Wastewater-Based Genomic Surveillance of SARS-CoV-2 Antiviral Resistance Determinants in Ontario: Towards a Scalable Framework for Population-Level Antiviral Resistance Monitoring
Viruses·
- DOI
- 10.3390/v18080923
- PMID
- —
- PMCID
- —
- OpenAlex
- —
- Study type
- Journal article
- Publisher
- MDPI AG
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The methodology supports large-scale tracking of pharmaceutical resistance and viral adaptation markers, indicating potential value for expanding community-level monitoring initiatives.
Structured evidence summary
Research question
The investigation evaluates whether municipal sewage analysis can effectively track spatial, temporal, and medication-specific viral resistance patterns.
Study design
This observational genomic surveillance project examined wastewater specimens over a multi-year timeframe using statistical smoothing and non-parametric testing to identify recurring genetic markers.
Population and setting
Researchers processed roughly ten thousand positive wastewater collections spanning six administrative health districts within Ontario between late 2021 and mid-2024.
Main findings
Twelve genetic variants satisfied the detection criteria. A sotrovimab-related marker appeared broadly but faded quickly at minimal levels. Remdesivir-linked changes emerged intermittently with intense localized surges. Nirmatrelvir-associated alterations displayed clear geographic disparities. Viral variants linked to immune evasion maintained steady prevalence throughout the observation window.
Public-health relevance
The methodology supports large-scale tracking of pharmaceutical resistance and viral adaptation markers, indicating potential value for expanding community-level monitoring initiatives.
Important limitations
No explicit constraints are detailed within the provided summary. Consequently, the summary is limited to the supplied single-article abstract and metadata, and requires the original paper for decision-grade interpretation.
GIDS interpretation
This article contributes to the genomic epidemiology domain by detailing a systematic approach for identifying treatment-resistant and immune-escape markers in municipal sewage networks. It serves as contextual reference material for understanding population-level monitoring frameworks without implying integration into active real-time tracking systems.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 10 auditable classifier relationships to diseases, places, topics, and study design.