Background: Coronavirus disease 2019 (COVID-19) vaccine acceptance is essential in controlling the virus. Vaccine knowledge influences vaccine acceptance and understanding this is vital in planning immunization strategies.

Objectives: This study aimed to examine the public COVID-19 vaccine knowledge levels and predictors of low knowledge levels in Vietnam.

Methods: A cross-sectional, community-based survey was conducted between April 16 and July 16, 2021. To examine the community knowledge levels regarding the vaccine essentialness and efficacy, a self-administered questionnaire was developed and comprised 7 questions with 5 Likert scale responses corresponding to the levels of agreement or disagreement with the provided statements and scores ranging from 0 to 4. An individual's knowledge score above the mean score of all participants was defined as "acceptable" and that below was defined as "low."

Results: Among 1708 respondents, the mean age was 34.3 ± 13.4 years, 942 (55.2%) were females, and 797 (46.7%) had acceptable knowledge levels. Age (adjusted odds ratio [AOR] 0.984 [95% CI 0.972-0.995], P = 0.005) and being vaccinated against COVID-19 (0.653 [0.431-0.991], P = 0.045) were inversely associated with lower knowledge levels. Those with a Gapminder income of $8 to < $15 per day (1.613 [1.117-2.329], P = 0.001), $2 to < $8 (2.093 [1.313-3.335], P = 0.002), and < $2 (3.341 [1.951-5.722], P < 0.001), less than a high school education (4.214 [1.616-10.988], P = 0.003), and nonclinical professionals and nonhealth lecturers (1.83 [1.146-2.922], P = 0.01) were positively associated with lower knowledge levels.

Conclusion: To ensure a successful vaccine rollout, it is crucial to improve community knowledge about vaccine essentialness and efficacy. Those who are at young age, who have low income or education levels, and working in nonclinical and nonhealth education fields should be the target of the intervention programs. Community education programs may benefit from using those who have been immunized as role models.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8767973PMC
http://dx.doi.org/10.1016/j.japh.2022.01.014DOI Listing

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