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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
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-Co...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8697423/ https://www.ncbi.nlm.nih.gov/pubmed/34954186 http://dx.doi.org/10.1016/j.scitotenv.2021.152503 |
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author | 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 |
author_facet | 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 |
author_sort | Barua, Visva Bharati |
collection | PubMed |
description | 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 10(3) to 10(5) 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. |
format | Online Article Text |
id | pubmed-8697423 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-86974232021-12-23 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 Sci Total Environ Article 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 10(3) to 10(5) 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. Elsevier 2022-03-25 2021-12-23 /pmc/articles/PMC8697423/ /pubmed/34954186 http://dx.doi.org/10.1016/j.scitotenv.2021.152503 Text en Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article 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 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 |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8697423/ https://www.ncbi.nlm.nih.gov/pubmed/34954186 http://dx.doi.org/10.1016/j.scitotenv.2021.152503 |
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