A0900
Title: Wastewater-based surveillance for early COVID-19 case detection and mass testing prediction in long-term care facilities
Authors: Jiabi Wen - University of Alberta (Canada) [presenting]
Kangyi Peng - Simon Fraser University (Canada)
Bonita E Lee - University of Alberta (Canada)
Rhonda J Rosychuk - University of Alberta (Canada)
Tiejun Gao - University of Alberta (Canada)
Judy Y Qiu - University of Alberta (Canada)
Michael Y Li - University of Alberta (Canada)
Eleanor Risling - University of Alberta (Canada)
Lorie A Little - Alberta Health Services (Canada)
Christopher Sikora - Alberta Health Services (Canada)
Xiao L Pang - University of Alberta (Canada)
Arto Ohinmaa - University of Alberta (Canada)
Abstract: Long-term care facilities (LTCFs) were disproportionately affected during the COVID-19 pandemic. While mass testing aids outbreak control, it is invasive and resource-intensive. Site-specific wastewater-based surveillance (WBS) offers a non-invasive alternative by capturing collective viral signals in facility wastewater. The effectiveness of WBS is assessed in detecting new COVID-19 cases in nine Edmonton LTCFs from January 2021 to May 2023. Constrained distributed lag models are used to identify critical windows when wastewater viral loads were significantly associated with new cases. The predictive accuracy of wastewater samples collected within these windows for mass testing outcomes is then evaluated, defined as testing 10-100% of facility residents and staff. Statistical comparisons (Fisher's exact and Mann-Whitney U tests) examined WBS accuracy by result type, population group, outbreak and wastewater operational factors. Prior to clinical testing scale-down in 2022, eight of nine facilities had critical detection windows within three days. Among 198 mass testing events, 140 had wastewater samples collected 13 days prior. Wastewater predicted 85% of negative and 60% of positive testing outcomes and had higher accuracy for predicting resident than staff cases (74% vs. 33%, p=0.02). These findings support the use of WBS for timely outbreak response and more targeted testing in LTCFs.
