SARS-CoV-2 Seroprevalence among Healthcare Workers in General Hospitals and Clinics in Japan

  1. Tatsuya Yoshihara
  2. Kazuya Ito
  3. Masayoshi Zaitsu
  4. Eunhee Chung
  5. Izumi Aoyagi
  6. Yoshikazu Kaji
  7. Tomomi Tsuru
  8. Takuma Yonemura
  9. Koji Yamaguchi
  10. Shinichi Nakayama
  11. Yosuke Tanaka
  12. Nobuo Yurino
  13. Hideki Koyanagi
  14. Shunji Matsuki
  15. Ryuji Urae
  16. Shin Irie

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Abstract

Coronavirus disease 2019 (COVID-19) has become a serious public health problem worldwide. In general, healthcare workers are considered to be at higher risk of COVID-19 infection. However, the prevalence of COVID-19 among healthcare workers in Japan is not well characterized. In this study, we aimed to examine the seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) antibodies among 2160 healthcare workers in hospitals and clinics that are not designated to treat COVID-19 patients in Japan. The prevalence of SARS-CoV-2 immunoglobulin G was 1.2% in August and October 2020 (during and after the second wave of the pandemic in Japan), which is relatively higher than that in the general population in Japan (0.03–0.91%). Because of the higher risk of COVID-19 infection, healthcare workers should be the top priority for further social support and vaccination against SARS-CoV-2.

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  1. Version published to 10.3390/ijerph18073786
  2. ScreenIT

    SciScore for 10.1101/2021.01.23.21249922: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the SOUSEIKAI Hakata Clinic Institutional Review Board (approval number: N-105) and registered in the UMIN Clinical Trial Registry (registration number: UMIN000041262).
    Consent: All participants provided a written informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    SARS-CoV-2-specific IgM and IgG antibodies in the venous blood were assessed using an immunochromatographic assay kit
    IgG
    suggested: None

    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:
    One limitation of this study is that only one antibody assay kit was used. As PCR tests or antigen tests were not conducted in participants with SARS-CoV-2 IgM or IgG antibodies, it remained uncertain whether false-positive data were included. In particular, among the eight participants who tested positive for IgM antibodies alone in August, none tested positive for IgG antibodies in October. We recruited individuals working at SOUSEIKAI medical group facilities for this study; of them, 91.6% (2,142 out of 2,338) in August and 90.0% (2,081 out of 2311) in October participated in this study. Thus, the effect of selection bias is limited. In conclusion, the prevalence of SARS-CoV-2 IgG antibodies among healthcare workers in Japan was 1.2%, which was relatively higher than that in Japan’s general population. Healthcare workers are at higher risk of infection; hence, they should be the top priority for further social support and SARS-CoV-2 vaccination.

    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 10.1101/2021.01.23.21249922v1 on medRxiv