Pooling for SARS-CoV2 Surveillance: Validation and Strategy for Implementation in K-12 Schools

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Abstract

Repeated testing of a population is critical for limiting the spread of the SARS-CoV-2 virus and for the safe reopening of educational institutions such as kindergarten—grade 12 (K-12) schools and colleges. Many screening efforts utilize the CDC RT-PCR based assay which targets two regions of the novel Coronavirus nucleocapsid gene. The standard approach of testing each person individually, however, poses a financial burden to these institutions and is therefore a barrier to using testing for re-opening. Pooling samples from multiple individuals into a single test is an attractive alternate approach that promises significant cost savings—however the specificity and sensitivity of such approaches needs to be assessed prior to deployment. To this end, we conducted a pilot study to evaluate the feasibility of analyzing samples in pools of eight by the established RT-PCR assay. Participants (1,576) were recruited from amongst the Tufts University community undergoing regular screening. Each volunteer provided two swabs, one analyzed separately and the other in a pool of eight. Because the positivity rate was very low, we spiked approximately half of the pools with laboratory-generated swabs produced from known positive cases outside the Tufts testing program. The results of pooled tests had 100% correspondence with those of their respective individual tests. We conclude that pooling eight samples does not negatively impact the specificity or sensitivity of the RT-PCR assay and suggest that this approach can be utilized by institutions seeking to reduce surveillance costs.

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  1. SciScore for 10.1101/2020.12.16.20248353: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was reviewed and approved by the Institutional Review Board of Tufts University (STUDY00000979: Pooled Testing).
    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.