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Monitoring changes in COVID-19 infection using wastewater-based epidemiology: A South African perspective
Monitoring of COVID-19 infections within communities via wastewater-based epidemiology could provide a cost-effective alternative to clinical testing. This approach, however, still requires improvement for its efficient application. In this paper, we present the use of wastewater-based epidemiology...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062404/ https://www.ncbi.nlm.nih.gov/pubmed/33965818 http://dx.doi.org/10.1016/j.scitotenv.2021.147273 |
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author | Pillay, Leanne Amoah, Isaac Dennis Deepnarain, Nashia Pillay, Kriveshin Awolusi, Oluyemi Olatunji Kumari, Sheena Bux, Faizal |
author_facet | Pillay, Leanne Amoah, Isaac Dennis Deepnarain, Nashia Pillay, Kriveshin Awolusi, Oluyemi Olatunji Kumari, Sheena Bux, Faizal |
author_sort | Pillay, Leanne |
collection | PubMed |
description | Monitoring of COVID-19 infections within communities via wastewater-based epidemiology could provide a cost-effective alternative to clinical testing. This approach, however, still requires improvement for its efficient application. In this paper, we present the use of wastewater-based epidemiology in monitoring COVID-19 infection dynamics in the KwaZulu-Natal province of South Africa, focusing on four wastewater treatment plants for 14 weeks. The SARS-CoV-2 viral load in influent wastewater was determined using droplet digital PCR, and the number of people infected was estimated using published models as well as using a modified model to improve efficiency. On average, viral loads ranged between 0 and 2.73 × 10(5) copies/100 ml, 0–1.52 × 10(5) copies/100 ml, 3 × 10(4)–7.32 × 10(5) copies/100 ml and 1.55 × 10(4)–4.12 × 10(5) copies/100 ml in the four wastewater treatment plants studied. The peak in viral load corresponded to the reported COVID-19 infections within the districts where these catchments are located. In addition, we also observed that easing of lockdown restrictions by authorities corresponded with an increase in viral load in the untreated wastewater. Estimation of infection numbers based on the viral load showed that a higher number of people could potentially be infected, compared to the number of cases reported based on clinical testing. The findings reported in this paper contribute to the field of wastewater-based epidemiology for COVID-19 surveillance, whilst highlighting some of the challenges associated with this approach, especially in developing countries. |
format | Online Article Text |
id | pubmed-8062404 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80624042021-04-23 Monitoring changes in COVID-19 infection using wastewater-based epidemiology: A South African perspective Pillay, Leanne Amoah, Isaac Dennis Deepnarain, Nashia Pillay, Kriveshin Awolusi, Oluyemi Olatunji Kumari, Sheena Bux, Faizal Sci Total Environ Article Monitoring of COVID-19 infections within communities via wastewater-based epidemiology could provide a cost-effective alternative to clinical testing. This approach, however, still requires improvement for its efficient application. In this paper, we present the use of wastewater-based epidemiology in monitoring COVID-19 infection dynamics in the KwaZulu-Natal province of South Africa, focusing on four wastewater treatment plants for 14 weeks. The SARS-CoV-2 viral load in influent wastewater was determined using droplet digital PCR, and the number of people infected was estimated using published models as well as using a modified model to improve efficiency. On average, viral loads ranged between 0 and 2.73 × 10(5) copies/100 ml, 0–1.52 × 10(5) copies/100 ml, 3 × 10(4)–7.32 × 10(5) copies/100 ml and 1.55 × 10(4)–4.12 × 10(5) copies/100 ml in the four wastewater treatment plants studied. The peak in viral load corresponded to the reported COVID-19 infections within the districts where these catchments are located. In addition, we also observed that easing of lockdown restrictions by authorities corresponded with an increase in viral load in the untreated wastewater. Estimation of infection numbers based on the viral load showed that a higher number of people could potentially be infected, compared to the number of cases reported based on clinical testing. The findings reported in this paper contribute to the field of wastewater-based epidemiology for COVID-19 surveillance, whilst highlighting some of the challenges associated with this approach, especially in developing countries. Elsevier B.V. 2021-09-10 2021-04-23 /pmc/articles/PMC8062404/ /pubmed/33965818 http://dx.doi.org/10.1016/j.scitotenv.2021.147273 Text en © 2021 Elsevier B.V. All rights reserved. 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 Pillay, Leanne Amoah, Isaac Dennis Deepnarain, Nashia Pillay, Kriveshin Awolusi, Oluyemi Olatunji Kumari, Sheena Bux, Faizal Monitoring changes in COVID-19 infection using wastewater-based epidemiology: A South African perspective |
title | Monitoring changes in COVID-19 infection using wastewater-based epidemiology: A South African perspective |
title_full | Monitoring changes in COVID-19 infection using wastewater-based epidemiology: A South African perspective |
title_fullStr | Monitoring changes in COVID-19 infection using wastewater-based epidemiology: A South African perspective |
title_full_unstemmed | Monitoring changes in COVID-19 infection using wastewater-based epidemiology: A South African perspective |
title_short | Monitoring changes in COVID-19 infection using wastewater-based epidemiology: A South African perspective |
title_sort | monitoring changes in covid-19 infection using wastewater-based epidemiology: a south african perspective |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062404/ https://www.ncbi.nlm.nih.gov/pubmed/33965818 http://dx.doi.org/10.1016/j.scitotenv.2021.147273 |
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