Your browser doesn't support javascript.
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.
Li, Qiaozhi; Lee, Bonita E; Gao, Tiejun; Qiu, Yuanyuan; Ellehoj, Erik; Yu, Jiaao; Diggle, Mathew; Tipples, Graham; Maal-Bared, Rasha; Hinshaw, Deena; Sikora, Christopher; Ashbolt, Nicholas J; Talbot, James; Hrudey, Steve E; Pang, Xiaoli.
  • Li Q; School of Public Health, University of Alberta, Edmonton, AB T6G 2R3, Canada.
  • Lee BE; Department of Pediatrics, University of Alberta, Edmonton, AB T6G 1C9, Canada.
  • Gao T; Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada.
  • Qiu Y; Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada.
  • Ellehoj E; University of Alberta Central Receiving, Edmonton, Alberta, T6G 2R3, Canada.
  • Yu J; Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada.
  • Diggle M; Provincial Laboratory for Public Health, Edmonton, Alberta, Canada.
  • Tipples G; Provincial Laboratory for Public Health, Edmonton, Alberta, Canada.
  • Maal-Bared R; EPCOR, Edmonton, AB T5H 0E8, Canada.
  • Hinshaw D; Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada.
  • Sikora C; Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada.
  • Ashbolt NJ; Faculty of Science and Engineering, Southern Cross University, East Lismore NSW 2480, Australia.
  • Talbot J; Department of Medicine, University of Alberta, Edmonton, AB T6G 2G3, Canada.
  • Hrudey SE; Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada.
  • Pang X; Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada; Provincial Laboratory for Public Health, Edmonton, Alberta, Canada. Electronic address: xiao-li.pang@albertaprecisionlabs.ca.
J Environ Sci (China) ; 125: 843-850, 2023 Mar.
Article in English | MEDLINE | ID: covidwho-1819537
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.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Observational study Limits: Humans Country/Region as subject: North America Language: English Journal: J Environ Sci (China) Journal subject: Environmental Health Year: 2023 Document Type: Article Affiliation country: J.jes.2022.04.047

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Observational study Limits: Humans Country/Region as subject: North America Language: English Journal: J Environ Sci (China) Journal subject: Environmental Health Year: 2023 Document Type: Article Affiliation country: J.jes.2022.04.047