Epidemiologic Parameters for COVID-19: A Systematic Review and Meta-Analysis

  1. Neda Izadi
  2. Niloufar Taherpour
  3. Yaser Mokhayeri
  4. Sahar Sotoodeh Ghorbani
  5. Khaled Rahmani
  6. Seyed Saeed Hashemi Nazari

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Abstract

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  1. Version published to 10.47176/mjiri.36.155
  2. ScreenIT

    SciScore for 10.1101/2020.05.02.20088385: (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
    Search Strategy: To find relevant studies, a comprehensive literature search of the Web of Science, Medline (Pubmed), Scopus and Google Scholar was performed for observational studies published electronically from early December 2019 up to 23 March 2020.
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)

    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:
    As a limitation, all 76 studies (except for one, Mirjam E Kretzschmar et al) (103) have been conducted in Asia, particularly in Wuhan, China. Some epidemiological parameters in Europe, Africa, and America could be different based on control strategies. Hence, distribution of these epidemiological parameters could be more globally. Future studies to calculate more generalized pooled estimates, using studies all over the world, would be recommended.

    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 10.1101/2020.05.02.20088385v1 on medRxiv