Time Course of COVID-19 Pandemic in Algeria: Retrospective Estimate of the Actual Burden

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Abstract

No abstract available

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  1. SciScore for 10.1101/2020.06.16.20132746: (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
    Statistical analysis and software: This study was carried out using Excel 2013 and STATA/IC 15 software.
    Excel
    suggested: None

    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:
    Our results may have some limitations, the R0 estimation is based on the reported cases, also, the found AS-IFR may not be very precise due to the age-standardization method we used or other factors related to countries specifications, consequently, the actual burden of infections might vary around the found estimations. Nevertheless, we believe that our results are very useful in clarifying the vision for decision-makers, and can help to understand the current situation of the epidemic in Algeria, thus, it can be used to adjust the after containment plan that is already in place since June 07, 2020. However, only a good serological study, based on a representative sampling and a good reliable serological tests can reveal the actual burden of the epidemic in Algeria.

    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.