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Examination of Preferences for COVID-19 Vaccines in Hungary Based on Their Properties—Examining the Impact of Pandemic Awareness with a Hybrid Choice Approach

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  • Zsanett Blaga

    (University Pharmacy, Clinical Centre, University of Debrecen, H-4032 Debrecen, Hungary
    Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Peter Czine

    (Institute of Statistics and Methodology, University of Debrecen, H-4032 Debrecen, Hungary)

  • Barbara Takacs

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Anna Szilagyi

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Reka Szekeres

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Zita Wachal

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Csaba Hegedus

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Gyula Buchholcz

    (University Pharmacy, Clinical Centre, University of Debrecen, H-4032 Debrecen, Hungary)

  • Balazs Varga

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Daniel Priksz

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Mariann Bombicz

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Adrienn Monika Szabo

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Rita Kiss

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Rudolf Gesztelyi

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Dana Diana Romanescu

    (Department of Diabetology, Pelican Clinical Hospital, 410087 Oradea, Romania
    Department of Medical Disciplines, Faculty of Medicine and Pharmacy, University of Oradea, 410087 Oradea, Romania)

  • Zoltan Szabo

    (Department of Emergency Medicine, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Miklos Szucs

    (Department of Urology and Andrology, Clinical Centre, Kenezy Gyula Campus, University of Debrecen, H-4001 Debrecen, Hungary)

  • Peter Balogh

    (Institute of Statistics and Methodology, University of Debrecen, H-4032 Debrecen, Hungary)

  • Zoltan Szilvassy

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

  • Bela Juhasz

    (Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary)

Abstract

The COVID-19 pandemic has posed a huge challenge to the world in recent years. The development of vaccines that are as effective as possible and accessible to society offers a promising alternative for addressing the problems caused by this situation as soon as possible and to restore the pre-epidemic system. The present study investigated the preferences of residents in Hungary’s second-largest city (Debrecen) for the COVID-19 vaccine. To achieve this aim, a discrete choice experiment was conducted with 1011 participants, and the vaccine characteristics included in the design of the experiment were determined by qualitative methods and a pilot survey: (1) country of origin; (2) efficiency; (3) side effect; and (4) duration of protection. During the data collection at three vaccination sites, respondents were asked to choose between three vaccine alternatives and one “no choice” option in eight decision situations. Discrete choice model estimations were performed using a random parameter logit (RPL) specification with the final model extended to include a latent variable measuring pandemic awareness. The results showed that the vaccine with a Chinese country of origin is the least preferred among the respondents, while the Hungarian and the European vaccines are the most preferred. Furthermore, the increase in the vaccine efficiency level increased the respondents’ sense of utility for the vaccine; the short-term side effect was preferred to the long-term one; and the increase in the duration of protection provided by the vaccine increased the respondents’ sense of utility for the vaccine. Based on the parameter estimated for the latent variable, it can be concluded that as the level of pandemic awareness (which is more positive among people with chronic diseases and less important among health workers) increases, the choice of a vaccine option becomes more preferred among respondents compared to the “no choice“. The results of our investigation could contribute towards increasing compliance in the case of the vaccination-rejecting population, not only for COVID-19, but for any kind of vaccination procedure.

Suggested Citation

  • Zsanett Blaga & Peter Czine & Barbara Takacs & Anna Szilagyi & Reka Szekeres & Zita Wachal & Csaba Hegedus & Gyula Buchholcz & Balazs Varga & Daniel Priksz & Mariann Bombicz & Adrienn Monika Szabo & R, 2023. "Examination of Preferences for COVID-19 Vaccines in Hungary Based on Their Properties—Examining the Impact of Pandemic Awareness with a Hybrid Choice Approach," IJERPH, MDPI, vol. 20(2), pages 1-16, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:1270-:d:1031294
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    References listed on IDEAS

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    1. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    2. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    3. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    4. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth & Börsch-Supan, Axel, 2002. "Hybrid Choice Models: Progress and Challenges," Sonderforschungsbereich 504 Publications 02-29, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
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