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Understanding hesitancy with revealed preferences across COVID-19 vaccine types

Author

Listed:
  • Kutasi Kristóf

    (Rice University, Department of Economics, Houston TX, 77005-1827, USA)

  • Koltai Júlia

    (Centre for Social Sciences, Computational Social Science - Research Center for Educational and Network Studies, Budapest, 1097, HungaryEötvös Loránd University, Faculty of Social Sciences, Budapest, 1117, Hungary Central European University, Department of Network and Data Science, Vienna, 1100, Austria)

  • Szabó-Morvai Ágnes

    (Eötvös Loránd Research Network, Centre for Economic and Regional Studies, Health and Population Lendület Research Group, Budapest, 1097, Hungary Debrecen University, Department of Economics, Debrecen, 4032, Hungary)

  • Röst Gergely

    (University of Szeged, Bolyai Institute, Szeged, 6722, Hungary)

  • Karsai Márton

    (Central European University, Department of Network and Data Science, Vienna, 1100, Austria Alfréd Rényi Institute of Mathematics, Budapest, 1053, Hungary)

  • Biró Péter

    (Eötvös Loránd Research Network, Centre for Economic and Regional Studies, Mechanism Design Lendület Research Group, Budapest, 1097, Hungary Corvinus University of Budapest, Department of Operations Research and Actuarial Sciences, Budapest, 1093, Hungary)

  • Lengyel Balázs

    (Eötvös Loránd Research Network, Centre for Economic and Regional Studies, Agglomeration and Social Networks Lendület Research Group, Budapest, 1097, HungaryCorvinus University of Budapest, Corvinus Institute for Advanced Studies, Budapest,)

Abstract

Many countries have secured larger quantities of COVID-19 vaccines than their populace is willing to take. This abundance and variety of vaccines created a historical moment to understand vaccine hesitancy better. Never before were more types of vaccines available for an illness and the intensity of vaccine-related public discourse is unprecedented. Yet, the heterogeneity of hesitancy by vaccine types in certain segments of society has been neglected so far, even though factual or believed vaccine characteristics and patient attributes are known to influence acceptance. In this paper, we address this problem by analysing acceptance and assessment of five vaccine types using information collected with a nationally representative survey (N=1000) at the end of the third wave of the COVID-19 pandemic in Hungary, where a unique portfolio of vaccines were available to the public in large quantities. Our special case enables us to quantify revealed preferences across vaccine types since one could evaluate a vaccine unacceptable and even could reject an assigned vaccine to wait for another type. We find that the source of information that respondents trust characterizes their attitudes towards vaccine types differently and leads to divergent vaccine hesitancy. Believers of conspiracy theories were significantly more likely to evaluate the mRNA vaccines (Pfizer and Moderna) unacceptable while those who follow the advice of politicians evaluate vector-based (AstraZeneca and Sputnik) or whole-virus vaccines (Sinopharm) acceptable with higher likelihood. We illustrate that the rejection of non-desired and re-selection of preferred vaccines fragments the population by the mRNA versus other type of vaccines while it generally improves the assessment of the received vaccine. These results highlight that greater variance of available vaccine types and individual free choice are desirable conditions that can widen the acceptance of vaccines in societies.

Suggested Citation

  • Kutasi Kristóf & Koltai Júlia & Szabó-Morvai Ágnes & Röst Gergely & Karsai Márton & Biró Péter & Lengyel Balázs, 2022. "Understanding hesitancy with revealed preferences across COVID-19 vaccine types," KRTK-KTI WORKING PAPERS 2207, Institute of Economics, Centre for Economic and Regional Studies.
    • Handle: RePEc:has:discpr:2207
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    References listed on IDEAS

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    1. Heidi Ledford, 2021. "How could a COVID vaccine cause blood clots? Scientists race to investigate," Nature, Nature, vol. 592(7854), pages 334-335, April.
    2. Sahil Loomba & Alexandre Figueiredo & Simon J. Piatek & Kristen Graaf & Heidi J. Larson, 2021. "Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA," Nature Human Behaviour, Nature, vol. 5(3), pages 337-348, March.
    3. Jamie Murphy & Frédérique Vallières & Richard P. Bentall & Mark Shevlin & Orla McBride & Todd K. Hartman & Ryan McKay & Kate Bennett & Liam Mason & Jilly Gibson-Miller & Liat Levita & Anton P. Martine, 2021. "Psychological characteristics associated with COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
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    Cited by:

    1. Stefkovics, Ádám & Krekó, Péter & Koltai, Júlia, 2024. "When reality knocks on the door. The effect of conspiracy beliefs on COVID-19 vaccine acceptance and the moderating role of experience with the virus," Social Science & Medicine, Elsevier, vol. 356(C).
    2. Péter Biró & Sándor Bozóki & Tamás Király & Alexandru Kristály, 2024. "Optimization methods and algorithms," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 32(1), pages 1-9, March.

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    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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