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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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    1. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
    2. Chris T Bauch & Samit Bhattacharyya, 2012. "Evolutionary Game Theory and Social Learning Can Determine How Vaccine Scares Unfold," PLOS Computational Biology, Public Library of Science, vol. 8(4), pages 1-12, April.
    3. Chris T Bauch & Samit Bhattacharyya & Robert F Ball, 2010. "Rapid Emergence of Free-Riding Behavior in New Pediatric Immunization Programs," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-9, September.
    4. Esther W. de Bekker‐Grob & Mandy Ryan & Karen Gerard, 2012. "Discrete choice experiments in health economics: a review of the literature," Health Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 145-172, February.
    5. Jeffrey T. Vietri & Meng Li & Alison P. Galvani & Gretchen B. Chapman, 2012. "Vaccinating to Help Ourselves and Others," Medical Decision Making, , vol. 32(3), pages 447-458, May.
    6. Goyal, Sanjeev & Vigier, Adrien, 2015. "Interaction, protection and epidemics," Journal of Public Economics, Elsevier, vol. 125(C), pages 64-69.
    7. Michael Clark & Domino Determann & Stavros Petrou & Domenico Moro & Esther Bekker-Grob, 2014. "Discrete Choice Experiments in Health Economics: A Review of the Literature," PharmacoEconomics, Springer, vol. 32(9), pages 883-902, September.
    8. Jorge E. Araña & Carmelo J. León, 2002. "Willingness to pay for health risk reduction in the context of altruism," Health Economics, John Wiley & Sons, Ltd., vol. 11(7), pages 623-635, October.
    9. Bliemer, Michiel C.J. & Rose, John M., 2010. "Construction of experimental designs for mixed logit models allowing for correlation across choice observations," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 720-734, July.
    10. Mandy Ryan & Karen Gerard & Gillian Currie, 2012. "Using Discrete Choice Experiments in Health Economics," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 41, Edward Elgar Publishing.
    11. John Rose & Michiel Bliemer, 2013. "Sample size requirements for stated choice experiments," Transportation, Springer, vol. 40(5), pages 1021-1041, September.
    12. Zhang, Yan, 2013. "The impact of other-regarding tendencies on the spatial vaccination game," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 209-215.
    13. Schimit, P.H.T. & Monteiro, L.H.A., 2011. "A vaccination game based on public health actions and personal decisions," Ecological Modelling, Elsevier, vol. 222(9), pages 1651-1655.
    14. Roselinde Kessels & Bradley Jones & Peter Goos, 2015. "An improved two‐stage variance balance approach for constructing partial profile designs for discrete choice experiments," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(5), pages 626-648, September.
    15. Jane Hall & Patricia Kenny & Madeleine King & Jordan Louviere & Rosalie Viney & Angela Yeoh, 2002. "Using stated preference discrete choice modelling to evaluate the introduction of varicella vaccination," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 457-465, July.
    16. Roselinde Kessels & Bradley Jones & Peter Goos & Martina Vandebroek, 2011. "The usefulness of Bayesian optimal designs for discrete choice experiments," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(3), pages 173-188, May.
    17. Skea, Zoë C. & Entwistle, Vikki A. & Watt, Ian & Russell, Elizabeth, 2008. "'Avoiding harm to others' considerations in relation to parental measles, mumps and rubella (MMR) vaccination discussions - An analysis of an online chat forum," Social Science & Medicine, Elsevier, vol. 67(9), pages 1382-1390, November.
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    2. 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).
    3. Meyerhoff, Jürgen & Oehlmann, Malte, 2023. "The performance of full versus partial profile choice set designs in environmental valuation," Ecological Economics, Elsevier, vol. 204(PA).
    4. 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.
    5. Soya Miyoshi & Marko Jusup & Petter Holme, 2021. "Flexible imitation suppresses epidemics through better vaccination," Journal of Computational Social Science, Springer, vol. 4(2), pages 709-720, November.
    6. 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.
    7. Mühlhoff, Katharina, 2022. "Convincing the “Herd” of immunity: Lessons from smallpox vaccination in 19th century Germany," Economics & Human Biology, Elsevier, vol. 47(C).
    8. 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.

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