Comparison of SARS-CoV-2 viral load in saliva samples in symptomatic and asymptomatic cases

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Abstract

SARS-CoV-2 infections can be symptomatic as well as asymptomatic. In this study, we analyzed 460,814 saliva samples collected from July 2020 to January 2021 for a SARS-CoV-2-specific gene target using the FDA EUA test, CRL Rapid Response™, based on reverse transcription polymerase chain reaction (RT-PCR). We measured SARS-CoV-2 viral loads using cycle threshold (Ct) values. A total of 17,813 samples tested positive for COVID-19 using self-collected saliva samples. The Ct values ranged from 11 to 40, 91.3% distributed between 22 to 38 Ct. We then compared Ct values for symptomatic and asymptomatic cases for all positive saliva samples. A total of 8,706 cases were symptomatic with an average Ct value of 29.24, and 9,107 cases were asymptomatic with an average Ct value of 30.99. Hence, SARS-CoV-2 viral loads (Ct) in saliva samples for both symptomatic and asymptomatic cases are similar.

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  1. SciScore for 10.1101/2021.02.12.21251229: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    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: 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.