Factors That Impact Acceptance of COVID-19 Vaccination in Different Community-Dwelling Populations in China.

COVID-19 influencing factors multi-level logistic regression vaccine acceptance rate

Journal

Vaccines
ISSN: 2076-393X
Titre abrégé: Vaccines (Basel)
Pays: Switzerland
ID NLM: 101629355

Informations de publication

Date de publication:
08 Jan 2022
Historique:
received: 26 11 2021
revised: 24 12 2021
accepted: 05 01 2022
entrez: 22 1 2022
pubmed: 23 1 2022
medline: 23 1 2022
Statut: epublish

Résumé

(1) Background: It is important to improve vaccination strategies and immunization programs to achieve herd immunity to infectious diseases. (2) Methods: To assess the acceptance of COVID-19 vaccination, we conducted face-to-face surveys and online surveys in Shanghai, Zhejiang, and Qinghai provinces. A fixed-effect model and a random effects model were used to analyze factors associated with the acceptance of COVID-19 vaccination. (3) Findings: We initially recruited 3173 participants, 3172 participants completed the full questionnaire (the response rate was nearly 100%), of which 2169 were valid questionnaires, with an effective rate of 87.3%. The results indicated that 82.6% of participants were willing to receive vaccination when it was available in the community, and 57.2% of deliverymen, 43.3% of medical workers, 78.2% of parents of primary and secondary school children, and 72.2% of parents of preschool children were willing to receive vaccination. The models showed that participants who were male (female vs. male: OR = 1.49, 95% CI (1.12, 1.98)), 60 to 69 years-old (60-69 vs. <30: OR = 0.52, 95% CI (0.29, 0.92)), had less education (medium vs. low: OR = 1.50, 95% CI (1.05, 2.23)), had good health status (good vs. low: OR = 0.36, 95% CI (0.15, 0.88)), and had positive attitudes and trust (OR = 0.14, 95% CI (0.10, 0.20)) in vaccines approved by the National Health Commission were more likely to accept vaccination. Participants also had an increased vaccination acceptance if it was recommended by government sources, doctors, relatives, or friends. Most participants learned about COVID-19 vaccination from television, radio, and newspapers, followed by community or hospital campaigns and the internet. (4) Conclusions: Government sources and doctors could increase the acceptance of vaccination by promoting the efficacy and safety of COVID-19 vaccination by the use of mass media and emphasizing the necessity of vaccination for everyone.

Identifiants

pubmed: 35062753
pii: vaccines10010091
doi: 10.3390/vaccines10010091
pmc: PMC8779453
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Bill & Melinda Gates Foundation
ID : INV-006277
Pays : United States

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Auteurs

Jinhua Pan (J)

Key Lab of Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.

Kezhong A (K)

Department of Immunization Programme Institute, Qing Hai Center for Disease Prevention and Control, Qinghai 810007, China.

Zhixi Liu (Z)

Key Lab of Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.

Peng Zhang (P)

Huzhou Center for Disease Prevention and Control, Huzhou 313000, China.

Zhiyin Xu (Z)

Department of Infections Disease Prevention and Control, Minhang Center for Disease Prevention and Control, Shanghai 201100, China.

Xiaoqin Guo (X)

Songjiang Center for Disease Prevention and Control, Shanghai 201600, China.

Guangtao Liu (G)

Huzhou Center for Disease Prevention and Control, Huzhou 313000, China.

Ao Xu (A)

Key Lab of Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.

Jing Wang (J)

Department of Health and Environmental Sciences, Xi'an Jiaotong-Liverpool University, Suzhou 215000, China.

Xinyu Wang (X)

Key Lab of Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.

Weibing Wang (W)

Key Lab of Public Health Safety of the Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.

Classifications MeSH