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Number of COVID-19 cases required in a population to detect SARS-CoV-2 RNA in wastewater in the province of Alberta, Canada: Sensitivity assessment.
- Source :
-
Journal of Environmental Sciences (Elsevier) . Mar2023, Vol. 125, p843-850. 8p. - Publication Year :
- 2023
-
Abstract
- With a unique and large size of testing results of 1,842 samples collected from 12 wastewater treatment plants (WWTP) for 14 months through from low to high prevalence of COVID-19, the sensitivity of RT-qPCR detection of SARS-CoV-2 RNA in wastewater that correspond to the communities was computed by using Probit analysis. This study determined the number of new COVID-19 cases per 100,000 population required to detect SARS-CoV-2 RNA in wastewater at defined probabilities and provided an evidence-based framework of wastewater-based epidemiology surveillance (WBE). Input data were positive and negative test results of SARS-CoV-2 RNA in wastewater samples and the corresponding new COVID-19 case rates per 100,000 population served by each WWTP. The analyses determined that RT-qPCR-based SARS-CoV-2 RNA detection threshold at 50%, 80% and 99% probability required a median of 8 (range: 4-19), 18 (9-43), and 38 (17-97) of new COVID-19 cases /100,000, respectively. Namely, the positive detection rate at 50%, 80% and 99% probability were 0.01%, 0.02%, and 0.04% averagely for new cases in the population. This study improves understanding of the performance of WBE SARS-CoV-2 RNA detection using the large datasets and prolonged study period. Estimated COVID-19 burden at a community level that would result in a positive detection of SARS-CoV-2 in wastewater is critical to support WBE application as a supplementary warning/monitoring system for COVID-19 prevention and control. [ABSTRACT FROM AUTHOR]
- Subjects :
- *COVID-19 pandemic
*SARS-CoV-2
*SEWAGE
*SEWAGE disposal plants
*PROBIT analysis
Subjects
Details
- Language :
- English
- ISSN :
- 10010742
- Volume :
- 125
- Database :
- Academic Search Index
- Journal :
- Journal of Environmental Sciences (Elsevier)
- Publication Type :
- Academic Journal
- Accession number :
- 160168207
- Full Text :
- https://doi.org/10.1016/j.jes.2022.04.047