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<p>Long-term care facilities (LTCFs) were disproportionately impacted during the COVID-19 pandemic. Site-specific wastewater-based surveillance (WBS) offers a non-invasive alternative to traditional mass testing by capturing collective viral loads in wastewater. This study assessed the effectiveness of WBS in detecting new COVID-19 cases in nine Edmonton LTCFs from January 2021 to May 2023. We used constrained distributed lag models to identify critical windows when wastewater viral loads were significantly associated with new cases. Using this critical window, we evaluated the predictive accuracy of wastewater samples for mass testing outcomes. Fisher’s exact test and Mann-Whitney U test compared WBS accuracy for predicting resident vs. staff cases and examined whether factors like sample type, quantity, outbreak duration, or collection timing influenced accuracy. Among 2,515 wastewater samples, 909 were positive, alongside 825 COVID-19 cases identified from 18,226 clinical specimens. Before the clinical testing scale-down in 2022, eight of nine facilities had critical windows within three days. Wastewater collected three days in advance predicted 85% of negative and 60% of positive mass testing outcomes. WBS more accurately predicted resident cases than staff cases (74% vs. 33%, p=0.02). Other factors did not significantly affect prediction accuracy. Findings support using site-specific WBS to enable timely outbreak responses and better testing allocation among vulnerable populations.</p>

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Site-specific wastewater-based surveillance in early detection of COVID-19 new cases and prediction of mass testing outcomes in long-term care facilities

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月13日

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  • Jiabi Wen,
  • Ken K Peng,
  • Bonita E Lee,
  • Rhonda J Rosychuk,
  • Tiejun Gao,
  • Judy Y Qiu,
  • Michael Y Li,
  • Eleanor Risling,
  • Lorie A Little,
  • Christopher Sikora,
  • Xiaoli Lilly Pang,
  • Arto Ohinmaa

摘要

Long-term care facilities (LTCFs) were disproportionately impacted during the COVID-19 pandemic. Site-specific wastewater-based surveillance (WBS) offers a non-invasive alternative to traditional mass testing by capturing collective viral loads in wastewater. This study assessed the effectiveness of WBS in detecting new COVID-19 cases in nine Edmonton LTCFs from January 2021 to May 2023. We used constrained distributed lag models to identify critical windows when wastewater viral loads were significantly associated with new cases. Using this critical window, we evaluated the predictive accuracy of wastewater samples for mass testing outcomes. Fisher’s exact test and Mann-Whitney U test compared WBS accuracy for predicting resident vs. staff cases and examined whether factors like sample type, quantity, outbreak duration, or collection timing influenced accuracy. Among 2,515 wastewater samples, 909 were positive, alongside 825 COVID-19 cases identified from 18,226 clinical specimens. Before the clinical testing scale-down in 2022, eight of nine facilities had critical windows within three days. Wastewater collected three days in advance predicted 85% of negative and 60% of positive mass testing outcomes. WBS more accurately predicted resident cases than staff cases (74% vs. 33%, p=0.02). Other factors did not significantly affect prediction accuracy. Findings support using site-specific WBS to enable timely outbreak responses and better testing allocation among vulnerable populations.