Association Between Nursing Home Crowding and COVID-19 Infection and Mortality in Ontario, Canada

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  1. SciScore for 10.1101/2020.06.23.20137729: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Health region population and community population size were based on Statistics Canada projections for 2020.13 Resident Characteristics: Four different resident characteristics, measured at the home level, were obtained from the most recent Resident Assessment Instrument Minimum Dataset (RAI-MDS),17 from August 2019: female sex (%), age ≥85 years (%), dementia (%), and the mean of the activities of daily living (ADL) impairment scale (0: no impairment, to 28: complete impairment).
    August
    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:
    Limitations: This study was subject to several limitations. First, the nursing home crowding index and the 1999 design standard were strongly related, and, as such, other design features may have played a role in driving COVID-19 incidence other than crowding.15 These could include resident home areas of less than 40 beds (which facilitates cohorting), larger square footage per room occupant, and improved ventilation systems. Second, our examination of crowding was at the nursing home level and we did not know which individual residents occupied single, double, or quadruple occupancy rooms. Third, while we adjusted for aggregate characteristics of nursing home residents, we only had up to date information on nursing home resident characteristics until August 2019, the time of the most recent resident assessment. Fourth, we did not have access to information on nursing home resident race, ethnicity, or socio-economic status. Conclusions: Crowding in nursing homes is common and crowded homes are more likely to experience larger and deadlier COVID-19 outbreaks. Interventions to reduce crowding of nursing homes could reduce future COVID-19 incidence and mortality. These interventions could include: 1) capping maximum room occupancy at 2 for incoming residents, to reduce crowding and prevent future outbreaks, 2) creating temporary overflow capacity, to assist with the management of ongoing outbreaks in crowded homes, 3) adapting existing nursing homes (especially converting multip...

    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.

  2. SciScore for 10.1101/2020.06.23.20137729: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementMethods Ethics Statement The study was approved by the Research Ethics Board of the University of Toronto .Randomizationnot detected.BlindingFailure to acknowledge or understand the challenges of cohorting given th overcrowded nature of certain homes , may represent a blind spot of current strategies .Power Analysisnot detected.Sex as a biological variableResident Characteristics Four different resident characteristics , measured at the home level , were obtained from the most 17 recent Resident Assessment Instrument Minimum Dataset ( RAI-MDS) , ( % ) , age from August 2019: female se

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Resident Characteristics Four different resident characteristics , measured at the home level , were obtained from the most 17 recent Resident Assessment Instrument Minimum Dataset ( RAI-MDS) , ( % ) , age from August 2019: female se ≥85 years ( % ) , dementia ( % ) , and the mean of the activities of daily living ( ADL ) impairment scale ( 0: no impairment , to 28: complete impairment) .
    August
    suggested: None

    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 OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).


    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.