Comparative evaluation of clinical and wastewater genomic surveillance for SARS-CoV-2: implications for integrated infectious disease monitoring

IntroductionThe COVID-19 pandemic demonstrated the need for comprehensive, cost-effective surveillance systems integrating multiple data streams. This study directly compares SARS-CoV-2 genomic data from wastewater-based surveillance (WBS) and clinical diagnostic testing (CDT) to evaluate lineage diversity, detection timing, and persistence patterns that could inform integrated surveillance strategies. MethodsWe analyzed SARS-CoV-2 genomic data from Alberta, Canada (July 2022 - March 2025), encompassing 13 municipal wastewater treatment plants covering 80% of the provincial population and clinical samples from provincial diagnostic testing. Clinical samples (n=28,610) and wastewater samples (n=1,685) were sequenced using a tiled amplicon approach. We compared lineage richness over time, lead time for first detection using collection dates and explored four additional wastewater metrics: abundance at first detection, peak abundance, time to peak abundance, and total time detected. The comparison grouped lineages into those found only in WBS and those that were seen in both WBS and CDT. ResultsOf the 2,586 unique lineages identified over the study period, 1,588 (61.1%) appeared exclusively in WBS, 42 (1.6%) only in CDT, and 956 (36.9%) in both systems. WBS consistently demonstrated higher monthly lineage richness (95-660 lineages) compared to CDT (23-160 lineages). While WBS detected lineages an average of almost 12 days earlier than CDT, the most frequent pattern showed CDT detection first by 8 days, indicating substantial variability. Lineages detected in both systems showed significantly higher initial relative abundance, peak relative abundance, longer persistence, and delayed time to peak compared to WBS-only lineages (all p<0.0001). ConclusionsWBS and CDT provide complementary surveillance capabilities with distinct strengths. Rather than relying on "first detection" as an early warning metric, integrated surveillance should prioritize concordance patterns and abundance metrics that indicate lineages with sustainable transmission potential. These findings support developing surveillance frameworks that strategically combine population-level WBS monitoring with case-linked CDT data for more effective public health response. KEY MESSAGESO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIWBS can detect SARS-CoV-2 and other pathogens at the population level and has been described as an early warning system, while CDT provides case-linked genomic data but may be biased towards symptomatic, high-risk or healthcare-seeking individuals. C_LIO_LIBoth surveillance methods were used during the COVID-19 pandemic, but it remains uncertain how to best integrate WBS and CDT genomics and which WBS metrics are most informative. C_LI What this study addsO_LIThis study provides the first direct comparison of SARS-CoV-2 genomic data from WBS and CDT processed by a single laboratory over nearly three years. C_LIO_LIWBS consistently captured greater lineage diversity than CDT, but "first detection" showed substantial variability, with lineages frequently detected in clinical samples before wastewater. C_LIO_LILineages identified in both surveillance systems showed distinct signatures: higher peak abundance and longer persistence, suggesting these concordance patterns are more reliable indicators than timing alone. C_LI How this study might affect research, practice or policyO_LIIntegrated surveillance frameworks should prioritize monitoring concordance between WBS and CDT, using abundance and persistence metrics to identify lineages with significant transmission potential. C_LIO_LIThe complementary strengths of these systems support their combined use for cost-effective surveillance with WBS monitoring population trends and CDT providing clinical context for targeted interventions. C_LI