Wastewater-Based Detection of a Rare SARS-CoV-2 Variant in a Hospital Setting: Implications for Individual-Level Resolution
Year: 2025
Type: article
Abstract: Wastewater-based surveillance is an effective method to monitor community health by detecting pathogens excreted from large populations. Traditionally, wastewater analyses are considered privacy-preserving since samples are pooled. However, advances in molecular resolution may challenge this assumption. This study investigated whether a rare SARS-CoV-2 variant detected in a hospital sewershed could be linked to a specific patient. During 2023, wastewater samples were collected weekly and analyzed for SARS-CoV-2 concentrations and variant composition using droplet digital PCR (ddPCR) and tiled sequencing. During the same period, nasal swab samples from hospital patients were sequenced for comparison. While wastewater was dominated by Omicron lineages, several weeks showed a sharp increase in SARS-CoV-2 concentrations, with over 80% belonging to the Delta lineage AY.25—rare globally since 2022. Nasal swab sequencing identified one patient carrying AY.25, whose admission and discharge coincided with the emergence and disappearance of AY.25 in the hospital’s wastewater. The temporal pattern and sequence similarity suggest that the Delta signal might have originated from this single patient, with sequence differences potentially reflecting intrahost divergence. These findings indicate that, under certain conditions, wastewater signals can be attributed to individuals, highlighting the need to keep in mind the ethical considerations surrounding privacy and data use while benefiting the community through wastewater surveillance.
Source: Environments
Authors: Jeffrey L. Ram, Md Alamin, Azadeh Bahmani, Lance Gable, Sneha Ghosh, Katherine Gurdziel, James Hartrick, Natasha Islam, Paul E. Kilgore, Anthony T. Lagina, Michael Mossing, Armin Namayandeh, Pelumi M. Oladipo, Natalie Ram, Rola Raychouni, William Shuster, Geehan Suleyman, Carrie L. Turner, Benjamin Wasinski, Thameena Yusuf, Marcus Zervos, Xiangmin Zhang, Wanqing Liu
Institutions: Wayne State University, University of Maryland, Baltimore
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,172
OpenAlex ID: W4417436193
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