Simulating and forecasting the cumulative confirmed cases of SARS-CoV-2 in China by Boltzmann function-based regression analyses

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Abstract

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  1. SciScore for 10.1101/2020.02.16.20023564: (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

    Software and Algorithms
    SentencesResources
    Data fitting with Boltzmann function and estimation of critical dates: Data were organized in Microsoft Excel and then incorporated into Microcal Origin software (note: 2021 Jan 21 was set as day 1 and so on).
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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:
    Another limitation is that this estimate is based on the assumption that the overall conditions are not changing. This might not be true, given that in many regions the workers have started to return for work half a month post the Spring Festival holiday (schedulely ending on Feb 31), which may increase the SARS-CoV-2 infection. In this regard, it is noted that the daily number of new confirmed cases in past a few days in several provinces and cities (e.g., Guangdong Province, Fig. 2A; Shanghai and Shenzhen City, Fig. S1D) have increased a little bit more than predicted by the model.

    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.