The Center for Communicable Disease Dynamics (CCDD) at Harvard School of Public Health (HSPH) will serve as a national and international center for research, teaching, and outreach to public health decision makers and other stakeholders in infectious disease modeling and epidemiology. The Center will expand and augment thriving training programs in infectious disease epidemiology and health decision science while strengthening connections within Harvard University and the surrounding area to draw in bioinformaticians, biostatisticians, evolutionary biologists, and others to activities related to infectious disease modeling and data analysis. Substantive research will focus on antimicrobial resistance, communicable disease seasonality, and the broad area of policy decisions around the allocation of scarce control measures. We will also develop novel methodology, emphasizing tools for analyzing emerging epidemics and directing control measures to optimize their effectiveness, as well as on the use of genetic and ultimately genome sequence data to track epidemics and to detect the effects of natural selection on pathogen populations. The Center will have numerous activities to make its resources, people, and methods widely available and to maintain productive interactions with public health professionals, decision makers and others. Software, including an epidemic analysis """"""""dashboard,"""""""" will be developed in partnership with public health collaborators from the US and Hong Kong. A short course in infectious disease modeling will be designed and offered annually at rotating sites on several continents;materials for this course and for a novel course on infectious disease statistics (to be developed at HSPH) will be made available by web. An annual symposium on a topic of public health importance will host academic and policymaking experts. Educational activities for science journalists will be set up. Short-term visiting fellowships for CDC and other scientists will be set up to facilitate collaborations, and a semester sabbatical for a faculty member from a minority serving institution (MSI) will be set up. Additional activities for outreach to disadvantaged group members will occur, including an """"""""ambassador"""""""" program and funded masters studentships with matching university funds. Intensive efforts will be made to integrate research, outreach, and teaching functions.

Public Health Relevance

Infectious disease modeling is an increasingly important part of decision making about the use and funding of interventions to control the spread of diseases. This Center will meet needs for enhanced training of modelers, better communication between modelers and policymakers, better methods and software for infectious disease data analysis, and enhanced understanding of key questions in infectious disease dynamics.

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-CBCB-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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Zu Erbach-Schoenberg, Elisabeth; Alegana, Victor A; Sorichetta, Alessandro et al. (2016) Dynamic denominators: the impact of seasonally varying population numbers on disease incidence estimates. Popul Health Metr 14:35
Wu, Joseph T; Peak, Corey M; Leung, Gabriel M et al. (2016) Fractional dosing of yellow fever vaccine to extend supply: a modelling study. Lancet 388:2904-2911
Yaesoubi, Reza; Cohen, Ted (2016) Identifying cost-effective dynamic policies to control epidemics. Stat Med 35:5189-5209
Ip, Dennis K M; Lau, Lincoln L H; Chan, Kwok-Hung et al. (2016) The Dynamic Relationship Between Clinical Symptomatology and Viral Shedding in Naturally Acquired Seasonal and Pandemic Influenza Virus Infections. Clin Infect Dis 62:431-7
Lipsitch, Marc; Jha, Ayan; Simonsen, Lone (2016) Observational studies and the difficult quest for causality: lessons from vaccine effectiveness and impact studies. Int J Epidemiol :
Gaughan, Andrea E; Stevens, Forrest R; Huang, Zhuojie et al. (2016) Spatiotemporal patterns of population in mainland China, 1990 to 2010. Sci Data 3:160005
Blackwood, J C; Childs, L M (2016) The role of interconnectivity in control of an Ebola epidemic. Sci Rep 6:29262
(2016) Impact of Host Heterogeneity on the Efficacy of Interventions to Reduce Staphylococcus aureus Carriage - CORRIGENDUM. Infect Control Hosp Epidemiol 37:244
Worby, Colin J; O'Neill, Philip D; Kypraios, Theodore et al. (2016) Reconstructing transmission trees for communicable diseases using densely sampled genetic data. Ann Appl Stat 10:395-417
Zelner, Jonathan L; Murray, Megan B; Becerra, Mercedes C et al. (2016) Identifying Hotspots of Multidrug-Resistant Tuberculosis Transmission Using Spatial and Molecular Genetic Data. J Infect Dis 213:287-94

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