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Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: A six-month long study in Charlotte, North Carolina.
Barua, Visva Bharati; Juel, Md Ariful Islam; Blackwood, A Denene; Clerkin, Thomas; Ciesielski, Mark; Sorinolu, Adeola Julian; Holcomb, David A; Young, Isaiah; Kimble, Gina; Sypolt, Shannon; Engel, Lawrence S; Noble, Rachel T; Munir, Mariya.
Afiliação
  • Barua VB; Department of Civil and Environmental Engineering, University of North Carolina Charlotte, 9201 University City Boulevard, Charlotte, NC 28223, USA.
  • Juel MAI; Department of Civil and Environmental Engineering, University of North Carolina Charlotte, 9201 University City Boulevard, Charlotte, NC 28223, USA.
  • Blackwood AD; Institute of Marine Sciences, The University of North Carolina at Chapel Hill, Morehead City, NC 28557, USA.
  • Clerkin T; Institute of Marine Sciences, The University of North Carolina at Chapel Hill, Morehead City, NC 28557, USA.
  • Ciesielski M; Institute of Marine Sciences, The University of North Carolina at Chapel Hill, Morehead City, NC 28557, USA.
  • Sorinolu AJ; Department of Civil and Environmental Engineering, University of North Carolina Charlotte, 9201 University City Boulevard, Charlotte, NC 28223, USA.
  • Holcomb DA; Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Young I; Department of Civil and Environmental Engineering, University of North Carolina Charlotte, 9201 University City Boulevard, Charlotte, NC 28223, USA.
  • Kimble G; Charlotte Water, 5100 Brookshire Blvd., Charlotte, NC 28216, USA.
  • Sypolt S; Charlotte Water, 5100 Brookshire Blvd., Charlotte, NC 28216, USA.
  • Engel LS; Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Noble RT; Institute of Marine Sciences, The University of North Carolina at Chapel Hill, Morehead City, NC 28557, USA.
  • Munir M; Department of Civil and Environmental Engineering, University of North Carolina Charlotte, 9201 University City Boulevard, Charlotte, NC 28223, USA. Electronic address: mmunir@uncc.edu.
Sci Total Environ ; 814: 152503, 2022 Mar 25.
Article em En | MEDLINE | ID: mdl-34954186
The global spread of SARS-CoV-2 has continued to be a serious concern after WHO declared the virus to be the causative agent of the coronavirus disease 2019 (COVID-19) a global pandemic. Monitoring of wastewater is a useful tool for assessing community prevalence given that fecal shedding of SARS-CoV-2 occurs in high concentrations by infected individuals, regardless of whether they are asymptomatic or symptomatic. Using tools that are part of wastewater-based epidemiology (WBE) approach, combined with molecular analyses, wastewater monitoring becomes a key piece of information used to assess trends and quantify the scale and dynamics of COVID-19 infection in a specific community, municipality, or area of service. This study investigates a six-month long SARS-CoV-2 RNA quantification in influent wastewater from four municipal wastewater treatment plants (WWTP) serving the Charlotte region of North Carolina (NC) using both RT-qPCR and RT-ddPCR platforms. Influent wastewater was analyzed for the nucleocapsid (N) genes N1 and N2. Both RT-qPCR and RT-ddPCR performed well for detection and quantification of SARS-CoV-2 using the N1 target, while for the N2 target RT-ddPCR was more sensitive. SARS-CoV-2 concentration ranged from 103 to 105 copies/L for all four plants. Both RT-qPCR and RT-ddPCR showed a significant positive correlation between SARS-CoV-2 concentrations and the 7-day rolling average of clinically reported COVID-19 cases when lagging 5 to 12 days (ρ = 0.52-0.92, p < 0.001-0.02). A major finding of this study is that RT-qPCR and RT-ddPCR generated SARS-CoV-2 data that was positively correlated (ρ = 0.569, p < 0.0001) and can be successfully used to monitor SARS-CoV-2 signals across the WWTP of different sizes and metropolitan service functions without significant anomalies.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Risk_factors_studies / Screening_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Risk_factors_studies / Screening_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2022 Tipo de documento: Article