Rapid Molecular Detection of SARS-CoV-2 (COVID-19) Virus RNA Using Colorimetric LAMP

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Abstract

The ability to detect an infectious agent in a widespread epidemic is crucial to the success of quarantine efforts in addition to sensitive and accurate screening of potential cases of infection from patients in a clinical setting. Enabling testing outside of sophisticated laboratories broadens the scope of control and surveillance efforts, but also requires robust and simple methods that can be used without expensive instrumentation. Here we report a method to identify SARS-CoV-2 (COVID-19) virus RNA from purified RNA or cell lysis using loop-mediated isothermal amplification (LAMP) using a visual, colorimetric detection. This test was additionally verified using RNA samples purified from respiratory swabs collected from COVID-19 patients in Wuhan, China with equivalent performance to a commercial RT-qPCR test while requiring only heating and visual inspection. This simple and sensitive method provides an opportunity to facilitate virus detection in the field without a requirement for complex diagnostic infrastructure.

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  1. SciScore for 10.1101/2020.02.26.20028373: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: Research on developing new diagnostic techniques for COVID-19 using clinical samples has been approved by the ethical committee of Wuhan Institute of Virology.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: Thank you for sharing your data.


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.