Due to reduced clinical testing and evolving monitoring challenges, tracking the emergence and evolution of SARS-CoV-2 variants has become increasingly complex. To address this gap, we investigated the utility of wastewater-based epidemiology (WBE) as a complementary tool for SARS-CoV-2 variant surveillance in sewage treatment plants (STPs) across Pune, India. We analyzed 1128 wastewater samples collected between May 2022 and May 2023, using Illumina and nanopore sequencing techniques for robust detection and variant characterization. The study revealed critical findings, including "silent waves" with elevated viral load despite minimal clinical cases, suggesting potential cryptic transmission. These silent waves aligned with the dominance of Omicron BA.2 in June-July 2022 and emergence of the recombinant XBB clade in December 2022. Importantly, sequencing detected XBB lineages 130-253 days before their initial clinical identification, demonstrating its significant advantage in early variant detection. Furthermore, wastewater analysis revealed a higher degree of lineage diversity compared to clinical data, indicating its ability to capture a broader spectrum of circulating variants. The BA.2.86.X was identified 103 days prior to its clinical detection in Pune, highlighting WBE's remarkable lead time. Surprisingly, BF.7.X and BQ.X fragments were also detected in wastewater but not yet reported clinically. These findings demonstrate the remarkable value of WBE as an early warning tool for SARS-CoV-2 variants ahead of time. By revealing silent waves, enabling early variant detection, and capturing a broader viral spectrum, WBE effort could empower public health officials to make informed decisions and implement effective strategies to mitigate future waves, especially in contexts with declining clinical testing.
Keywords: COVID-19; Early warning; Next-generation sequencing; SARS-CoV-2; Wastewater; Wastewater-based epidemiology.
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