Timing is everything: the relationship between COVID outcomes and the date at which mask mandates are relaxed

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Abstract

Importance

Several states including Texas and Mississippi have lifted their mask mandates, sparking concerns that this policy change could lead to a surge in cases and hospitalizations.

Objective

To estimate the increase in incidence, hospitalizations, and deaths in Texas and Mississippi following the removal of mask mandates, and to evaluate the relative reduction of these outcomes if policy change is delayed by 90 days.

Design, Setting, and Participants

This study uses an age-stratified compartmental model parameterized to incidence data in Texas and Mississippi to simulate increased transmission following policy change in March or June 2021, and to estimate the resulting number of incidence, hospitalizations, and deaths.

Main Outcomes and Measures

The increase in incidence, hospitalizations, and deaths if mask mandates are lifted on March 14 compared to lifting on June 12.

Results

If transmission is increased by 67% when mask mandates are lifted, we projected 11.39 (CrI: 11.22 - 11.55) million infections, 170,909 (CrI: 167,454 - 174,379) hospitalizations, and 5647 (5511 - 5804) deaths (Figure 1) in Texas from March 14 through the end of 2021. Delaying NPI lift until June reduces the average number of infections, hospitalizations, and deaths by 36%, 65%, and 62%, respectively. Proportionate differences were similar for the state of Mississippi. Peak hospitalization rates would be reduced by 79% and 63% in Texas and Mississippi, respectively.

Conclusions and Relevance

Removal of mask mandates in March 2021 is premature. Delaying this policy change until June 2021, when a larger fraction of the population has been vaccinated, will avert more than half of the expected COVID-19 hospitalizations and deaths, and avoid an otherwise likely strain on healthcare capacity.

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  1. SciScore for 10.1101/2021.03.31.21254646: (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: 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: 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.

    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.