This is a proposal for a multi-institutional MIDAS Center of Excellence called the Center for Statistics and Quantitative Infectious Diseases (CSQUID). The mission the Center is to provide national and international leadership. The lead institution is the Fred Hutchinson Cancer Research Center (FHCRC). Other participating institutions are the University of Florida, Northeastern University, University of Michigan, Emory University, University of Washington (UW), University of Georgia, and Duke University. The proposal includes four synergistic research projects (RP) that will develop cutting-edge methodologies applied to solving epidemiologic, immunologic and evolutionary problems important for public health policy in influenza, dengue, polio, TB, and other infectious agents: RP1: Modeling, Spatial, Statistics (Lead: I. Longini, U. Florida);RP2: Dynamic Inference (Lead: P. Rohani, U Michigan);RP 3: Understanding transmission with integrated genetic and epidemiologic inference (Co-Leads: E. Kenah, U Florida and T. Bedford, FHCRC);RP 4: Dynamics and Evolution of Influenza Strain Variation (Lead: R. Antia, Emory U). The Software Development and Core Facilities (Lead: A. Vespignani, Northeastern U) will provide leadership in software development, access, and communication. The Policy Studies (Lead: J. Koopman, U Michigan) will provide leadership in communication of our research results to policy makers, as well as conducting novel research into policy making. The Training, Outreach, and Diversity Plans include ongoing training of 9 postdoctoral fellows and 5.25 predoctoral research assistants each year, support for participants in the Summer Institute for Statistics and Modeling in Infectious Diseases (UW) and ongoing Research Experience for Undergraduates programs at two institutions, among others. All participating institutions and the Center are committed to increasing diversity at all levels. Center-wide activities include Career Development Awards for junior faculty, annual workshops and symposia, outside speakers, and participation in the MIDAS Network meetings. Scientific leadership will be provided by the Center Director, a Leadership Committee, an external Scientific Advisory Board as well as the MIDAS Steering Committee.
This multi-institutional MIDAS Center of Excellence provides a multi-disciplinary approach to computational, statistical, and mathematical modeling of important infectious diseases. The research is motivated by multiscale problems such as immunologic, epidemiologic, and environmental drivers of the spread of infectious diseases with the goal of understanding and communicating the implications for public health policy.
|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