A key to predicting medical decisions, such as vaccinations, is to understand individual behavior and its determinants, including self-interest and self-determined goals (desire to benefit oneself or enhance one's utility), prosociality (preferences for the well-being of others), imitation (imitating decisions of others), habitual behavior (tendency to repeat past actions), as well as time and budget constraints. As these behavioral factors influence vaccination decisions, they need to be incorporated into models of alternative vaccination strategies in order to provide policy decision-making guidance. Here, we propose to evaluate how behavioral factors shape influenza vaccination decisions, vary across nations, and can be used to inform vaccination strategies. To do so, we will use epidemiological-economic models including game theory and network models of influenza transmission, parameterized by psychological, economic and sociological data. Specifically, our transdisciplinary team will employ surveys, statistical analysis, and mathematical modeling to assess the interplay among decision-making processes of individuals, infectious disease transmission, and social influences in different countries. We will evaluate behavior, decision-making and epidemiological outcomes at multiple interrelated scales, including at the individual, household, age class, national, and population levels. Individual-level vaccination decisions can profoundly influence the fate of outbreaks, and thus have far reaching public health consequences for regional, national, and international populations. Understanding the factors underlying vaccination decisions and adherence to public health recommendations will enable the design of more effective vaccination programs. Therefore, we will also evaluate the capacity to influence behavioral factors, including prosociality, imitation, and habitual behavior, to promote vaccination policies that are optimal at both the individual and public health scales. Our results will increase our understanding of health decision-making and inform intervention strategies to improve vaccination rates.

Public Health Relevance

We propose to evaluate how behavioral factors shape influenza vaccination decisions. Using epidemiological game theory models of influenza parameterized by analysis of novel psychological data, we will evaluate behavior, decision-making, and epidemiological outcomes at multiple interrelated scales, including the individual, age class, population and international levels. Our findings will improve our understanding of health decision- making and enable us to inform vaccination strategies in order to improve public health outcomes.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01GM105627-01
Application #
8477594
Study Section
Special Emphasis Panel (ZEB1-OSR-C (J2))
Program Officer
Marcus, Stephen
Project Start
2013-07-10
Project End
2018-03-31
Budget Start
2013-07-10
Budget End
2014-03-31
Support Year
1
Fiscal Year
2013
Total Cost
$338,540
Indirect Cost
$112,369
Name
Yale University
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
Medley, Graham F; Blok, David J; Crump, Ronald E et al. (2018) Policy Lessons From Quantitative Modeling of Leprosy. Clin Infect Dis 66:S281-S285
Rock, Kat S; Ndeffo-Mbah, Martial L; CastaƱo, Soledad et al. (2018) Assessing Strategies Against Gambiense Sleeping Sickness Through Mathematical Modeling. Clin Infect Dis 66:S286-S292
Sah, Pratha; Medlock, Jan; Fitzpatrick, Meagan C et al. (2018) Optimizing the impact of low-efficacy influenza vaccines. Proc Natl Acad Sci U S A 115:5151-5156
Durham, David P; Fitzpatrick, Meagan C; Ndeffo-Mbah, Martial L et al. (2018) Evaluating Vaccination Strategies for Zika Virus in the Americas. Ann Intern Med 168:621-630
Marshall, Brandon D L; Goedel, William C; King, Maximilian R F et al. (2018) Potential effectiveness of long-acting injectable pre-exposure prophylaxis for HIV prevention in men who have sex with men: a modelling study. Lancet HIV 5:e498-e505
Grantz, Kyra H; Chabaari, Winnie; Samuel, Ramolotja Kagiso et al. (2018) Spatial distribution of leprosy in India: an ecological study. Infect Dis Poverty 7:20
Fitzpatrick, Meagan C; Gray, Glenda E; Galvani, Alison P (2018) The Challenge of Vanquishing HIV for the Next Generation-Facing the Future. JAMA Pediatr 172:609-610
Ndeffo-Mbah, Martial L; Vigliotti, Vivian S; Skrip, Laura A et al. (2018) Dynamic Models of Infectious Disease Transmission in Prisons and the General Population. Epidemiol Rev 40:40-57
Lee, Bruce Y; Bartsch, Sarah M; Skrip, Laura et al. (2018) Are the London Declaration's 2020 goals sufficient to control Chagas disease?: Modeling scenarios for the Yucatan Peninsula. PLoS Negl Trop Dis 12:e0006337
Skrip, Laura A; Fallah, Mosoka P; Gaffney, Stephen G et al. (2017) Characterizing risk of Ebola transmission based on frequency and type of case-contact exposures. Philos Trans R Soc Lond B Biol Sci 372:

Showing the most recent 10 out of 41 publications