The goal of this research is to develop a quantitative understanding of the dynamics of pathogens such as influenza and dengue that exhibit strain variation. We will use this understanding to design strategies for vaccination and control of these infections. The evolution of these pathogens is affected by two factors. The first is the generation of variation in the virus. This is determined by the molecular constraints that limit the mutations tolerated by the virus. The second is the selection that operates on the generated variation. This is determined by both the fitness of the virus and the immune status of individuals in the population. Understanding the selective forces on the virus is complicated by population heterogeneity which arises from previous exposure of individuals to different numbers of strains and their antigenic composition. Consequently we will take a multi-scale approach that integrates key processes at three scales: (i) Evolutionary changes in the virus. At the molecular level we will use computational models to predict how mutations in the key proteins of the influenza virus affect its fitness. In doing so we will determine the extent to which molecular constraints limit virus evolution. (ii) Within-host dynamics of influenza infections. We will develop models for the dynamics of infection and immunity in an individual. These models will allow us to determine how infection with influenza changes the level of immunity and how this impacts the dynamics of infection following exposure to new virus strains. These models will be applied to understanding the generation of immunity following vaccination with the killed subunit vaccine as well as the live attenuated virus. In doing so we hope to optimize the choice of strains to include in annual influenza vaccination programs and in the longer term help design universal influenza vaccines that provide protection against all strains. (iii) Epidemiological models that track the generation and spread when multiple virus strains in the population of individual with different and changing levels of immunity.

Public Health Relevance

This project develops computational models for understanding and predicting the dynamics of pathogens such as influenza and dengue that exhibit strain variation. This will help the public health community with the design and choice of vaccines and other control measures for these pathogens. This project will integrate with the other proposed Center activities for predicting and controlling evolving pathogens.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
1U54GM111274-01
Application #
8796475
Study Section
Special Emphasis Panel (ZGM1-BBCB-5 (MI))
Project Start
Project End
Budget Start
2014-09-12
Budget End
2015-06-30
Support Year
1
Fiscal Year
2014
Total Cost
$404,768
Indirect Cost
$100,622
Name
Fred Hutchinson Cancer Research Center
Department
Type
DUNS #
078200995
City
Seattle
State
WA
Country
United States
Zip Code
98109
Tsang, Tim K; Chen, Tian-Mu; Longini Jr, Ira M et al. (2018) Transmissibility of Norovirus in Urban Versus Rural Households in a Large Community Outbreak in China. Epidemiology 29:675-683
PavĂ­a-Ruz, Norma; Barrera-Fuentes, Gloria Abigail; Villanueva-Jorge, Salha et al. (2018) Dengue seroprevalence in a cohort of schoolchildren and their siblings in Yucatan, Mexico (2015-2016). PLoS Negl Trop Dis 12:e0006748
Hladish, Thomas J; Pearson, Carl A B; Patricia Rojas, Diana et al. (2018) Forecasting the effectiveness of indoor residual spraying for reducing dengue burden. PLoS Negl Trop Dis 12:e0006570
Rojas, Diana Patricia; Barrera-Fuentes, Gloria Abigail; Pavia-Ruz, Norma et al. (2018) Epidemiology of dengue and other arboviruses in a cohort of school children and their families in Yucatan, Mexico: Baseline and first year follow-up. PLoS Negl Trop Dis 12:e0006847
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
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
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

Showing the most recent 10 out of 134 publications