Wastewater-Based Genomic Surveillance of SARS-CoV-2 Antiviral Resistance Determinants in Ontario: Towards a Scalable Framework for Population-Level Antiviral Resistance Monitoring

Abstract

Background: Wastewater surveillance has emerged as an effective tool for population-level pathogen monitoring. Its application to mutations associated with resistance to antivirals remains comparatively underdeveloped. We assessed the wastewater epidemiology framework using SARS-CoV-2 as a model pathogen to evaluate spatial, temporal, and therapeutic class-specific resistance dynamics. Methods: We analyzed about 10,000 SARS-CoV-2-positive wastewater samples from six Ontario public health regions collected between October 2021 and July 2024. Fifty-five mutations were screened, comprising therapeutic resistance-associated mutations and a biologically distinct group of immune-evasion mutations. Mutations detected in ≥10 samples at ≥1% frequency were retained for spatiotemporal analysis using LOESS smoothing and Kruskal–Wallis testing. Results: Twelve mutations met the inclusion thresholds. S:E340D, associated with reduced susceptibility to sotrovimab was geographically widespread but transient and low-frequency. Five remdesivir-associated polymerase mutations were sporadic with sharp localized peaks, including two mutations exceeding 99% frequency in isolated catchments. Three nirmatrelvir-associated protease mutations were detected, with ORF1a:Q3452K showing significant regional variation. FLiRT and FLuQE immune-evasion mutations were most persistent and abundant. LOESS smoothing showed distinct temporal patterns among mutations, while Kruskal–Wallis testing identified significant regional variation for ORF1a:Q3452K and the three immune-evasion mutations. Conclusions: These findings demonstrate that wastewater surveillance enables population-scale monitoring of antiviral resistance and immune escape-associated mutations and offers a scalable model for broader surveillance.