Stabilization of the coronavirus pandemic in Italy and global prospects

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Abstract

The pandemic caused by coronavirus COVID-19 are of great concern. A detailed scientific analysis of this phenomenon is still to come, but now it is urgently needed to evaluate the parameters of the disease dynamics in order to make some preliminary estimations of the number of cases and possible duration of the pandemic. The corresponding mathematical models must be simple enough, since their parameters are unknown and have to be estimated using limited statistical data sets. The SIR model, statistical approach to the parameter identification and the official WHO daily data about the confirmed cumulative number of cases were used to calculate the SIR curves and make some estimations and predictions. New cases in Italy could stop to appear after May 12, 2020, and the final number of such accumulated cases could be around 112 thousand. Some prospects for the global pandemic dynamics are discussed.

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  1. SciScore for 10.1101/2020.03.28.20045898: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    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: 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 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.