The Impact of Keeping Indoor Dining Closed on COVID-19 Rates Among Large US Cities

  1. Alina S. Schnake-Mahl
  2. Gabriella O’Leary
  3. Pricila H. Mullachery
  4. Vaishnavi Vaidya
  5. Gabrielle Connor
  6. Heather Rollins
  7. Jennifer Kolker
  8. Ana V. Diez Roux
  9. Usama Bilal

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Abstract

Indoor dining is one of the potential drivers of COVID-19 transmission. We used the heterogeneity among state government preemption of city indoor dining closures to estimate the impact of keeping indoor dining closed on COVID-19 incidence.

Methods:

We obtained case rates and city or state reopening dates from March to October 2020 in 11 US cities. We categorized cities as treatment cities that were allowed by the state to reopen but kept indoor dining closed or comparison cities that would have kept indoor dining closed but that were preempted by their state and had to reopen indoor dining. We modeled associations using a difference-in-difference approach and an event study specification. We ran negative binomial regression models, with city-day as the unit of analysis, city population as an offset, and controlling for time-varying nonpharmaceutical interventions, as well as city and time fixed effects in sensitivity analysis and the event study specification.

Results:

Keeping indoor dining closed was associated with a 55% (IRR = 0.45; 95% confidence intervals = 0.21, 0.99) decline in the new COVID-19 case rate over 6 weeks compared with cities that reopened indoor dining, and these results were consistent after testing alternative modeling strategies.

Conclusions:

Keeping indoor dining closed may be directly or indirectly associated with reductions in COVID-19 spread. Evidence of the relationship between indoor dining and COVID-19 case rates can inform policies to restrict indoor dining as a tailored strategy to reduce COVID-19 incidence. See video abstract at, http://links.lww.com/EDE/B902.

Article activity feed

  1. Version published to 10.1097/ede.0000000000001444
  2. ScreenIT

    SciScore for 10.1101/2021.04.12.21251656: (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

    Software and Algorithms
    SentencesResources
    We conducted analyses in R 4.0.2 and STATA 15.1.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has several limitations. The cities are similar on multiple potential confounders that may affect COVID incidence and NPI implementation and compliance, including political leaning, age structure, socioeconomic and housing factors, service workers percentage and mask compliance. However, only a small number of cities met study inclusion criteria, and treatment cities were smaller, had larger, Black and smaller Hispanic populations, and used transit more frequently than comparison cities. These differences should not bias our difference-in-difference analysis unless they were changing significantly during the study period. However, our treatment and comparison groups may differ on other factors related to COVID-19 rates, and our approach does not capture relevant unmeasured or unobservable time-varying between-city confounders, that may have increased COVID-19 transmission, such as mobility data or longitudinal test count, which is not available at the city/county level. Re-opening indoor dining timing in some states coincided with other re-openings such as museums, malls, and theaters. Though contact tracing data suggests that such activities pose relatively limited risk for COVID-19 transmission32, if re-opening other non-essential leisure activities also contributed to increased infections then our results may slightly overestimate the association attributable to indoor dining. Importantly, and given transmission dynamics of an infectious disease like COVID-19, th...

    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 10.1101/2021.04.12.21251656 on medRxiv