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  1. SciScore for 10.1101/2022.05.04.22274692: (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:
    These results might be explained by the limitations of the statistical models which yielded these predictions. Additionally, specific local population and environmental characteristics as well as the low case ascertainment might have had a mitigating effect. The prediction model of the MRC Centre for Global Infectious Disease Analysis at Imperial College London was built on estimates of severity obtained from data from China and Europe, and model parameters obtained from data from China and the United Kingdom (11). On the other hand, Pearson et al. considered that the reproductive number R (which is the number of ancillary cases that one case would generate if in contact with a completely susceptible population (18)) would be 2, that the dispersion estimate k (which is the variance of R over the mean of R and quantifies whether a set of observed cases are clustered or dispersed when compared to cases following a standard negative binomial distribution (19)) would be 0.58, and that the serial interval (which is the time that elapses between two consecutive cases of an infectious disease (20)) would be normally distributed with a mean of 4.7 ± 2.9 days (1). These model parameters all originated from populations which substantially differ from SSA populations in terms of composition, density, living customs, and health status, all of which impact the dynamic of the COVID-19 pandemic. Furthermore, Abbot et al. acknowledged that data were scarce at the time they estimated R and k,...

    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.

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