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Research Project Grants – R01s


  • 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 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.
  • 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.
  • Development of Methodology to Measure Incidence and Transmission of Mycobacterium Tuberculosis

    Principal Investigator: 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.

  • 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.
  • Future of Influenza Vaccine Strategies Given Interference and Choice

    Principal Investigators: Richard Zimmerman, M.D., and Kenneth Smith, M.D., University of Pittsburgh

     

    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.
  • 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 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 the Evolutionary and Public Health Impacts of HIV Adaptation in Response to Vaccination

    Joshua Herbeck

    Principal Investigator: Joshua Herbeck, Ph.D., University of Washington, Seattle

     

    This team is developing a novel modeling framework that integrates HIV evolutionary processes into mathematical models of HIV epidemiology and vaccination to enable more accurate predictions of vaccine impact and improved vaccine design.

  • 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.
  • 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.
  • Vaccine Hesitancy and Erosion of Herd Immunity: Harnessing Big Data to Forecast Disease Re-Emergence

    Shweta Bansal

    Principal Investigator: Shweta Bansal, Ph.D., Georgetown University

     

    The PI works to characterize the relationship between behavioral factors like vaccine hesitancy and the re-emergence of vaccine-preventable diseases.
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This page last reviewed on October 11, 2017