Predictors of COVID-19 actual vaccine uptake in Hong Kong: A longitudinal population-based survey

Elsie Yan*, Daniel W L Lai, Haze K L Ng, Vincent W P Lee

*Corresponding author for this work

    Research output: Contribution to journalJournal articlepeer-review

    8 Citations (Scopus)

    Abstract

    Purpose of the research: Identifying predictors of COVID-19 vaccine uptake decisions is central to the development of evidence-based strategies for promoting vaccination. This longitudinal study investigated the link between previous willingness to vaccinate and vaccine uptake decision, and examined potential predictors of vaccine uptake in Hong Kong.

    Methods: A longitudinal telephone survey study was conducted using a population-based sample of Chinese adult residents (≥18 years) in Hong Kong. Data were collected at two time points: T1 (December 2020-January 2021) and T2 (June-July 2021). Primary outcome was vaccine uptake status; whilst independent variables and covariates included socio-demographic factors, COVID-19 related experiences, health beliefs, and perception, as well as vaccine related perceptions.

    Results: Among the 1,003 participants, 23.7% had received a COVID-19 vaccine. Previous willingness to vaccinate did not predict vaccine uptake at later stage. Vaccine uptake by known others ( aOR = 8.00), trust in authorities ( aOR = 1.53), acceptability of non-pharmaceutical preventive measures ( aOR = 2.96), and first-hand experience of COVID-19 ( aOR = 1.32) were significant predictors of vaccine uptake after adjusting for confounding factors.

    Conclusions: Future strategies to promote vaccination may focus on building public trust in government and healthcare professional, and encouraging vaccinated individuals to share their vaccine uptake status via social networking.

    Original languageEnglish
    Article number101130
    Number of pages9
    JournalSSM - Population Health
    Volume18
    DOIs
    Publication statusPublished - Jun 2022

    Scopus Subject Areas

    • Health(social science)
    • Public Health, Environmental and Occupational Health
    • Health Policy

    User-Defined Keywords

    • COVID-19
    • Health belief
    • Pandemic
    • Perception
    • Vaccination
    • Vaccines

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