Harel Dahari, Ph.D., Loyola University Chicago; Basmattee Boodram, Ph.D., University of Illinois at Chicago; and Jonathan Ozik, Ph.D., University of Chicago

    The PIs work to develop a data-driven agent-based model of daily risk activities for persons who inject drugs to identify the most effective intervention strategies for elimination of hepatitis C.
  • 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.
  • Development of Methodology to Measure Incidence and Transmission of Mycobacterium Tuberculosis
    Principal investigators: Laura White, Ph.D., Boston University

    This research group develops novel approaches to monitor the incidence and transmission of Tuberculosis (TB). This will enable our understanding of the spread of TB in populations and areas where the burden of TB disease is greatest.
  • 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.
  • Integrative Modeling of Study Design and Transmission Dynamics to Infer Epidemic Drivers and Inform Decision-making: Applications to HIV and other Emerging Pathogens.
    Principal investigator: Steven Bellan, Ph.D., University of Georgia

    This research group takes a broad quantitative perspective to address applied questions in infectious disease epidemiology. Their research spans multiple pathogen systems (HIV, Ebola, anthrax, rabies) by integrating mathematical and statistical models with empirical data to understand infectious disease processes and how to control them.
  • Measuring Social Behavior via Dynamic Network Interaction.
    Principal investigator: Kirk Dombrowski, Ph.D., University of Nebraska, Lincoln

    This research team is working to build, test, and implement a cost-effective mobile/wearable cross-platform continuous time interaction (CTI) data acquisition system operated via a web-based administration service.
  • Methods for Reducing Spatial Uncertainty and Bias in Disease Surveillance
    Principal investigator: Justin Lessler, Ph.D., Johns Hopkins University.

    The PI works on real-time dengue disease forecasting by developing and evaluating inferential methods to evaluate the spatiotemporal distribution of dengue.
  • Modeling and Control of Environmentally Transmitted Pathogens
    Principal investigator: Cristina Lanzas, Ph.D., North Carolina State University

    This research group is developing and analyzing mathematical models that address relevant mechanisms and spatial heterogeneity associated with environmental transmission. Using both queuing theory and spacial agent-based models, this team is evaluating the success of environmental interventions, and to use optimal control theory to identify preferred interventions.
  • 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.
  • New Approaches to Measuring and Containing the Spatial Spread of Human Pathogens
    Principal investigators: Caroline Buckee, Ph.D., Harvard School of Public Health

    This research program supports the development of analytical methods and tools for integrating human mobility data (i.e., aggregate mobile phone usage data) and parasite population genomic data (i.e., genome sequencing data from spatially sampled parasites) to understand the impact of human mobility on epidemic infectious diseases.
  • 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.
  • Spatio-temporal Data Integration Methods for Optimizing Infectious Disease Surveillance in LMICs
    Principal investigators: Justin V. Remais, Ph.D., University of California, Berkeley; Howard Chang, Ph.D., and Lance Waller, Ph.D., Emory University

    This research group is developing statistical techniques for integrating data from multiple surveillance systems; developing methods for simulating and optimizing surveillance networks to detect existing and emerging infectious diseases under changing epidemiological conditions; examining how surveillance systems perform under different configurations, and estimating the optimal allocation of surveillance resources under various constraints.
  • 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.
  • Systems Analysis of Social Pathways of Epidemics to Reduce Health Disparities
    Principal investigators: Achla Marathe, Ph.D., and Kaja Abbas, Ph.D., Virginia Polytechnic Institute and State University

    This research team is conducting systems analysis of social pathways of epidemics to reduce health disparities by incorporating social behavior into mathematical models of infectious disease transmission dynamics, with a focus on influenza like illness. The inferences of this project will improve our understanding of the impact of different control and prevention strategies for infectious disease epidemics in general and influenza epidemics in particular.

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 August 18, 2017