Individual factors influencing COVID-19 vaccine acceptance in between and during pandemic waves (July-December 2020)

Autor: Pierre Van Damme, S. Valckx, Maren Vranckx, Niel Hens, Koen Pepermans, Thomas Neyens, Frederik Verelst, Greet Hendrickx, Jonas Crevecoeur, Philippe Beutels
Přispěvatelé: Neyens, Thomas/0000-0003-2364-7555
Jazyk: angličtina
Rok vydání: 2022
Předmět:
COVID-19 Vaccines
GAM
generalized additive model
Coronavirus disease 2019 (COVID-19)
NPI
non-pharmaceutical intervention
Employment sector
Trust
Article
Vaccine willingness
NS
not selected
Pandemic
Humans
Pandemics
Vaccine hesitancy
GLM
Generalized linear model
Government
Vaccines
HCW
healthcare worker
Data collection
General Veterinary
General Immunology and Microbiology
SARS-CoV-2
MMR
Measles Mumps Rubella
Public Health
Environmental and Occupational Health
Outbreak
COVID-19
Educational attainment
Socio-demographics
CI
confidence interval
OR
odds ratio
Infectious Diseases
Vaccination coverage
REF
reference model
UK
United Kingdom
Molecular Medicine
Online survey
EMA
European Medicines Agency
Female
Human medicine
WHO
World Health Organisation
Psychology
Demography
BIC
Bayesian Information Criterion
Zdroj: Vaccine
ISSN: 0264-410X
Popis: Background: A year after the start of the COVID-19 outbreak, the global rollout of vaccines gives us hope of ending the pandemic. Lack of vaccine confidence, however, poses a threat to vaccination campaigns. This study aims at identifying individuals' characteristics that explain vaccine willingness in Flanders (Belgium), while also describing trends over time (July-December 2020). Methods: The analysis included data of 10 survey waves of the Great Corona Survey, a large-scale online survey that was open to the general public and had 17,722-32,219 respondents per wave. Uni-and multivariable general additive models were fitted to associate vaccine willingness with socio-demographic and behavioral variables, while correcting for temporal and geographical variability. Results: We found 84.2% of the respondents willing to be vaccinated, i.e., respondents answering that they were definitely (61.2%) or probably (23.0%) willing to get a COVID-19 vaccine, while 9.8% indicated maybe, 3.9% probably not and 2.2% definitely not. In Flanders, vaccine willingness was highest in July 2020 (90.0%), decreased over the summer period to 80.2% and started to increase again from late September, reaching 85.9% at the end of December 2020. Vaccine willingness was significantly associated with respondents' characteristics: previous survey participation, age, gender, province, educational attainment, household size, financial situation, employment sector, underlying medical conditions, mental well-being, government trust, knowing someone with severe COVID-19 symptoms and compliance with restrictive measures. These variables could explain much, but not all, variation in vaccine willingness. Conclusions: Both the timing and location of data collection influence vaccine willingness results, emphasizing that comparing data from different regions, countries and/or timepoints should be done with caution. To maximize COVID-19 vaccination coverage, vaccination campaigns should focus on (a combination of) subpopulations: aged 31-50, females, low educational attainment, large households, difficult financial situation, low mental well-being and labourers, unemployed and self-employed citizens. (c) 2021 Elsevier Ltd. All rights reserved. The Great Corona Survey is supported by the Research Foundation Flanders (Grant G0G1920N, 2020) and the University of Antwerp Fund. Authors FV, NH and PB acknowledge funding from the European Union’s Horizon 2020 research and innovation programme (Project EpiPose - No. 101003688, 2020). All VAXINFECTIO authors acknowledge funding as part of the Methusalem-Centre of Excellence consortium VAX–IDEA. Support from the Methusalem finance programme of the Flemish Government is gratefully acknowledged. These funding sources had no role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. The authors acknowledge the expert assistance of Linguapolis for linguistical support (for the Great Corona Survey) and Peter De Meyer for distributing news and media items to promote participation in the Great Corona Survey.
Databáze: OpenAIRE
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