Associations between COVID-19 transmission rates, park use, and landscape structure

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Abstract

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  1. SciScore for 10.1101/2020.10.20.20215731: (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

    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:
    A major limitation of the work is the difficulty in comparing across local authorities that vary simultaneously in many different variables likely important to case rates. As mentioned previously, this makes inference about the importance of their individual effects very difficult, or simply not possible. Therefore, we reiterate that our results do not provide evidence that the demographic and social groups included are not more or less affected by COVID-19, and we suggest that any findings from studies directly addressing questions about these groups are given priority. Another challenge is that pandemics are rare events, consequently, our analysis covers only a snapshot of time for each local authority. During this period, many different factors not included in the analysis (e.g. chance super spreading events) may have explained much of the variation between local authorities. Despite this, the model fits are reasonably high, especially after incorporating the green transmission models. However, the modest beneficial effect of park use on COVID-19 transmission could be useful in the general attempt to develop guidance for which spaces to use during an exponential phase of transmission. A further limitation in the work is the underlying quality of the COVID-19 case data. In the first wave of the pandemic, COVID-19 testing capacity was very limited and there were reports of testing demand exceeding capacity, where people showing COVID-19 symptoms were unable to receive a test...

    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.