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Wastewater, waste, and water-based epidemiology (WWW-BE): A novel hypothesis and decision-support tool to unravel COVID-19 in low-income settings?
Traditional wastewater-based epidemiology (W-BE) relying on SARS-CoV-2 RNA detection in wastewater is attractive for understanding COVID-19. Yet traditional W-BE based on centralized wastewaters excludes putative SARS-CoV-2 reservoirs such as: (i) wastewaters from shared on-site sanitation facilitie...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Elsevier B.V.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481624/ https://www.ncbi.nlm.nih.gov/pubmed/34599955 http://dx.doi.org/10.1016/j.scitotenv.2021.150680 |
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author | Gwenzi, Willis |
author_facet | Gwenzi, Willis |
author_sort | Gwenzi, Willis |
collection | PubMed |
description | Traditional wastewater-based epidemiology (W-BE) relying on SARS-CoV-2 RNA detection in wastewater is attractive for understanding COVID-19. Yet traditional W-BE based on centralized wastewaters excludes putative SARS-CoV-2 reservoirs such as: (i) wastewaters from shared on-site sanitation facilities, (ii) solid waste including faecal sludge from non-flushing on-site sanitation systems, and COVID-19 personal protective equipment (PPE), (iii) raw/untreated water, and (iv) drinking water supply systems in low-income countries (LICs). A novel hypothesis and decision-support tool based on Wastewater (on-site sanitation, municipal sewer systems), solid Waste, and raw/untreated and drinking Water-based epidemiology (WWW-BE) is proposed for understanding COVID-19 in LICs. The WWW-BE conceptual framework, including components and principles is presented. Evidence on the presence of SARS-CoV-2 and its proxies in wastewaters, solid materials/waste (papers, metals, fabric, plastics), and raw/untreated surface water, groundwater and drinking water is discussed. Taken together, wastewaters from municipal sewer and on-site sanitation systems, solid waste such as faecal sludge and COVID-19 PPE, raw/untreated surface water and groundwater, and drinking water systems in LICs act as potential reservoirs that receive and harbour SARS-CoV-2, and then transmit it to humans. Hence, WWW-BE could serve a dual function in estimating the prevalence and potential transmission of COVID-19. Several applications of WWW-BE as a hypothesis and decision support tool in LICs are discussed. WWW-BE aggregates data from various infected persons in a spatial unit, hence, putatively requires less resources (analytical kits, personnel) than individual diagnostic testing, making it an ideal decision-support tool for LICs. The novelty, and a critique of WWW-BE versus traditional W-BE are presented. Potential challenges of WWW-BE include: (i) biohazards and biosafety risks, (ii) lack of expertise, analytical equipment, and accredited laboratories, and (iii) high uncertainties in estimates of COVID-19 cases. Future perspectives and research directions including key knowledge gaps and the application of novel and emerging technologies in WWW-BE are discussed. |
format | Online Article Text |
id | pubmed-8481624 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84816242021-09-30 Wastewater, waste, and water-based epidemiology (WWW-BE): A novel hypothesis and decision-support tool to unravel COVID-19 in low-income settings? Gwenzi, Willis Sci Total Environ Review Traditional wastewater-based epidemiology (W-BE) relying on SARS-CoV-2 RNA detection in wastewater is attractive for understanding COVID-19. Yet traditional W-BE based on centralized wastewaters excludes putative SARS-CoV-2 reservoirs such as: (i) wastewaters from shared on-site sanitation facilities, (ii) solid waste including faecal sludge from non-flushing on-site sanitation systems, and COVID-19 personal protective equipment (PPE), (iii) raw/untreated water, and (iv) drinking water supply systems in low-income countries (LICs). A novel hypothesis and decision-support tool based on Wastewater (on-site sanitation, municipal sewer systems), solid Waste, and raw/untreated and drinking Water-based epidemiology (WWW-BE) is proposed for understanding COVID-19 in LICs. The WWW-BE conceptual framework, including components and principles is presented. Evidence on the presence of SARS-CoV-2 and its proxies in wastewaters, solid materials/waste (papers, metals, fabric, plastics), and raw/untreated surface water, groundwater and drinking water is discussed. Taken together, wastewaters from municipal sewer and on-site sanitation systems, solid waste such as faecal sludge and COVID-19 PPE, raw/untreated surface water and groundwater, and drinking water systems in LICs act as potential reservoirs that receive and harbour SARS-CoV-2, and then transmit it to humans. Hence, WWW-BE could serve a dual function in estimating the prevalence and potential transmission of COVID-19. Several applications of WWW-BE as a hypothesis and decision support tool in LICs are discussed. WWW-BE aggregates data from various infected persons in a spatial unit, hence, putatively requires less resources (analytical kits, personnel) than individual diagnostic testing, making it an ideal decision-support tool for LICs. The novelty, and a critique of WWW-BE versus traditional W-BE are presented. Potential challenges of WWW-BE include: (i) biohazards and biosafety risks, (ii) lack of expertise, analytical equipment, and accredited laboratories, and (iii) high uncertainties in estimates of COVID-19 cases. Future perspectives and research directions including key knowledge gaps and the application of novel and emerging technologies in WWW-BE are discussed. Elsevier B.V. 2022-02-01 2021-09-30 /pmc/articles/PMC8481624/ /pubmed/34599955 http://dx.doi.org/10.1016/j.scitotenv.2021.150680 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 | Review Gwenzi, Willis Wastewater, waste, and water-based epidemiology (WWW-BE): A novel hypothesis and decision-support tool to unravel COVID-19 in low-income settings? |
title | Wastewater, waste, and water-based epidemiology (WWW-BE): A novel hypothesis and decision-support tool to unravel COVID-19 in low-income settings? |
title_full | Wastewater, waste, and water-based epidemiology (WWW-BE): A novel hypothesis and decision-support tool to unravel COVID-19 in low-income settings? |
title_fullStr | Wastewater, waste, and water-based epidemiology (WWW-BE): A novel hypothesis and decision-support tool to unravel COVID-19 in low-income settings? |
title_full_unstemmed | Wastewater, waste, and water-based epidemiology (WWW-BE): A novel hypothesis and decision-support tool to unravel COVID-19 in low-income settings? |
title_short | Wastewater, waste, and water-based epidemiology (WWW-BE): A novel hypothesis and decision-support tool to unravel COVID-19 in low-income settings? |
title_sort | wastewater, waste, and water-based epidemiology (www-be): a novel hypothesis and decision-support tool to unravel covid-19 in low-income settings? |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481624/ https://www.ncbi.nlm.nih.gov/pubmed/34599955 http://dx.doi.org/10.1016/j.scitotenv.2021.150680 |
work_keys_str_mv | AT gwenziwillis wastewaterwasteandwaterbasedepidemiologywwwbeanovelhypothesisanddecisionsupporttooltounravelcovid19inlowincomesettings |