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Vaccination against COVID-19: A systematic review and meta-analysis of acceptability and its predictors
We aimed to estimate the coronavirus disease 2019 (COVID-19) vaccine acceptance rate and identify predictors associated with acceptance. To this end, we searched PubMed, Web of Science, Cochrane Library, and Embase databases until November 4, 2020. Meta-analyses were performed to estimate the rate w...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8217737/ https://www.ncbi.nlm.nih.gov/pubmed/34171345 http://dx.doi.org/10.1016/j.ypmed.2021.106694 |
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author | Wang, Qiang Yang, Liuqing Jin, Hui Lin, Leesa |
author_facet | Wang, Qiang Yang, Liuqing Jin, Hui Lin, Leesa |
author_sort | Wang, Qiang |
collection | PubMed |
description | We aimed to estimate the coronavirus disease 2019 (COVID-19) vaccine acceptance rate and identify predictors associated with acceptance. To this end, we searched PubMed, Web of Science, Cochrane Library, and Embase databases until November 4, 2020. Meta-analyses were performed to estimate the rate with 95% confidence intervals (CI). Predictors were identified to be associated with vaccination intention based on the health belief model framework. Thirty-eight articles, with 81,173 individuals, were included. The pooled COVID-19 vaccine acceptance rate was 73.31% (95%CI: 70.52, 76.01). Studies using representative samples reported a rate of 73.16%. The pooled acceptance rate among the general population (81.65%) was higher than that among healthcare workers (65.65%). Gender, educational level, influenza vaccination history, and trust in the government were strong predictors of COVID-19 vaccination willingness. People who received an influenza vaccination in the last year were more likely to accept COVID-19 vaccination (odds ratio: 3.165; 95%CI: 1.842, 5.464). Protecting oneself or others was the main reason for willingness, and concerns about side effects and safety were the main reasons for unwillingness. National- and individual-level interventions can be implemented to improve COVID-19 vaccine acceptance before large-scale vaccine rollout. Greater efforts could be put into addressing negative predictors associated with willingness. |
format | Online Article Text |
id | pubmed-8217737 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82177372021-06-23 Vaccination against COVID-19: A systematic review and meta-analysis of acceptability and its predictors Wang, Qiang Yang, Liuqing Jin, Hui Lin, Leesa Prev Med Article We aimed to estimate the coronavirus disease 2019 (COVID-19) vaccine acceptance rate and identify predictors associated with acceptance. To this end, we searched PubMed, Web of Science, Cochrane Library, and Embase databases until November 4, 2020. Meta-analyses were performed to estimate the rate with 95% confidence intervals (CI). Predictors were identified to be associated with vaccination intention based on the health belief model framework. Thirty-eight articles, with 81,173 individuals, were included. The pooled COVID-19 vaccine acceptance rate was 73.31% (95%CI: 70.52, 76.01). Studies using representative samples reported a rate of 73.16%. The pooled acceptance rate among the general population (81.65%) was higher than that among healthcare workers (65.65%). Gender, educational level, influenza vaccination history, and trust in the government were strong predictors of COVID-19 vaccination willingness. People who received an influenza vaccination in the last year were more likely to accept COVID-19 vaccination (odds ratio: 3.165; 95%CI: 1.842, 5.464). Protecting oneself or others was the main reason for willingness, and concerns about side effects and safety were the main reasons for unwillingness. National- and individual-level interventions can be implemented to improve COVID-19 vaccine acceptance before large-scale vaccine rollout. Greater efforts could be put into addressing negative predictors associated with willingness. Elsevier Inc. 2021-09 2021-06-22 /pmc/articles/PMC8217737/ /pubmed/34171345 http://dx.doi.org/10.1016/j.ypmed.2021.106694 Text en © 2021 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Wang, Qiang Yang, Liuqing Jin, Hui Lin, Leesa Vaccination against COVID-19: A systematic review and meta-analysis of acceptability and its predictors |
title | Vaccination against COVID-19: A systematic review and meta-analysis of acceptability and its predictors |
title_full | Vaccination against COVID-19: A systematic review and meta-analysis of acceptability and its predictors |
title_fullStr | Vaccination against COVID-19: A systematic review and meta-analysis of acceptability and its predictors |
title_full_unstemmed | Vaccination against COVID-19: A systematic review and meta-analysis of acceptability and its predictors |
title_short | Vaccination against COVID-19: A systematic review and meta-analysis of acceptability and its predictors |
title_sort | vaccination against covid-19: a systematic review and meta-analysis of acceptability and its predictors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8217737/ https://www.ncbi.nlm.nih.gov/pubmed/34171345 http://dx.doi.org/10.1016/j.ypmed.2021.106694 |
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