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Covid-19 Endemism and the Control Skeptics


  • Jacques Bughin
  • Michele Cincera
  • Dorota Reykowska
  • Marcin Zyszkiewicz
  • Rafal Ohme


This paper analyses the widespread difference in Covid-19 vaccination and Non-Pharmaceutical interventions (NPI) acceptance by the European population and finds that this difference can be clustered in nine archetype clusters. Calibrating a SIR model with control acceptance on Covid-19 pandemics, it is also estimated that three anti-control segments (standing in aggregate for 15% of the population) may be contributing to the entire bulk of the endemism of the Covid-19. While poorly compliant segments have lower risk perception than others, tend to be younger, and less educated, or are more self-centric, trust with respect to media, governmental, and healthcare institutions are significantly shaping control acceptance by the population. In particular, the way to overturn a large set of vaccination “hesitant” (20% of the population), must pass by rebuilding much higher trust in how the current crisis is managed by the government and healthcare system

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  • Jacques Bughin & Michele Cincera & Dorota Reykowska & Marcin Zyszkiewicz & Rafal Ohme, 2021. "Covid-19 Endemism and the Control Skeptics," Working Papers TIMES² 2021-044, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:ict:wpaper:2013/320304

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    References listed on IDEAS

    1. Sarah Dryhurst & Claudia R. Schneider & John Kerr & Alexandra L. J. Freeman & Gabriel Recchia & Anne Marthe van der Bles & David Spiegelhalter & Sander van der Linden, 2020. "Risk perceptions of COVID-19 around the world," Journal of Risk Research, Taylor & Francis Journals, vol. 23(7-8), pages 994-1006, August.
    2. Sebastian Neumann-Böhme & Nirosha Elsem Varghese & Iryna Sabat & Pedro Pita Barros & Werner Brouwer & Job Exel & Jonas Schreyögg & Tom Stargardt, 2020. "Once we have it, will we use it? A European survey on willingness to be vaccinated against COVID-19," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(7), pages 977-982, September.
    3. Coibion, Olivier & Gorodnichenko, Yuriy & Weber, Michael, 2020. "The Cost of the COVID-19 Crisis: Lockdowns, Macroeconomic Expectations, and Consumer Spending," Department of Economics, Working Paper Series qt4jn1x65h, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    4. Debanjan Banerjee & Mayank Rai, 2020. "Social isolation in Covid-19: The impact of loneliness," International Journal of Social Psychiatry, , vol. 66(6), pages 525-527, September.
    5. Paul T E Cusack, 2020. "Anxiety Disorders," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 31(3), pages 24255-24260, October.
    6. Nicholas W. Papageorge & Matthew V. Zahn & Michèle Belot & Eline Broek-Altenburg & Syngjoo Choi & Julian C. Jamison & Egon Tripodi, 2021. "Socio-demographic factors associated with self-protecting behavior during the Covid-19 pandemic," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(2), pages 691-738, April.
    7. Esping-Andersen, Gosta, 1999. "Social Foundations of Postindustrial Economies," OUP Catalogue, Oxford University Press, number 9780198742005, Decembrie.
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    RePEc Biblio mentions

    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Behavioral issues > Trust


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    Cited by:

    1. Jacques Bughin & Michele Cincera & Dorota Reykowska & Rafal Ohme, 2021. "Big Data is Decision Science: the Case of Covid-19 Vaccination," Working Papers TIMES² 2021-047, ULB -- Universite Libre de Bruxelles.

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    More about this item


    Covid-19; Pandemic Endemism; vaccine strategy; Non-Pharmaceutical Interventions; SIR;
    All these keywords.

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