Mechanistic modelling of in-sewer viral fate and transport of SARS-CoV-2 to enhance wastewater disease surveillance strategies

Wastewater-based surveillance is a valuable tool for monitoring community-level SARS-CoV-2 transmission, but in-sewer physical and biochemical processes can attenuate and distort viral signals before they reach sampling points, complicating interpretation. We developed a stochastic, mechanistic fate and transport model to quantify viral losses between shedding locations and wastewater treatment plants under dry-weather conditions in Winnipeg, Canada. We explicitly included sedimentation and resuspension of virus-associated solids, biofilm adsorption, and biodegradation. The simulation results suggest sedimentation as the dominant loss pathway, reducing viral concentrations by a mean of 11-33%, compared with 4.1-5% for biofilm adsorption and 4.6-6.5% for biodegradation. Total viral loss across the network ranged from 0% to 80%, corresponding to a population-equivalent loss per neighborhood of up to 8,000 individuals. This value represents the equivalent number of individuals whose viral signals may go undetected due to transport-related losses in the sewer network, reducing the effective population coverage of wastewater-based surveillance to approximately 80% citywide and provide an incomplete picture of the infection risk. Furthermore, the minimum detectable prevalence varied across wastewater treatment plants catchments, ranging from 0.055% to over 0.08%, highlighting spatial differences in surveillance sensitivity. By quantifying the spatial heterogeneity of in-sewer signal attenuation, this study highlights the importance of incorporating fate and transport processes when estimating process limits of detection, designing sampling strategies, and interpreting wastewater-based surveillance data. These findings provide essential guidance for improving the accuracy, sensitivity, and public health utility of wastewater surveillance.