COVID-19 Mitigation Practices and COVID-19 Rates in Schools: Report on Data from Florida, New York and Massachusetts

  1. Emily Oster
  2. Rebecca Jack
  3. Clare Halloran
  4. John Schoof
  5. Diana McLeod

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Abstract

This paper reports on the correlation of mitigation practices with staff and student COVID-19 case rates in Florida, New York, and Massachusetts during the 2020-2021 school year. We analyze data collected by the COVID-19 School Response Dashboard and focus on student density, ventilation upgrades, and masking. We find higher student COVID-19 rates in schools and districts with lower in-person density but no correlations in staff rates. Ventilation upgrades are correlated with lower rates in Florida but not in New York. We do not find any correlations with mask mandates. All rates are lower in the spring, after teacher vaccination is underway.

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  1. ScreenIT

    SciScore for 10.1101/2021.05.19.21257467: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    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:
    This represents a preliminary analysis and carries limitations. First, we have comprehensive data for only three states, which are not representative of students across the U.S. as a whole. Second, there is variation in masking only in Florida, meaning that the data may be even less generalizable to all U.S. students. Third, our data only represent cases among people associated with schools, not cases spread in schools. Careful contact tracing would be helpful in focusing on the latter, but is not widely available. Finally, we do not focus on possible community spread as a result of schools opening, which is a separate consideration and has been considered in other work (Courtemanche et al., 2021; Harris et al., 2021; Harell & Lieberman, 2021). Future work with these data, and updated versions, may help shed more light on these issues. Given the challenges of virtual schooling (Diliberti & Kaufman, 2020), there is significant policy pressure to open fully in the fall and to establish the best approaches to doing so. The data here indicates higher density is at least not correlated with higher COVID-19 rates in schools. It may also suggest a more limited need for various mitigation measures in the fall, especially when staff and some older students are vaccinated.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

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

    About SciScore

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  2. Version published to 10.1101/2021.05.19.21257467v1 on medRxiv