US influenza vaccination policy is problematic. First, influenza vaccine effectiveness is low (e.g., 27%) in the elderly, the group most likely to die. Second, interference between successive doses has recently been described. Third, there are many vaccine formulations, with differing valences, efficacies, administration routes, and allowable ages of use, complicating policy recommendations. Fourth, the tension between the timing of vaccination, annual epidemics, and duration of immunity is clear: if waning immunity occurs with early vaccination and a late epidemic occurs, protection may be reduced whereas an early epidemic may occur before vaccination is completed. To address these challenges, we will use complimentary computational modeling techniques: Markov cohort decision analysis (DA), equation-based dynamic transmission modeling (EBM), and agent-based modeling (ABM). DA provides a clear visual framework for the breadth of strategies under consideration and is relatively quicker for initial analyses. EBM adds to this the dynamics of disease transmission and indirect (herd immunity) effects of vaccination strategies. ABM, conducted on supercomputers, adds further detail through simulating autonomous persons and their spatial and temporal demographics and social interactions during disease spread through a population. Because ABM is computationally intensive, strategies considered by ABM will be narrowed using DA and EBM. Using all three modeling techniques offers a balance of clarity and the complexity of reality, as well as the opportunity to perform validity comparisons between techniques.
Aim 1 : Determine the optimal vaccine selection strategy that minimizes disease burden and resource use in various age groups in 1) the US population and 2) various medical practice populations.
Aim 2 : Determine the ideal timing of annual vaccination, weighing the potential impact of early vaccination, waning immunity, and epidemic timing, interference, and missed vaccination opportunities..
Aim 3 : Using ABM, compare the trade-offs of effectiveness, duration, herd immunity, side effects, achievable vaccination rates, and cost of inactivated vaccines to those of potential universal vaccines in different US locations/populations and determine universal vaccine characteristics that favor its adoption. The research team is experienced in modeling, possesses diverse skill sets, has worked together, has access to epidemiologic data in the Influenza Vaccine Effectiveness Network, and has a strong publication record in vaccination issues, encompassing modeling, cost- effectiveness analysis, and policy.

Public Health Relevance

Flu vaccine policy for the nation must account for the dynamic nature of flu and the growing number of flu vaccine choices. We will use multiple mathematical modeling methods, including use of a supercomputer, to make better flu vaccine policy choices.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
3R01GM111121-03S1
Application #
9164412
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Ravichandran, Veerasamy
Project Start
2014-08-01
Project End
2018-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
3
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of Pittsburgh
Department
Family Medicine
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Tajgardoon, Mohammadamin; Wagner, Michael M; Visweswara, Shyam et al. (2018) A Novel Representation of Vaccine Efficacy Trial Datasets for Use in Computer Simulation of Vaccination Policy. AMIA Jt Summits Transl Sci Proc 2017:389-398
Shim, Eunha; Smith, Kenneth J; Nowalk, Mary Patricia et al. (2018) Impact of seasonal influenza vaccination in the presence of vaccine interference. Vaccine 36:853-858
DePasse, Jay V; Smith, Kenneth J; Raviotta, Jonathan M et al. (2017) Does Choice of Influenza Vaccine Type Change Disease Burden and Cost-Effectiveness in the United States? An Agent-Based Modeling Study. Am J Epidemiol 185:822-831
Raviotta, Jonathan M; Smith, Kenneth J; DePasse, Jay et al. (2017) Reply to: Estimating the Full Value of High-Dose Influenza Vaccine. J Am Geriatr Soc 65:2111-2112
Smith, Kenneth J; Nowalk, Mary Patricia; Wateska, Angela et al. (2017) Potential Consequences of Not Using Live Attenuated Influenza Vaccine. Am J Prev Med 53:500-503
DePasse, Jay V; Nowalk, Mary Patricia; Smith, Kenneth J et al. (2017) Does cost-effectiveness of influenza vaccine choice vary across the U.S.? An agent-based modeling study. Vaccine 35:3974-3981
Raviotta, Jonathan M; Smith, Kenneth J; DePasse, Jay et al. (2017) Cost-effectiveness and public health impact of alternative influenza vaccination strategies in high-risk adults. Vaccine 35:5708-5713
Smith, Kenneth J; Raviotta, Jonathan M; DePasse, Jay V et al. (2016) Cost Effectiveness of Influenza Vaccine Choices in Children Aged 2-8 Years in the U.S. Am J Prev Med 50:600-608
Shim, Eunha; Brown, Shawn T; DePasse, Jay et al. (2016) Cost Effectiveness of Influenza Vaccine for U.S. Children: Live Attenuated and Inactivated Influenza Vaccine. Am J Prev Med 51:309-17
Raviotta, Jonathan M; Smith, Kenneth J; DePasse, Jay et al. (2016) Cost-Effectiveness and Public Health Effect of Influenza Vaccine Strategies for U.S. Elderly Adults. J Am Geriatr Soc 64:2126-2131