Performance of a rapid SARS-COV-2 serology test in whole blood and separated plasma

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Abstract

Rapid SARS-COV-2 related serology testing can help identify and manage the spread of infection in decentralized testing environments but the limitation in performance of existing tests in blood has restricted implementation of testing at the point-of-care. Optimization of existing rapid tests in whole blood will require significant effort in the short-term and there is a need for solutions to help bridge the gap in performance between plasma and whole blood. We demonstrate here the implementation of the H.E.R.M.E.S platform, a portable plasma separation system that can enhance the performance of blood-based diagnostic testing, with a commercially available SARS-COV-2 IgG/IgM serology rapid diagnostic test (RDT) in a blinded study with 61 human samples. We compare the performance of the RDT in whole blood and separated plasma and highlight that plasma yields a 39% increase in positivity agreement with PCR in samples collected from patients with early infections. We further legitimize the increase in positivity agreement rate with the help of an independent evaluation by 10 previously untrained users. The H.E.R.M.E.S plasma separation system circumvents the need for assay optimization in whole blood and furthers the legitimacy of incorporating SARS-COV-2 serology RDTs at the point-of-care. The data highlighted in this work makes a compelling case for the incorporation of the H.E.R.M.E.S system in large scale efforts to perform SARS-COV-2 serology testing in decentralized testing environments.

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  1. SciScore for 10.1101/2020.10.02.20199083: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationThe order that images were displayed were also randomized for each participant.
    BlindingOnce the samples were received from their respective vendors, they were anonymized and assigned a random 6-digit alphanumeric code to facilitate a blinded study.
    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.