Tracking community infection dynamics of COVID-19 by monitoring SARS-CoV-2 RNA in wastewater, counting positive reactions by qPCR

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Abstract

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  1. SciScore for 10.1101/2021.12.23.21268343: (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

    Software and Algorithms
    SentencesResources
    Spearman’s rank correlation test was performed in GraphPad Prism 5 software.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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:
    Usefulness and limitation of the positive count method: Although SARS-CoV-2 RNA concentrations in wastewater were lower than the LOQ, the number of positives in repeated RT-qPCR reactions could trace the prevalence of COVID-19 in the community. In conventional qPCR testing, the limit of quantification is usually 5 to 10 copies per reaction. In contrast, the positive count method could distinguish lower copy numbers, i.e., 0.1 to 4 copies per reaction, which means that it increases the sensitivity of qPCR by 50 to 100 times to reveal the trend of viral RNA concentrations in wastewater. For the purpose of tracking the virus infection dynamics in the community, exact values of virus concentrations are not always necessary; it is enough to see the change of viral RNA levels in wastewater, for which the positive count method is useful. We used the positive count method with RT-qPCR of the supernatant fraction of wastewater. This method can also be used with the solid fraction of wastewater. Recent studies have improved the sensitivity of viral RNA detection in wastewater by RT-qPCR by concentrating virus from the solid fraction of raw influent or primary sludge rather than the water fraction.6,8-11 However, in regions where the virus concentration in wastewater is not high enough for quantification from the solid fraction, the positive count methods might be useful to reveal changes in viral RNA levels in wastewater. The idea of the positive count method is the same as that for th...

    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.

    Results from scite Reference Check: We found no unreliable references.


    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.