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Wastewater-based epidemiology has played a significant role in monitoring the COVID-19 pandemic, yet little is known about degradation of SARS-CoV-2 in sewer networks. Here, we used advanced sewershed modeling software to simulate SARS-CoV-2 RNA degradation in sewersheds across Houston, TX under various temperatures and decay rates. Moreover, a novel metric, population times travel time ( PT ), was proposed to identify localities with a greater likelihood of undetected COVID-19 outbreaks and to aid in the placement of upstream samplers. Findings suggest that travel time has a greater influence on RNA degradation across the sewershed as compared to temperature. SARS-CoV-2 RNA degradation at median travel times was approximately two times greater in 20 °C wastewater between the small sewershed, Chocolate Bayou, and the larger sewershed, 69th Street. Lastly, placement of upstream samplers according to the PT metric can provide a more representative snapshot of disease incidence in large sewersheds. This study helps to elucidate discrepancies between SARS-CoV-2 viral load in wastewater and clinical incidence of COVID-19. Incorporating travel time and SARS-CoV-2 RNA decay can improve wastewater surveillance efforts.
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Year‐long wastewater monitoring for SARS‐CoV‐2 signals in combined and separate sanitary sewers
Abstract COVID‐19 wastewater‐based epidemiology has been performed in catchments of various sizes and sewer types with many short‐term studies available and multi‐seasonal studies emerging. The objective of this study was to compare weekly observations of SARS‐CoV‐2 genes in municipal wastewater across multiple seasons for different systems as a factor of sewer type (combined, separate sanitary) and system size. Sampling occurred following the first wave of SARS‐CoV‐2 cases in the study region (June 2020) and continued through the third wave (May 2021), the period during which clinical testing was widely available and different variants dominated clinical cases. The strongest correlations were observed between wastewater N1 concentrations and the cumulative clinical cases reported in the 2 weeks prior to wastewater sampling, followed by the week prior, new cases, and the week after wastewater sampling. Sewer type and size did not necessarily explain the strength of the correlations, indicating that other non‐sewer factors may be impacting the observations. In‐system sampling results for the largest system sampled are presented for 1 month. Removing wet weather days from the data sets improved even the flow‐normalized correlations for the systems, potentially indicating that interpreting results during wet weather events may be more complicated than simply accounting for dilution. Practitioner PointsSARS‐CoV‐2 in wastewater correlated best with total clinical cases reported in 2 weeks before wastewater sampling at the utility level.Study performed when clinical testing was widespread during the year after the first COVID‐19 wave in the region.Sewer type and size did not necessarily explain correlation strength between clinical cases and wastewater‐based epidemiology results.Removing wet weather days improved correlations for 3/4 utilities studied, including both separate sanitary and combined sewers.
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- PAR ID:
- 10370951
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Water Environment Research
- Volume:
- 94
- Issue:
- 8
- ISSN:
- 1061-4303
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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