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Vaccine Hesitancy and Political Populism. An Invariant Cross-European Perspective

Author

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  • Almudena Recio-Román

    (Department of Economics and Business, University of Almería, Carretera de Sacramento s/n, 04120 Almería, Spain)

  • Manuel Recio-Menéndez

    (Department of Economics and Business, University of Almería, Carretera de Sacramento s/n, 04120 Almería, Spain)

  • María Victoría Román-González

    (Department of Economics and Business, University of Almería, Carretera de Sacramento s/n, 04120 Almería, Spain)

Abstract

Vaccine-hesitancy and political populism are positively associated across Europe: those countries in which their citizens present higher populist attitudes are those that also have higher vaccine-hesitancy rates. The same key driver fuels them: distrust in institutions, elites, and experts. The reluctance of citizens to be vaccinated fits perfectly in populist political agendas because is a source of instability that has a distinctive characteristic known as the “small pockets” issue. It means that the level at which immunization coverage needs to be maintained to be effective is so high that a small number of vaccine-hesitants have enormous adverse effects on herd immunity and epidemic spread. In pandemic and post-pandemic scenarios, vaccine-hesitancy could be used by populists as one of the most effective tools for generating distrust. This research presents an invariant measurement model applied to 27 EU + UK countries (27,524 participants) that segments the different behaviours found, and gives social-marketing recommendations for coping with the vaccine-hesitancy problem when used for generating distrust.

Suggested Citation

  • Almudena Recio-Román & Manuel Recio-Menéndez & María Victoría Román-González, 2021. "Vaccine Hesitancy and Political Populism. An Invariant Cross-European Perspective," IJERPH, MDPI, vol. 18(24), pages 1-20, December.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:24:p:12953-:d:697993
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    References listed on IDEAS

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    1. Jeff French & Sameer Deshpande & William Evans & Rafael Obregon, 2020. "Key Guidelines in Developing a Pre-Emptive COVID-19 Vaccination Uptake Promotion Strategy," IJERPH, MDPI, vol. 17(16), pages 1-14, August.
    2. Brock, Guy & Pihur, Vasyl & Datta, Susmita & Datta, Somnath, 2008. "clValid: An R Package for Cluster Validation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i04).
    3. Yaqub, Ohid & Castle-Clarke, Sophie & Sevdalis, Nick & Chataway, Joanna, 2014. "Attitudes to vaccination: A critical review," Social Science & Medicine, Elsevier, vol. 112(C), pages 1-11.
    4. Robert Jennrich, 2006. "Rotation to Simple Loadings Using Component Loss Functions: The Oblique Case," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 173-191, March.
    5. Helmut Herwartz & Bernd Theilen, 2014. "Health Care And Ideology: A Reconsideration Of Political Determinants Of Public Healthcare Funding In The Oecd," Health Economics, John Wiley & Sons, Ltd., vol. 23(2), pages 225-240, February.
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