Incubation Period and Reproduction Number for Novel Coronavirus 2019 (COVID-19) Infections in India

  1. Seema Rajesh Patrikar
  2. Atul Kotwal
  3. Vijay K. Bhatti
  4. Amitav Banerjee
  5. Kunal Chatterjee
  6. Renuka Kunte
  7. Murlidhar Tambe

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Abstract

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  1. Version published to 10.1177/1010539520956427
  2. ScreenIT

    SciScore for 10.1101/2020.06.27.20141424: (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
    The herd immunity (HI) estimate was based on R0 value12. (HI= (R0 – 1) or R0 = 1 − 1/R0) The statistical software used were IBM SPSS Statistics for Windows version 23.0 (SPSS Inc., Chicago, Ill., USA) and EASY-FIT, a software system for data fitting in dynamical systems.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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:
    Limitations of the study: The data on complete information for estimating incubation period as well reproduction number could be extracted for limited number of cases. Also, the time delay of test results, with varying turn around time among States, for estimating incubation period was averaged for India based on the public domain information and media reports.

    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.

  3. Version published to 10.1101/2020.06.27.20141424v1 on medRxiv