The overall objective of this research is to develop, validate, and implement mathematical and statistical models for the transmission and within-host dynamics of naturally occurring infectious diseases and bioterrorism agents. These models will be used to assess the effectiveness and efficacy of various interventions to aid the distribution and allocation of resources in response to infectious disease outbreaks.
The specific aims are as follows: 1. To develop epidemic mathematical models for the transmission of naturally occurring infectious diseases and bioterrorism agents: a. To develop or further develop mathematical models for important infectious disease threats including influenza, cholera, dengue fever, TB and new emerging infectious disease threats. b. To use the epidemic mathematical and statistical models to evaluate the effectiveness of interventions involving surveillance and containment, vaccination, antimicrobials, social distancing, and other control strategies for the infectious diseases in specific aim 1 .a. c. To use and develop statistical methods to estimate the important parameters and variables from data available for the infectious diseases. d. To develop frameworks to make the developed mathematical and statistical models available to public health organizations and researchers. e. To develop a comprehensive framework using graph theory for the estimation of social contact networks for acute infectious diseases. 2. To develop models at the within-host level which allow us to link the dynamics of infection of individual hosts with the transmission of the pathogen in the host population: a. To construct models to examine the within-host dynamics of pathogens. b. To extend the models developed in specific aim 2. a. to include antiviral treatment and prophylaxis as well as vaccination. c. To explicitly link the models of within-host dynamics of infection with its spread between hosts. Public Health Relevance: The introduction of naturally occurring infectious diseases or bioterrorism agents into the population continues to pose a considerable public health threat to the nation and the world. This research will prove analytical and mathematical tools to help with the rapid assessment of how these infectious agents are spreading and how to contain them in real time. This work also will provide methods for control should containment fail.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project--Cooperative Agreements (U01)
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Special Emphasis Panel (ZGM1-CBCB-5 (MI))
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Sheeley, Douglas
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Fred Hutchinson Cancer Research Center
United States
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Feldstein, Leora R; Matrajt, Laura; Elizabeth Halloran, M et al. (2016) Extrapolating theoretical efficacy of inactivated influenza A/H5N1 virus vaccine from human immunogenicity studies. Vaccine 34:3796-802
Koepke, Amanda A; Longini Jr, Ira M; Halloran, M Elizabeth et al. (2016) PREDICTIVE MODELING OF CHOLERA OUTBREAKS IN BANGLADESH. Ann Appl Stat 10:575-595
Potter, Gail E; Smieszek, Timo; Sailer, Kerstin (2015) Modeling workplace contact networks: The effects of organizational structure, architecture, and reporting errors on epidemic predictions. Netw Sci (Camb Univ Press) 3:298-325
Yao, Hong-Wu; Yang, Yang; Liu, Kun et al. (2015) The spatiotemporal expansion of human rabies and its probable explanation in mainland China, 2004-2013. PLoS Negl Trop Dis 9:e0003502
Yang, Y; Zhang, Y; Fang, L et al. (2015) Household transmissibility of avian influenza A (H7N9) virus, China, February to May 2013 and October 2013 to March 2014. Euro Surveill 20:21056
Ma, Mai-Juan; Yang, Yang; Wang, Hai-Bin et al. (2015) Transmissibility of tuberculosis among school contacts: an outbreak investigation in a boarding middle school, China. Infect Genet Evol 32:148-55
Matrajt, Laura; Britton, Tom; Halloran, M Elizabeth et al. (2015) One versus two doses: What is the best use of vaccine in an influenza pandemic? Epidemics 13:17-27
Tran, Cuc H; Sugimoto, Jonathan D; Pulliam, Juliet R C et al. (2014) School-located influenza vaccination reduces community risk for influenza and influenza-like illness emergency care visits. PLoS One 9:e114479
Halloran, M Elizabeth; Longini Jr, Ira M (2014) Emerging, evolving, and established infectious diseases and interventions. Science 345:1292-4
Yang, Yang; Halloran, M Elizabeth; Chen, Yanjun et al. (2014) A pathway EM-algorithm for estimating vaccine efficacy with a non-monotone validation set. Biometrics 70:568-78

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