Examining Australian public perceptions and behaviors towards a future COVID-19 vaccine

  1. Holly Seale
  2. Anita E. Heywood
  3. Julie Leask
  4. Meru Sheel
  5. David N. Durrheim
  6. Katarzyna Bolsewicz
  7. Rajneesh Kaur

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Abstract

Background

As immunisation program launches have previously demonstrated, it is essential that careful planning occurs now to ensure the readiness of the public for a COVID-19 vaccine. As part of that process, this study aimed to understand the public perceptions regarding a future COVID-19 vaccine in Australia.

Methods

A national cross-sectional online survey of 1420 Australian adults (18 years and older) was undertaken between 18 and 24 March 2020. The statistical analysis of the data included univariate and multivariable logistic regression model analysis.

Results

Respondents generally held positive views towards vaccination. Eighty percent ( n  = 1143) agreed with the statement that getting myself vaccinated for COVID-19 would be a good way to protect myself against infection . Females ( n  = 614, 83%) were more likely to agree with the statement than males ( n  = 529, 78%) (aOR = 1.4 (95% CI: 1.1–1.8); P  = 0.03), while 91% of those aged 70 years and above agreed compared to 76% of 18–29-year-olds (aOR = 2.3 (95% CI:1.2–4.1); P  = 0.008). Agreement was also higher for those with a self-reported chronic disease (aOR = 1.4 (95% CI: 1.1–2.0); P  = 0.04) and among those who held private health insurance (aOR = 1.7 (95% CI: 1.3–2.3); P  < 0.001). Beyond individual perceptions, 78% stated that their decision to vaccinate would be supported by family and friends.

Conclusion

This study presents an early indication of public perceptions towards a future COVID-19 vaccine and represents a starting point for mapping vaccine perceptions. To support an effective launch of these new vaccines, governments need to use this time to understand the communities concerns and to identify the strategies that will support engagement.

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  1. Version published to 10.1186/s12879-021-05833-1
  2. ScreenIT

    SciScore for 10.1101/2020.09.29.20204396: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: After reading the participant information, consent was implied if the person completed the survey and submitted it via the QOR website.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data were analyzed using the SPSS software version 26.0 (SPSS Science, Chicago, IL, USA).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    However, the work is subject to several limitations including that we recruited a convenience sample of participants. People who could not communicate in English were excluded from the sample, which may have affected representation of ethnic minorities. We also had under-representation of Aboriginal and Torres Strait Islander peoples and those residing in remote settings. As participation in our study was on a voluntary basis, this study has potential for self-selection bias by community members who are particularly concerned about this pandemic.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.09.29.20204396v1 on medRxiv