Author:
Caserotti Marta,Girardi Paolo,Tasso Alessandra,Rubaltelli Enrico,Lotto Lorella,Gavaruzzi Teresa
Abstract
AbstractPharmacological and non-pharmacological measures will overlap for a period after the onset of the pandemic, playing a strong role in virus containment. We explored which factors influence the likelihood to adopt two different preventive measures against the COVID-19 pandemic. An online snowball sampling (May–June 2020) collected a total of 448 questionnaires in Italy. A Bayesian bivariate Gaussian regression model jointly investigated the willingness to get vaccinated against COVID-19 and to download the national contact tracing app. A mixed-effects cumulative logistic model explored which factors affected the motivation to adopt one of the two preventive measures. Despite both COVID-19 vaccines and tracing apps being indispensable tools to contain the spread of SARS-CoV-2, our results suggest that adherence to the vaccine or to the national contact tracing app is not predicted by the same factors. Therefore, public communication on these measures needs to take in consideration not only the perceived risk associated with COVID-19, but also the trust people place in politics and science, their concerns and doubts about vaccinations, and their employment status. Further, the results suggest that the motivation to comply with these measurements was predominantly to protect others rather than self-protection.
Publisher
Springer Science and Business Media LLC
Reference56 articles.
1. Almagor, J. & Picascia, S. Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model. Sci. Rep. 10, 22235. https://doi.org/10.1038/s41598-020-79000-y (2020).
2. European Centre for Disease Prevention and Control. Risk Assessment: Risk Related to the Spread of New SARS-CoV-2 Variants of Concern in the EU/EEA—First Update (European Centre for Disease Prevention and Control, 2021).
3. Ministero della Salute. Vaccini Anti COVID-19 (Ministero della Salute, 2021).
4. Randolph, H. E. & Barreiro, L. B. Herd immunity: Understanding COVID-19. Immunity 52, 737–741 (2020).
5. Perkins, T. A. & España, G. Optimal control of the COVID-19 pandemic with non-pharmaceutical interventions. Bull. Math. Biol. 82, 1–24 (2020).
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