A national survey of potential acceptance of COVID-19 vaccines in healthcare workers in Egypt

  1. Aliae AR Mohamed Hussein
  2. Islam Galal
  3. Nahed A Makhlouf
  4. Hoda A Makhlouf
  5. Howaida K Abd-Elaal
  6. Karima MS Kholief
  7. Mahmoud M Saad
  8. Doaa A Abdellah

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Abstract

Background

Since the start of COVID-19 outbreak investigators are competing to develop and exam vaccines against COVID-19. It would be valuable to protect the population especially health care employees from COVID-19 infection. The success of COVID-19 vaccination programs will rely heavily on public willingness to accept the vaccine.

Aims

This study aimed to describe the existing COVID-19 vaccine approval landscape among the health care providers and to identify the most probable cause of agreement or disagreement of COVID-19 vaccine.

Methods

A cross-sectional online survey was done.

Results

The present study included 496 health care employees, 55% were at age group from 18-45 years old. History of chronic diseases was recorded in 40.4%, and definite history of drug/food allergy in 10.1%. Only 13.5% totally agree to receive the vaccine, 32.4% somewhat agree and 40.9% disagreed to take the vaccine. Causes of disagreement were none safety, fear of genetic mutation and recent techniques and believe that the vaccine is not effective (57%, 20.2%, 17.7% and 16.6% respectively). The most trusted vaccine was the mRNA based vaccine. The age of health care employees and the presence of comorbidities or chronic diseases were the main factors related to COVID-19 acceptance (P<0.001 and 0.02 respectively).

Conclusion

Vaccine hesitancy is not uncommon in healthcare employees in Egypt and this may be an alarming barrier of vaccine acceptance in the rest of population. There is an urgent need to start campaigns to increase the awareness of the vaccine importance.

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  1. ScreenIT

    SciScore for 10.1101/2021.01.11.21249324: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Inclusion criteria were available in the consent form at the beginning of the survey.
    IACUC: The following data were collected including: The study was approved by the ethical committee Assiut Faculty of Medicine and registered in ClinicalTrials.gov Identifier: NCT04694651
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    1 Statistical analysis: Completed forms were imported into a Microsoft Excel spreadsheet.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    Data were then analyzed on Statistical Package for the Social Sciences (SPSS) software version 23 (Chicago, IL, USA).
    Statistical Package for the Social Sciences
    suggested: (SPSS, RRID:SCR_002865)
    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04694651RecruitingPotential Acceptance of COVID-19 Vaccines in Healthcare Work…

    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.

  2. Version published to 10.1101/2021.01.11.21249324v1 on medRxiv