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

Mechanistic modelling of in-sewer viral fate and transport of SARS-CoV-2 to enhance wastewater disease surveillance strategies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Mechanistic modelling of in-sewer viral fate and transport of SARS-CoV-2 to enhance wastewater disease surveillance strategies Shokoofeh Nourbakhsh, David Champredon, Usman Khan, Ravinder Lidder, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7774650/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract 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. Earth and environmental sciences/Environmental sciences/Environmental impact Health sciences/Diseases/Infectious diseases/Viral infection Physical sciences/Mathematics and computing/Computational science Earth and environmental sciences/Hydrology Physical sciences/Engineering/Civil engineering Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7774650","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":529665628,"identity":"11986f41-51be-410c-8e18-e49f84cd6b64","order_by":0,"name":"Shokoofeh 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