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.
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.
|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|
|Ho, Lam Si Tung; Xu, Jason; Crawford, Forrest W et al. (2018) Birth/birth-death processes and their computable transition probabilities with biological applications. J Math Biol 76:911-944|
|Liu, Quan-Hui; Ajelli, Marco; Aleta, Alberto et al. (2018) Measurability of the epidemic reproduction number in data-driven contact networks. Proc Natl Acad Sci U S A 115:12680-12685|
|Gallagher, Molly E; Brooke, Christopher B; Ke, Ruian et al. (2018) Causes and Consequences of Spatial Within-Host Viral Spread. Viruses 10:|
Showing the most recent 10 out of 134 publications