Tracking SARS-CoV-2 in rivers as a tool for epidemiological surveillance

  1. María Noel Maidana-Kulesza
  2. Hugo Ramiro Poma
  3. Diego Gastón Sanguino-Jorquera
  4. Sarita Isabel Reyes
  5. María del Milagro Said-Adamo
  6. Juan Martín Mainardi-Remis
  7. Dolores Gutiérrez-Cacciabue
  8. Héctor Antonio Cristóbal
  9. Mercedes Cecilia Cruz
  10. Mónica Aparicio González
  11. Verónica Beatriz Rajal

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Abstract

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  1. Version published to 10.1016/j.scitotenv.2022.157707
  2. ScreenIT

    SciScore for 10.1101/2021.06.17.21259122: (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
    Statistical analyses were run with the InfoStat software (Di Rienzo et al., 2016) and RStudio version 4.0.0 (Ihaka and Gentleman, 1996; R Development Core Team, 2005;
    InfoStat
    suggested: (InfoStat, RRID:SCR_014310)
    RStudio
    suggested: (RStudio, RRID:SCR_000432)
    R Development Core
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)

    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:
    Although it allows to understand the magnitude of the viral circulation in the area, there are some limitations that should be considered, especially if the intention is to estimate the number of infected people. A water body like a river will show flow rate variations due to the input of stormwater, illegal raw sewage, and industrial effluents, among others. In other words, the viral concentration will depend on all those human or natural contributions; thus, those flow rates or dilution factors should be considered if the absolute number of virus were to be calculated. On the other hand, there could be some discussion about the influence of population dynamic in the area of impact. One possibility to account for population dynamics and for other human and non-human inputs is to normalize the viral concentration using some other target or surrogate (Medema et al, 2020b). Some chemical compounds, like fecal sterols like coprostanol (Daughton, 2012; Chen et al, 2014), other viruses common in human urinary tract, like human polyomavirus (HPyV) (McQuaig et al., 2009) or pepper mild mottle virus (PMMoV) (D’Aoust et al, 2020), or bacterial fecal indicators like human Bacteroidales (D’Aoust et al, 2020), just to mention some, have been suggested for normalization. The advantage of using any of them is that, as they are excreted by all the population all the time, then cultural or seasonal effects could be neglected. In addition to the detection of SARS-CoV-2, two other targets link...

    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.
    • Thank you for including a protocol registration statement.

    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.

  3. Version published to 10.1101/2021.06.17.21259122 on medRxiv