Site-specific wastewater-based surveillance in early detection of COVID-19 new cases and prediction of mass testing outcomes in long-term care facilities
Rattachement africain : ca. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
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.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Site-specific wastewater-based surveillance in early detection of COVID-19 new cases and prediction of mass testing outcomes in long-term care facilities
- Date Crossref
- 13/04/2026
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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University of Alberta Department of Pediatrics pays non établi dans la noticeUniversité ou école supérieure
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Simon Fraser University Department of Statistics and Actuarial Science pays non établi dans la noticeUniversité ou école supérieure
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Alberta Precision Laboratories pays non établi dans la noticeÉtablissement de santé
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Alberta Health Services pays non établi dans la noticeÉtablissement de santé
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Alberta Health pays non établi dans la noticeOrganisme public
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School of Public Health pays non établi dans la noticeUniversité ou école supérieure
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Faculty of Medicine & Dentistry Department of Laboratory Medicine & Pathology pays non établi dans la noticeUniversité ou école supérieure
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Public Health Laboratory pays non établi dans la noticeStructure de recherche
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Edmonton Zone pays non établi dans la noticeInstitution
Department of Pediatrics — University of Alberta, Department of Statistics and Actuarial Science — Simon Fraser University et Alberta Precision Laboratories, avec 6 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.