SARS-CoV-2 infection among educational staff in Berlin, Germany, June to December 2020

  1. Sophia Kindzierski
  2. Welmoed van Loon
  3. Stefanie Theuring
  4. Franziska Hommes
  5. Eberhard Thombansen
  6. Malik Böttcher
  7. Harald Matthes
  8. Heike Rössig
  9. David Weiger
  10. Christof Wiesmann
  11. Tobias Kurth
  12. Valerie Kirchberger
  13. Joachim Seybold
  14. Frank P Mockenhaupt
  15. Maximilian Gertler

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Abstract

SARS-CoV-2 infections in preschool and school settings potentially bear occupational risks to educational staff.

Aim

We aimed to assess the prevalence of SARS-CoV-2 infection in teachers and preschool educators and at identifying factors associated with infection.

Methods

We analysed cross-sectional data derived from 17,448 voluntary, PCR-based screening tests of asymptomatic educational staff in Berlin, Germany, between June and December 2020 using descriptive statistics and a logistic regression model.

Results

Participants were largely female (73.0%), and median age was 41 years (range: 18-78). Overall, SARS-CoV-2 infection proportion was 1.2% (95% CI: 1.0–1.4). Proportion of positive tests in educational staff largely followed community incidence until the start of the second pandemic wave, when an unsteady plateau was reached. Then, the proportion of positive tests in a (concurrent) population survey was 0.9% (95% CI: 0.6–1.4), 1.2% (95% CI: 0.8–1.8) in teachers and 2.6% (95% CI: 1.6–4.0) in preschool educators. Compared with teachers, increased odds of infection were conferred by being a preschool educator (adjusted odds ratio (aOR): 1.6; 95% CI: 1.3–2.0) and by contact with a SARS-CoV-2 infected individual outside of work (aOR: 3.0; 95% CI: 1.5–5.5). In a step-wise backward selection, the best set of associated factors with SARS-CoV-2 infection involved age, occupation, and calendar week.

Conclusions

These results indicate that preschool educators bear increased odds of SARS-CoV-2 infection compared with teachers. At the same time, the private environment appeared to be a relevant source of SARS-CoV-2 infection for educational staff in 2020.

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  1. Version published to 10.2807/1560-7917.es.2022.27.11.2100524
  2. ScreenIT

    SciScore for 10.1101/2021.05.19.21257452: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The study was reviewed and approved by the Charité ethics committee (EA1/313/20), and participants provided informed written consent.
    Consent: The study was reviewed and approved by the Charité ethics committee (EA1/313/20), and participants provided informed written consent.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    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:
    Our study has several limitations including approximate proportions of 15% repeatedly tested and 5% symptomatic individuals. Under-reporting of symptoms (presumed to lead to exclusion from screening) and over-reporting (misunderstood test indication) cannot be excluded. Selection bias due to easily accessible testing might apply. At two testing sites, educational staff not being teacher or educator was excluded, and it is possible that a similar proportion of some 15% applies to the remaining data set. Nevertheless, re-running the analysis with and without exclusion (Supplement 3) did not yield differing results suggesting that our overall results are not substantially affected. Comparing prevalence to community incidence data has inherent limitations. Community incidence is based on notified symptomatic patients or primary contacts, the detection of which is subject to changing testing indication, access to testing, and test willingness. Translating the peak weekly incidence of >200/100,000 in Berlin to a prevalence over seven days of approximately 0.2% provides a figure, which is substantially lower than the simultaneous population prevalence of 1% [5]. Antibody assessments reveal incidence data to be grossly underestimated [9]. Therefore, we compared our figures with population prevalence rather than incidence. The resulting temporal restriction is deplorable as is the mere absence of representative prevalence data in Germany. Absence of complete datasets for all participa...

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.05.19.21257452v1 on medRxiv