We aim to improve infectious disease surveillance and control through mathematical modeling, optimization, and translational collaborations with public health decision makers. Methodologically, we will advance the application of mathematical modeling to inform public heath policy decisions by (i) integrating large-scale optimization, economic analyses, and uncertainty quantification into mathematical models of disease transmission in complex and dynamic populations, and by (ii) developing goal-oriented optimization methods for integrating diverse data sources to improve infectious disease surveillance systems. We will apply these approaches using data on influenza, respiratory syncytial virus (RSV), pertussis, West Nile virus (WNV), and dengue from around the world to elucidate the complex drivers of outbreaks and control and to identify highly effective, economical, and feasible control policies. We will disseminate our models and results to public health authorities and develop user-friendly modeling tools to facilitate preparedness and real-time decision- making regarding the optimal distribution of limited disease control resources. Thus, our interdisciplinary research will expand the methodological toolkit for modeling infectious disease dynamics, provide better strategies for tracking and mitigating epidemics, and make science, data, and models more broadly accessible to public health agencies engaged in the global fight against infectious diseases.

Public Health Relevance

By applying optimization, economic, and uncertainty quantification methods to mathematical models of both disease dynamics and surveillance systems, we will answer fundamental questions about the spread of influenza, respiratory syncytial virus (RSV), pertussis, dengue, and West Nile virus (WNV), identify innovative strategies for improving the detection and control of these diseases, and produce translational public health decision-support tools.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01GM087719-09
Application #
9267996
Study Section
Special Emphasis Panel (ZGM1-BBCB-5 (MI))
Program Officer
Janes, Daniel E
Project Start
2009-06-01
Project End
2019-04-30
Budget Start
2017-05-01
Budget End
2018-04-30
Support Year
9
Fiscal Year
2017
Total Cost
$588,512
Indirect Cost
$122,308
Name
Yale University
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
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Fitzpatrick, Meagan C; Gray, Glenda E; Galvani, Alison P (2018) The Challenge of Vanquishing HIV for the Next Generation-Facing the Future. JAMA Pediatr 172:609-610
Ndeffo-Mbah, Martial L; Vigliotti, Vivian S; Skrip, Laura A et al. (2018) Dynamic Models of Infectious Disease Transmission in Prisons and the General Population. Epidemiol Rev 40:40-57
Fallah, Mosoka P; Skrip, Laura A; Raftery, Philomena et al. (2017) Bolstering Community Cooperation in Ebola Resurgence Protocols: Combining Field Blood Draw and Point-of-Care Diagnosis. PLoS Med 14:e1002227

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