Wastewater surveillance for SARS-CoV-2 and influenza A: A complementary tool for monitoring community transmission...

Clinical surveillance for respiratory viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A underestimates community transmission due to limited detection of asymptomatic infections and high resource requirements. Wastewater-based surveillance (WWS) provides a cost-effective, noninvasive approach for population-level monitoring. This study evaluated the concordance between wastewater and clinical surveillance for detection and genetic characterization of SARS-CoV-2 and influenza A. Fortnightly wastewater samples (n = 649) were collected from March 2022 to June 2023 across 11 sewage treatment plants in Bhopal, India. Samples were concentrated using polyethylene glycol precipitation, followed by RNA extraction and reverse transcription-polymerase chain reaction (RT-PCR) detection of SARS-CoV-2 and influenza A. RT-PCR-positive samples underwent viral subtyping and whole genome sequencing. Clinical surveillance data were analyzed concurrently, and temporal trends and phylogenetic relationships were assessed. SARS-CoV-2 RNA was detected in 10 influent wastewater samples during April 2023, coinciding with a surge in reported COVID-19 cases. Influenza A RNA was detected in 32 wastewater samples, with trends aligning with seasonal influenza activity. Wastewater surveillance captured subtype transitions from H1N1pdm09 to H3N2 and identified persistent H1N1 circulation beyond its period of clinical predominance. Whole genome sequencing identified SARS-CoV-2 Omicron sub-lineages XBB.1 and XBB.1.16, matching variants circulating in patients. Phylogenetic analyses showed close clustering of wastewater-derived and clinical viral genomes, with no evidence of novel lineages. All treated effluent samples tested negative. WWS provided sensitive, near real-time insights into community transmission of SARS-CoV-2 and influenza A, demonstrating strong temporal and genomic concordance with clinical data. WWS represents a valuable complementary surveillance tool for early outbreak detection, particularly in resource-limited settings.