ArticleJournal of water and health2025
Hydrological and physicochemical parameters associated with SARS-CoV-2 and pepper mild mottle virus wastewater concentrations for a large-combined sewer system.
Article in Journal of water and health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- First Wastewater-Based Surveillance of Tomato Brown Rugose Fruit Virus (ToBRFV) in Korea.Food and environmental virology · 2026Article
- Near-Source Wastewater Surveillance of SARS-CoV-2, Influenza A, and Respiratory Syncytial Virus With Spatiotemporal Evaluation of Pepper Mild Mottle Virus as a Fecal Indicator.Water environment research : a research publication of the Water Environment Federation · 2026Article
- Temporal dynamics of SARS-CoV-2 detection in wastewater and population infection trends in Mexico City.Frontiers in public health · 2025Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
During COVID-19, surveillance of SARS-CoV-2 in wastewater has been a promising tool for tracking viral infection at the community level. However, in addition to the shedding rates within the community, SARS-CoV-2 concentrations in raw wastewater are influenced by several environmental factors. This study investigated the effects of wastewater characteristics on the viral quantification of SARS-CoV-2 and pepper mild mottle virus (PMMoV) for a large wastewater system with combined sewers. Principal component analysis illustrated that water temperature negatively correlates with SARS-CoV-2 and PMMoV in wastewater, but flow rate and EC are highly correlated with SARS-CoV-2 in spring and winter. The normalization using EC enhanced the correlation with clinical data compared to normalization using pH, flow rate, and raw SARS-CoV-2. The normalization using PMMoV reduced the correlation with clinical data. Multiple linear and random forest (RF) applied to predict the concentrations of SARS-CoV-2 in wastewater, given the confirmed cases and physicochemical parameters. RF regression was the best model to predict SARS-CoV-2 in wastewater (R
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Registered trials
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