We propose a competing renewal of the MIDAS Center for Communicable Disease Dynamics (CCDD) at Harvard School of Public Health. Building on a four-year record of over 170 peer-reviewed publications and significant achievements in outreaching and education, we propose a multipronged approach to extend the activities of this Center of Excellence into the next funding period. Combining expertise in mathematical and statistical modeling of infection with related disciplines, we will undertake methodologic development and application to a range of public health problems. Project I. Pathogen Genomics and Evolution develops computational and statistical models to infer local and global transmission and clustering of infections, antigenic change by recombination, and evolution under vaccine-mediated selection. Project II. New Analytic Methods for New Data Sources develops and tests statistical approaches for interpreting participatory surveillance and mobile phone data for parameterization and testing of transmission-dynamic models, uses hydrological modeling to build risk maps for malaria, and develops the statistical theory of negative controls. Project III. Accounting for Measured and Unmeasured Heterogeneity in Host Populations proposes a variety of studies to assess the contribution of host heterogeneity to model parameter estimation for infections with different transmission routes and creates models incorporating two key sources of such heterogeneity: virus interference and dose-response relationships. Project IV. Understanding and Controlling Antibiotic Resistance studies drug resistance in gonorrhea, tuberculosis, and pneumococcal infections, applying methods from earlier projects to understand the genetic and selective origins of resistance and the mechanisms underlying observed heterogeneities in its prevalence. Project V. Collaborative Modeling for Assessment and Optimization in Public Health proposes work with public health partners to address two key aspects of their work ~ burden/severity estimation and optimization of interventions - using a range of modeling approaches. Software development and sharing and Policy Studies are integral parts of our research activities. In Outreach and Education we propose an ambitious set of initiatives aimed at pipeline and recruiting, training the next generation of modelers, and engaging colleagues in policy, academia and journalism.

Public Health Relevance

Preparedness for public health emergencies including emerging infectious diseases requires a foundation of statistical, mathematical, epidemiological, biological and computational knowledge and infrastructure to respond quickly with policy-relevant analyses. CCDD, working as part of the MIDAS network, pursues all of these avenues, building understanding of disease transmission through research and close collaboration with decision makers to answer relevant questions at times of urgent need.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZGM1-BBCB-5 (MI))
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Sheeley, Douglas
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Harvard University
Public Health & Prev Medicine
Schools of Public Health
United States
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Cobey, Sarah; Baskerville, Edward B; Colijn, Caroline et al. (2017) Host population structure and treatment frequency maintain balancing selection on drug resistance. J R Soc Interface 14:
Eyal, Nir; Lipsitch, Marc (2017) Vaccine testing for emerging infections: the case for individual randomisation. J Med Ethics 43:625-631
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Andam, Cheryl P; Worby, Colin J; Gierke, Ryan et al. (2017) Penicillin Resistance of Nonvaccine Type Pneumococcus before and after PCV13 Introduction, United States. Emerg Infect Dis 23:1012-1015

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