Staff–pupil SARS-CoV-2 infection pathways in schools in Wales: a population-level linked data approach

  1. Daniel A Thompson
  2. Hoda Abbasizanjani
  3. Richard Fry
  4. Emily Marchant
  5. Lucy Griffiths
  6. Ashley Akbari
  7. Joe Hollinghurst
  8. Laura North
  9. Jane Lyons
  10. Fatemeh Torabi
  11. Gareth Davies
  12. Mike B Gravenor
  13. Ronan A Lyons

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Abstract

Better understanding of the role that children and school staff play in the transmission of SARS-CoV-2 is essential to guide policy development on controlling infection while minimising disruption to children’s education and well-being.

Methods

Our national e-cohort (n=464531) study used anonymised linked data for pupils, staff and associated households linked via educational settings in Wales. We estimated the odds of testing positive for SARS-CoV-2 infection for staff and pupils over the period August– December 2020, dependent on measures of recent exposure to known cases linked to their educational settings.

Results

The total number of cases in a school was not associated with a subsequent increase in the odds of testing positive (staff OR per case: 0.92, 95% CI 0.85 to 1.00; pupil OR per case: 0.98, 95% CI 0.93 to 1.02). Among pupils, the number of recent cases within the same year group was significantly associated with subsequent increased odds of testing positive (OR per case: 1.12, 95% CI 1.08 to 1.15). These effects were adjusted for a range of demographic covariates, and in particular any known cases within the same household, which had the strongest association with testing positive (staff OR: 39.86, 95% CI 35.01 to 45.38; pupil OR: 9.39, 95% CI 8.94 to 9.88).

Conclusions

In a national school cohort, the odds of staff testing positive for SARS-CoV-2 infection were not significantly increased in the 14-day period after case detection in the school. However, pupils were found to be at increased odds, following cases appearing within their own year group, where most of their contacts occur. Strong mitigation measures over the whole of the study period may have reduced wider spread within the school environment.

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  1. Version published to 10.1136/bmjpo-2021-001049
  2. ScreenIT

    SciScore for 10.1101/2021.02.04.21251087: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot 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:
    Study strengths and limitations: Our study included the entire staff and pupil records in Wales, in publicly funded schools, and hence avoids some selection biases, other than through the privately educated sector, which is very small in Wales (75 private schools). The sample size of tests, and numbers of infections was substantial. A key strength is the fine scale of data linkage, which allowed us to link household and school events, which has not been a feature in previous reports. Adjusting for likely transmission in the home and through extended school bubbles is important in clarifying effect sizes for likely transmission in the school and community setting. Among the weaknesses of our study design is that testing for cases has been very largely based on testing those who are symptomatic, and most staff and pupils have not been tested. Hence, our results are based on detected cases and not all infections. The school links are generated from 2019 data. Some pupils will have left or moved school during the summer holidays which could introduce biases. To mitigate against this, we excluded all children aged 11 or 16+ in the 2019 data as these will have moved from primary to secondary schools or have left school. We cannot exclude that there will be some mismatches with linking children to schools they no longer attend. Measures to reduce transmission in the school environment, although advised at a national government level, will likely have varied subtly across schools in ...

    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 10.1101/2021.02.04.21251087v1 on medRxiv