Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Aug 2;11(8):e048025.
doi: 10.1136/bmjopen-2020-048025.

Correlates of intended COVID-19 vaccine acceptance across time and countries: results from a series of cross-sectional surveys

John R Kerr  1   2 , Claudia R Schneider  3   2 , Gabriel Recchia  3 , Sarah Dryhurst  3 , Ullrika Sahlin  4 , Carole Dufouil  5   6 , Pierre Arwidson  7 , Alexandra Lj Freeman  3 , Sander van der Linden  2
Affiliations

Correlates of intended COVID-19 vaccine acceptance across time and countries: results from a series of cross-sectional surveys

John R Kerr et al. BMJ Open. .

Abstract

Objective: Describe demographical, social and psychological correlates of willingness to receive a COVID-19 vaccine.

Setting: Series of online surveys undertaken between March and October 2020.

Participants: A total of 25 separate national samples (matched to country population by age and sex) in 12 different countries were recruited through online panel providers (n=25 334).

Primary outcome measures: Reported willingness to receive a COVID-19 vaccination.

Results: Reported willingness to receive a vaccine varied widely across samples, ranging from 63% to 88%. Multivariate logistic regression analyses reveal sex (female OR=0.59, 95% CI 0.55 to 0.64), trust in medical and scientific experts (OR=1.28, 95% CI 1.22 to 1.34) and worry about the COVID-19 virus (OR=1.47, 95% CI 1.41 to 1.53) as the strongest correlates of stated vaccine acceptance considering pooled data and the most consistent correlates across countries. In a subset of UK samples, we show that these effects are robust after controlling for attitudes towards vaccination in general.

Conclusions: Our results indicate that the burden of trust largely rests on the shoulders of the scientific and medical community, with implications for how future COVID-19 vaccination information should be communicated to maximise uptake.

Keywords: COVID-19; preventive medicine; public health.

PubMed Disclaimer

Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
COVID-19 vaccine acceptance across countries and time. Percentage of respondents who stated they were willing to receive or recommend a COVID-19 vaccine across surveys. UK and US samples using different panel providers are reported separately.
Figure 2
Figure 2
Correlates of vaccine acceptance. Heat map of ORs in multivariate logistic regression model predicting stated vaccine acceptance. Columns represent individual samples, and rows represent independent variables in model. Grey values are non-significant (p>0.05). Red shading indicates a lower likelihood of reported vaccine acceptance and blue shading a higher likelihood. For space, samples are defined by their two-character ISO country code and a letter denoting participant source (B, BVA; D, Dynata; P, Prolific; and R, Respondi). Political orientation data were not collected in the French sample; this sample is excluded from pooled data.
Figure 3
Figure 3
Political ideology and vaccine acceptance in the UK. Predicted likelihood that an individual will accept being vaccinated at varying levels of political ideology (1=very liberal/left wing and 7=very conservative/right wing) in UK samples over time.
Figure 4
Figure 4
Negative general attitudes towards vaccination do not fully account for relationships in the model. Results of multivariate logistic regression models investigating reported COVID-19 vaccine acceptance in UK samples, excluding (left panel) or including (right panel) general vaccine attitudes as an independent variable. ORs shown are based on scaled variables (other than gender). Grey values are non-significant (p>0.05). For space, samples are defined by a letter denoting participant source (P, Prolific; R, Respondi).
See this image and copyright information in PMC

References

    1. Porterfield C. Global coronavirus death Toll tops 2.5 million — though new fatalities have dropped. Forbes, 2021. Available: https://www.forbes.com/sites/carlieporterfield/2021/02/25/global-coronav... [Accessed 3 Mar 2021].
    1. International Monetary Fund . World economic outlook, October 2020: a long and difficult ascent. Washington, DC, 2020. Available: https://www.imf.org/en/Publications/WEO/Issues/2020/09/30/world-economic... [Accessed 29 Nov 2020].
    1. Lytras T, Tsiodras S. Lockdowns and the COVID-19 pandemic: what is the endgame? Scand J Public Health 2021;49:37–40. 10.1177/1403494820961293 - DOI - PMC - PubMed
    1. Schoch-Spana M, Brunson EK, Long R, et al. The public's role in COVID-19 vaccination: Human-centered recommendations to enhance pandemic vaccine awareness, access, and acceptance in the United States. Vaccine 2020. 10.1016/j.vaccine.2020.10.059. [Epub ahead of print: 29 Oct 2020]. - DOI - PMC - PubMed
    1. Callaway E. What Pfizer’s landmark COVID vaccine results mean for the pandemic. Nature 2020. 10.1038/d41586-020-03166-8. [Epub ahead of print: 9 Nov 2020]. - DOI - PubMed

Publication types

Substances