Evidence That Higher Temperatures Are Associated With a Marginally Lower Incidence of COVID-19 Cases

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Abstract

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  1. SciScore for 10.1101/2020.03.18.20036731: (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:
    There are several important limitations to this study. These results remain preliminary, as they only include confirmed cases as of February 29th 2020, at which point reported local transmission outside China was relatively limited. There was no data available on many characteristics that affect rate of spread within a region, especially the interventions initiated in response to the detection of imported or locally transmitted cases. Furthermore, the model could not be fitted with a random intercept for country to account for clustering of ADM1 units within countries, as the uneven distribution of the number of affected provinces by country led to model instability. However, the early detection score likely captures part of the country-level variance. Is it also important to note that the classification of cases as local or imported was based on available information, and in some ADM1 (in particular in China, South Korea and Italy) the first imported case could not be identified. These results need to be confirmed by repeating the analysis as the pandemic progresses, and including data on implemented interventions to contain or mitigate COVID-19 as it becomes available. Many LMICs had not detected a COVID-19 case as of 29th February 2020 and therefore were not included in this analysis. Caution is warranted in extrapolating the association between local COVID-19 case counts and temperature to LMICs in tropical regions. COVID-19 outbreaks in LMICs, even if at somewhat lower i...

    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.