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Individual decisions to vaccinate one's child or oneself: A discrete choice experiment rejecting free-riding motives

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  • Verelst, Frederik
  • Willem, Lander
  • Kessels, Roselinde
  • Beutels, Philippe

Abstract

It is essential for public health to understand what drives people's hesitance towards vaccination. Theoretical models of vaccination decisions are ubiquitous, often incorporating herd immunity, perceptions of vaccine-related side-effects (VRSE) and of vaccine-preventable burden of disease, but with little to no empirical exploration. Herd immunity is a (usually) positive externality where vaccinated individuals influence others' risks by their reduced capability to transmit an infectious disease to them. It is often assumed that (rational) individuals incorporate this externality in their strategic vaccination decision, from which free-riding behavior arises. We performed a Bayesian D-efficient discrete choice experiment in February–March 2017 to study vaccination behavior in 1919 Belgian respondents. Choice sets with vaccine profiles were constructed using six attributes: vaccine effectiveness, VRSE, accessibility (in terms of convenience and reimbursement), vaccine-preventable burden of disease, local (respondents' network of contacts) vaccination coverage, and population (the population at large) vaccination coverage. VRSE and accessibility are the most influential attributes, followed by vaccine effectiveness and burden of disease. Both population and local coverage are less important than the other attributes, but show a significant direct linear relationship with vaccine utility. This supports the existence of peer influence (more incentivized as more and more vaccinate), rather than free-riding on herd immunity. These findings were independent of whether respondents made vaccine choices for themselves or for their child. Around 40% of the respondents indicated accepting vaccination with little or no questioning. These ‘acceptors’ were less sensitive to changes in the vaccine-preventable burden of disease for their child's vaccination choices (but not for themselves). Public health institutions are critical in stimulating vaccine uptake by making vaccines conveniently available at an affordable price and by communicating pro-actively on perceived VRSEs. The free-riding assumption as a driver of individual vaccine decisions, seems inappropriate, but this observation needs confirming in other populations.

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  • Verelst, Frederik & Willem, Lander & Kessels, Roselinde & Beutels, Philippe, 2018. "Individual decisions to vaccinate one's child or oneself: A discrete choice experiment rejecting free-riding motives," Social Science & Medicine, Elsevier, vol. 207(C), pages 106-116.
    • Handle: RePEc:eee:socmed:v:207:y:2018:i:c:p:106-116
    DOI: 10.1016/j.socscimed.2018.04.038
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    3. Anupama Sharma & Shakti N Menon & V Sasidevan & Sitabhra Sinha, 2019. "Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes," PLOS Computational Biology, Public Library of Science, vol. 15(5), pages 1-18, May.
    4. Mühlhoff, Katharina, 2022. "Convincing the “Herd” of immunity: Lessons from smallpox vaccination in 19th century Germany," Economics & Human Biology, Elsevier, vol. 47(C).
    5. Jingrong Zhu & Jinlin Li & Zengbo Zhang & Hao Li, 2019. "Patients' choice and preference for common disease diagnosis and diabetes care: A discrete choice experiment," International Journal of Health Planning and Management, Wiley Blackwell, vol. 34(4), pages 1544-1555, October.
    6. Blondel, Serge & Langot, François & Mueller, Judith E. & Sicsic, Jonathan, 2021. "Preferences and COVID-19 Vaccination Intentions," IZA Discussion Papers 14823, Institute of Labor Economics (IZA).
    7. Meyerhoff, Jürgen & Oehlmann, Malte, 2023. "The performance of full versus partial profile choice set designs in environmental valuation," Ecological Economics, Elsevier, vol. 204(PA).
    8. Thao Thai & Michiel Bliemer & Gang Chen & Jean Spinks & Sonja de New & Emily Lancsar, 2023. "Comparison of a full and partial choice set design in a labeled discrete choice experiment," Health Economics, John Wiley & Sons, Ltd., vol. 32(6), pages 1284-1304, June.

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