Optimizing RT-PCR detection of SARS-CoV-2 for developing countries using pool testing

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Abstract

No abstract available

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  1. SciScore for 10.1101/2020.04.15.20067199: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: This work is considered thus for as a public health intervention to improve diagnosis and individual consent nor ethical approval was requested.
    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: We detected the following sentences addressing limitations in the study:
    Our study has the limitation of having performed only 31 pools on 63 nasopharyngeal samples (40 negatives and 23 positives), however, results were consistent and provide relevant information for the implementation of strategies that might allow optimizing the detection of SARS-CoV-2. We included 5 samples in each pool which seems adequate in our current situation with a near overall 10% positivity rate. In areas with lower positivity rates, especially in future post-pandemic testing, increasing sample numbers in the pool can be considered. Finally, we did not test the inclusion of more than one sample in each pool, however, we would not expect this to modify the observed results. In conclusion, sample pooling and nucleic acid extraction through automated or manual methods are a reliable and efficient alternative strategy for less developed regions with reduced detection capacity.

    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.