Impact of climatic, demographic and disease control factors on the transmission dynamics of COVID-19 in large cities worldwide

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Abstract

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  1. SciScore for 10.1101/2020.07.17.20155226: (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:
    The presented analytical framework is subject to some methodological assumptions and caveats. Firstly, our study relies on six months of case data with variable data quality between sources. For example, data describing case counts in China between different sources have demonstrated some inconsistencies (Python et al., 2020), potentially as a result of differences in case definitions or magnitude and strategy of testing. Similarly, epidemic trajectory is still currently unclear for several cities, particularly those in Africa where cases may not have yet reached peak epidemic growth (WHO, 2020b). A more detailed analysis of climate variability would require data at interannual to decadal time scales, though only one previous betacoronavirus pandemic has occurred to date. For influenza, Shaman and Lipsitch (2013) have highlighted that each major pandemic (1918, 1957, 1968, and 2009) was preceded by La Niña conditions e.g. colder sea surface temperatures than average in the equatorial Pacific. This year, winter temperature conditions were close to neutral in the Pacific, but a mild La Niña signal seems to be developing during boreal spring-summer 2020 (NOAA Climate Prediction Center, 2020) and further data will be necessary for formal influenza comparisons. Our analysis covers large cities on all inhabited continents. However, data was unavailable for cities in the arid Middle East and in colder parts of the world, e.g. northern Russia, therefore our models represent a restric...

    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

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