Significant and sustained decrease in non-SARS-CoV-2 respiratory viral infections during COVID-19 public health interventions

  1. Jeffrey D. Whitman
  2. Phong Pham
  3. Caryn Bern
  4. Elaine M. Dekker
  5. Barbara L. Haller
  6. Vivek Jain
  7. Lisa G. Winston

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Abstract

Public health interventions to decrease the spread of SARS-CoV-2 were largely implemented in the United States during spring 2020. This study evaluates the additional effects of these interventions on non-SARS-CoV-2 respiratory viral infections from a single healthcare system in the San Francisco Bay Area. The results of a respiratory pathogen multiplex polymerase chain reaction panel intended for inpatient admissions were analyzed by month between 2019 and 2020. We found major decreases in the proportion and diversity of non-SARS-CoV-2 respiratory viral illnesses in all months following masking and shelter-in-place ordinances. These findings suggest real-world effectiveness of nonpharmaceutical interventions on droplet-transmitted respiratory infections.

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  1. ScreenIT

    SciScore for 10.1101/2021.05.11.21256147: (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.
    Cell Line AuthenticationAuthentication: Results of a multiplex polymerase chain reaction respiratory pathogen panel (RPP) assay (FilmArray RP2, Biofire Diagnostics) were extracted from the Zuckerberg San Francisco General Hospital (ZSFG) clinical laboratory information system from January 2019 to December 2020; a period spanning approximately one year before and during the COVID-19 pandemic.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All statistical analyses were performed in Prism 9.0.0 (GraphPad Software).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    This project was approved by UCSF Human Research Protections Program (IRB# 20-32769) and ZSFG protocol approval board.
    UCSF Human Research Protections Program
    suggested: None

    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 contains certain limitations. We employed a cross-sectional design comparing two years of data from a single healthcare system. As such, we cannot control for year-to-year variations in viral respiratory illnesses or demographic confounders in our study population. Our data may also be affected by reduction of health services or avoidance of medical care directly from COVID-19 and evolving local policies regarding allowable indoor businesses and personal gathering (6, 7). Despite this, our focus on inpatients tested for respiratory infections, rather than the larger population of outpatients, should decrease variation in testing practices that may occur from workup of mild and undifferentiated illness. While our findings add to the evidence regarding effective disease mitigation strategies (8–10), it is also notable that the low rate of respiratory virus detection remained low during intermittent months of increased public interaction and movement in the Bay Area, including periods when businesses were allowed to partially reopen, times at which civil protests occurred, and periods of increased summer outdoor recreational activities. This suggests a central role for masking and reduction of enclosed space gathering for the disruption of respiratory viral transmission. Since our study population focuses on prospective inpatient admissions, these results primarily represent moderate and severe infections requiring high-level care. As such, these findings also suggest ...

    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.

    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.

  2. Version published to 10.1101/2021.05.11.21256147 on medRxiv