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Examining How Young Adults Perceive, Understand, and Respond to SARS-CoV-2 Variants in Canada and France: Implications for Public Health Preparedness Efforts

Published online by Cambridge University Press:  24 August 2023

Pierre-julien Coulaud*
Affiliation:
Department of Medicine, University of British Columbia, Vancouver, BC, Canada
Florence Débarre
Affiliation:
Institute of Ecology and Environmental Sciences of Paris (IEES-Paris, UMR 7618), CNRS, Sorbonne Université, UPEC, IRD, INRAE, Paris, France
Naseeb Bolduc
Affiliation:
British Columbia Centre on Substance Use, Vancouver, BC, Canada
Devon Greyson
Affiliation:
School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
Jeffrey V. Lazarus
Affiliation:
Barcelona Institute for Global Health (ISGlobal), Hospital Clínic, University of Barcelona, Barcelona, Spain
Marie Jauffret-Roustide
Affiliation:
Centre d'Étude des Mouvements Sociaux (EHESS/CNRS UMR8044/INSERM U1276), Paris, France
Rod Knight
Affiliation:
École de Santé Publique de l’Université de Montréal, Montréal, QC, Canada
*
Corresponding author: Pierre-julien Coulaud; Email: pierre-julien.coulaud@bccsu.ubc.ca
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Abstract

Information

Type
Research Letters
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Society for Disaster Medicine and Public Health
Figure 0

Figure 1.Perceptions, general knowledge, and level of cautiousness regarding the emergence of new COVID-19 variants among young adults in Canada and France.

Figure 1

Table 1.Factors associated with level of caution with regard to the emerging COVID-19 variants among young adults in Canada and France: Results from weighted multivariable logistic regression models