Scientific Program 5.1 Research Project 1: Modeling, Spatial, Statistics The overall objective of this research project is to develop, validate, and implement mathematical and statistical models for the transmission 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 or further develop mathematical and statistical models for important infectious disease threats including influenza, cholera, dengue fever, TB, novel coronaviruses, and new emerging infectious diseases. This will involve the development of general models to understand the transsmission of infectious diseases, as well as the development of specific models for each infectious disease studied. 2. 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. 3. To use and develop statistical methods to estimate the important parameters and variables from data available for the infectious diseases. These statistical methods will include both novel and innovative likelihood and empirical, hierarchical Bayesian models, as well as MCMC methods

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Specialized Center--Cooperative Agreements (U54)
Project #
Application #
Study Section
Special Emphasis Panel (ZGM1-BBCB-5 (MI))
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Fred Hutchinson Cancer Research Center
United States
Zip Code
Brouwer, Andrew F; Eisenberg, Joseph N S; Pomeroy, Connor D et al. (2018) Epidemiology of the silent polio outbreak in Rahat, Israel, based on modeling of environmental surveillance data. Proc Natl Acad Sci U S A 115:E10625-E10633
Feldstein, Leora R; Rowhani-Rahbar, Ali; Staples, J Erin et al. (2018) An Assessment of Household and Individual-Level Mosquito Prevention Methods during the Chikungunya Virus Outbreak in the United States Virgin Islands, 2014-2015. Am J Trop Med Hyg 98:845-848
Ma, Mai-Juan; Zhao, Teng; Chen, Shan-Hui et al. (2018) Avian Influenza A Virus Infection among Workers at Live Poultry Markets, China, 2013-2016. Emerg Infect Dis 24:1246-1256
Faulkner, James R; Minin, Vladimir N (2018) Locally Adaptive Smoothing with Markov Random Fields and Shrinkage Priors. Bayesian Anal 13:225-252
Ma, Mai-Juan; Liu, Cheng; Wu, Meng-Na et al. (2018) Influenza A(H7N9) Virus Antibody Responses in Survivors 1 Year after Infection, China, 2017. Emerg Infect Dis 24:663-672
Lee, Juhye M; Huddleston, John; Doud, Michael B et al. (2018) Deep mutational scanning of hemagglutinin helps predict evolutionary fates of human H3N2 influenza variants. Proc Natl Acad Sci U S A 115:E8276-E8285
Viboud, Cécile; Sun, Kaiyuan; Gaffey, Robert et al. (2018) The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt. Epidemics 22:13-21
Pavía-Ruz, Norma; Diana Patricia Rojas; Salha Villanueva et al. (2018) Seroprevalence of Dengue Antibodies in Three Urban Settings in Yucatan, Mexico. Am J Trop Med Hyg 98:1202-1208
Massaro, Emanuele; Ganin, Alexander; Perra, Nicola et al. (2018) Resilience management during large-scale epidemic outbreaks. Sci Rep 8:1859
Yang, Yang; Meng, Ya; Halloran, M Elizabeth et al. (2018) Dependency of Vaccine Efficacy on Preexposure and Age: A Closer Look at a Tetravalent Dengue Vaccine. Clin Infect Dis 66:178-184

Showing the most recent 10 out of 134 publications