Unlocking SARS-CoV-2 detection in low- and middle-income countries

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Abstract

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  1. SciScore for 10.1101/2021.04.14.21255479: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot 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:
    Paradoxically, globalization hampered LMICs for accessing molecular detection solutions, yet unlocked the access to information for driving local efforts to deal with the global market limitations. The latter is further evidenced by several and remarkable open access initiatives like BEARmix (Graham et al., 2021), Addgene (https://www.addgene.org/), BEI Resources (https://www.beiresources.org/), Nextstrain (https://nextstrain.org/), and GISAID (https://www.gisaid.org/). The work presented here was fully performed in a LMIC laboratory and used all available open access resources to implement a molecular toolkit aiming to provide versatile solutions for LMICs, and to cope with the international shortage of testing supplies for SARS-CoV-2 or any other pathogenic agent. The molecular toolkit validated here shows high versatility to be adapted to different contexts by exploiting widely accepted and known PCR-based methods (Figure 4A). The initial stage focused on providing a minimal set of essential recombinant enzymes that allows the amplification and visualization of viral genes in laboratories with minimal equipment. The open access BEARmix initiative was particularly important as they kindly provided plasmids, protocols, and initial conditions along their development and prior to any publication (Graham et al., 2021). Yet, some routines of the protein production workflow needed to be adapted due to equipment availability. For instance, enzyme production can be achieved to high...

    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.
    • Thank you for including a protocol registration statement.

    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.