Global survey on COVID-19 beliefs, behaviours and norms

Avinash Collis^#¹, Kiran Garimella^#², Alex Moehring^#^{3

4}, M Amin Rahimian^#⁵, Stella Babalola^{6

7}, Nina H Gobat⁸, Dominick Shattuck⁶, Jeni Stolow⁹, Sinan Aral^{10

11

12}, Dean Eckles^{13

14

15}

Affiliations

¹ McCombs School of Business, The University of Texas at Austin, Austin, TX, USA.
² School of Communication and Information, Rutgers University, New Brunswick, NJ, USA.
³ Initiative on the Digital Economy, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁴ Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁵ Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
⁶ Center for Communications Programming, Johns Hopkins University, Baltimore, MD, USA.
⁷ Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
⁸ Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
⁹ Global Outbreak Alert and Response Network, Geneva, Switzerland.
¹⁰ Initiative on the Digital Economy, Massachusetts Institute of Technology, Cambridge, MA, USA. sinan@mit.edu.
¹¹ Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA. sinan@mit.edu.
¹² Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA. sinan@mit.edu.
¹³ Initiative on the Digital Economy, Massachusetts Institute of Technology, Cambridge, MA, USA. eckles@mit.edu.
¹⁴ Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA. eckles@mit.edu.
¹⁵ Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA. eckles@mit.edu.

^# Contributed equally.

PMID: 35606513
DOI: 10.1038/s41562-022-01347-1

Global survey on COVID-19 beliefs, behaviours and norms

Avinash Collis et al. Nat Hum Behav. 2022 Sep.

. 2022 Sep;6(9):1310-1317.

doi: 10.1038/s41562-022-01347-1. Epub 2022 May 23.

Authors

Affiliations

¹ McCombs School of Business, The University of Texas at Austin, Austin, TX, USA.
² School of Communication and Information, Rutgers University, New Brunswick, NJ, USA.
³ Initiative on the Digital Economy, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁴ Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁵ Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
⁶ Center for Communications Programming, Johns Hopkins University, Baltimore, MD, USA.
⁷ Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
⁸ Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
⁹ Global Outbreak Alert and Response Network, Geneva, Switzerland.
¹⁰ Initiative on the Digital Economy, Massachusetts Institute of Technology, Cambridge, MA, USA. sinan@mit.edu.
¹¹ Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA. sinan@mit.edu.
¹² Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA. sinan@mit.edu.
¹³ Initiative on the Digital Economy, Massachusetts Institute of Technology, Cambridge, MA, USA. eckles@mit.edu.
¹⁴ Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA. eckles@mit.edu.
¹⁵ Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA. eckles@mit.edu.

^# Contributed equally.

PMID: 35606513
DOI: 10.1038/s41562-022-01347-1

Abstract

Policy and communication responses to COVID-19 can benefit from better understanding of people's baseline and resulting beliefs, behaviours and norms. From July 2020 to March 2021, we fielded a global survey on these topics in 67 countries yielding over 2 million responses. This paper provides an overview of the motivation behind the survey design, details the sampling and weighting designed to make the results representative of populations of interest and presents some insights learned from the survey. Several studies have already used the survey data to analyse risk perception, attitudes towards mask wearing and other preventive behaviours, as well as trust in information sources across communities worldwide. This resource can open new areas of enquiry in public health, communication and economic policy by leveraging large-scale, rich survey datasets on beliefs, behaviours and norms during a global pandemic.

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References

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1. West, R., Michie, S., Rubin, G. J. & Amlôt, R. Applying principles of behaviour change to reduce SARS-CoV-2 transmission. Nat. Hum. Behav. 4, 451–459 (2020). - DOI
1. Van Bavel, J. J. et al. Using social and behavioural science to support COVID-19 pandemic response. Nat. Hum. Behav. 4, 460–471 (2020). - DOI
1. Allcott, H. et al. Polarization and public health: partisan differences in social distancing during the coronavirus pandemic. J. Public Econ. 191, 104254 (2020). - DOI
1. Bursztyn, L., Rao, A., Roth, C. P. & Yanagizawa-Drott, D. H. Misinformation During a Pandemic No. w27417 (National Bureau of Economic Research, 2020).

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Global survey on COVID-19 beliefs, behaviours and norms

Affiliations

Global survey on COVID-19 beliefs, behaviours and norms

Authors

Affiliations

Abstract

References

Publication types

MeSH terms

LinkOut - more resources

Full Text Sources

Medical