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. 2025 Mar;23(3):413-427.
doi: 10.2166/wh.2025.352. Epub 2025 Jan 21.

Hydrological and physicochemical parameters associated with SARS-CoV-2 and pepper mild mottle virus wastewater concentrations for a large-combined sewer system

Luan Nguyen Thanh  1 , Mounia Hachad  2 , Natasha McQuaid  2 , Kateryna Krylova  2 , Loan Nguyen Ha Thanh  2 , Flavia Visentin  2 , Jean-Baptiste Burnet  2 , Fernando Sanchez Quete  3 , Thomas Maere  4 , Alexandra Tsitouras  3 , Peter Vanrolleghem  4 , Dominic Frigon  3 , Stephanie Loeb  3 , Sarah Dorner  2 , Eyerusalem Goitom  2
Affiliations

Hydrological and physicochemical parameters associated with SARS-CoV-2 and pepper mild mottle virus wastewater concentrations for a large-combined sewer system

Luan Nguyen Thanh et al. J Water Health. 2025 Mar.

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 (R2=0.8), with the most important variables being the confirmed cases followed by water temperature. RF model is a potent predictor of the presence of SARS-CoV-2 in wastewater. This enhances the degree of reliability between community outbreaks and SARS-CoV-2 monitoring.

Keywords: COVID-19; SARS-CoV-2 normalization; regression models; wastewater-based epidemiology (WBE).

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Conflict of interest statement

The authors declare there is no conflict.

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