SARS-CoV-2 Detection in Sewage in Santiago, Chile - Preliminary results

  1. Manuel Ampuero
  2. Santiago Valenzuela
  3. Fernando Valiente-Echeverría
  4. Ricardo Soto-Rifo
  5. Gonzalo P. Barriga
  6. Jonás Chnaiderman
  7. Cecilia Rojas
  8. Sergio Guajardo-Leiva
  9. Beatriz Díez
  10. Aldo Gaggero

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Abstract

The detection of viruses in sewage is a method of environmental surveillance, which allows evaluating the circulation of different viruses in a community. This study presents the first results of sewage surveillance to detect the circulation of SARS-CoV-2 virus in Santiago, Chile. Using ultracentrifugation associated with RT-qPCR, we detected SARS-CoV-2 in untreated and treated wastewater samples obtained two treatment plants, which together process around 85% of the wastewater from the city. This is the first report of detection of SARS-CoV-2 in sewage in Chile and indicates that wastewater surveillance could be a sensitive tool useful as a predictive marker of the circulation of the virus in a population and therefore, be used as an early warning tool.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.02.20145177: (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.

  2. ScreenIT

    SciScore for 10.1101/2020.07.02.20145177: (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
    Individuals infected with SARSCoV-2 have recently been reported to shed the virus in the stool, for prolonged periods of time and with variable viral loads that can reach up to 1 x 106 copies or more of viral genome/g of fecal material.3,4,5 On the other hand, it has been observed that there is a significant percentage of the population carrying the infection asymptomatically and therefore, they are not detected as infected despite these individuals are capable of eliminating the virus through respiratory secretions and feces.
    SARSCoV-2
    suggested: None

    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 OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.07.02.20145177 on medRxiv