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Individual factors influencing COVID-19 vaccine acceptance in between and during pandemic waves (July–December 2020)
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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8634074/ https://www.ncbi.nlm.nih.gov/pubmed/34863621 http://dx.doi.org/10.1016/j.vaccine.2021.10.073 |
Sumario: | 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. |
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