SARS-CoV-2 RNA concentrations in primary municipal sewage sludge as a leading indicator of COVID-19 outbreak dynamics

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Abstract

We report a time course of SARS-CoV-2 RNA concentrations in primary sewage sludge during the Spring COVID-19 outbreak in a northeastern U.S. metropolitan area. SARS-CoV-2 RNA was detected in all environmental samples, and when adjusted for the time lag, the virus RNA concentrations tracked the COVID-19 epidemiological curve. SARS-CoV-2 RNA concentrations were a leading indicator of community infection ahead of compiled COVID-19 testing data and local hospital admissions. Decisions to implement or relax public health measures and restrictions require timely information on outbreak dynamics in a community.

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  1. SciScore for 10.1101/2020.05.19.20105999: (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

    Software and Algorithms
    SentencesResources
    Samples were analyzed using the Bio-Rad iTaq Universal Probes One-Step kit in 20 μL reactions run at 50°C for 10 min, 95°C for 1 min followed by 40 cycles of 95°C for 10 s and 60°C for 30 s per the manufacturer’s recommendations.
    Bio-Rad iTaq Universal Probes
    suggested: None
    iTaq
    suggested: None

    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:
    Jurisdictions can use primary sludge SARS-CoV-2 concentrations to preempt community outbreak dynamics or provide an additional basis for easing restrictions, especially when there are limitations in clinical testing. Raw wastewater and sludge-based surveillance is particularly useful for low and middle-income countries where clinical testing capacity is limited.

    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.