Successful application of wastewater-based epidemiology in prediction and monitoring of the second wave of COVID-19 with fragmented sewerage systems–a case study of Jaipur (India)

  1. Sudipti Arora
  2. Aditi Nag
  3. Aakanksha Kalra
  4. Vikky Sinha
  5. Ekta Meena
  6. Samvida Saxena
  7. Devanshi Sutaria
  8. Manpreet Kaur
  9. Tamanna Pamnani
  10. Komal Sharma
  11. Sonika Saxena
  12. Sandeep K. Shrivastava
  13. A. B. Gupta
  14. Xuan Li
  15. Guangming Jiang

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Abstract

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  1. Version published to 10.1007/s10661-022-09942-5
  2. ScreenIT

    SciScore for 10.1101/2021.09.11.21263417: (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
    The PCR run was analyzed with Bio-Rad CFX Manager software version 3.1 (Bio-Rad Laboratories).
    Bio-Rad CFX Manager
    suggested: None
    CFX
    suggested: None
    Bio-Rad Laboratories
    suggested: (Bio-Rad Laboratories, RRID:SCR_008426)

    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:
    This becomes more important in India since the development of a proper and integrated wastewater treatment system is far-fetched even in the urban areas considering the overall limitations. Therefore, the present study aimed to investigate the applicability of WBE in the prediction and monitoring of COVID-19 wave in a city level paradigm with a limited interconnected sewerage system. Despite the presence of disconnected and fragmented WWTPs, undergoing the treatment of only 60-70% of the total wastewater generated, the collection sites were selected such that they covered most of the total WWTPs installed in the city. A combination of small and medium decentralized WWTPs and large centralized treatment plants was selected to investigate in detail about the ability & feasibility of WBE to detect the upcoming COVID-19 active case load rise in advance. As mentioned in results section 3.1, it was observed that even with such a restricted coverage, the increase in positivity from various sites could be observed at least 14-20 days (at a total active case count of less than 50 per day) before a visible rise in newly detected active cases. Another important observation to be made in this case study that in contrast to Kumar et al., 2021 this study shows that if the sites are selected carefully it is possible to directly correlate the positivity rate of the sites to the upcoming wave in advance. As is the case in point where this study was able to predict the upcoming wave of COVID19...

    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.

  3. Version published to 10.1101/2021.09.11.21263417v1 on medRxiv