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Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19

Wastewater-based epidemiology (WBE) has emerged as a useful tool in the fight to track and contain COVID-19 spread within communities. One of the motives behind COVID-19 WBE efforts is the potential for ‘early warning’ of either the onset of disease in a new setting or changes in trends in communiti...

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Autores principales: Bibby, Kyle, Bivins, Aaron, Wu, Zhenyu, North, Devin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8274973/
https://www.ncbi.nlm.nih.gov/pubmed/34333296
http://dx.doi.org/10.1016/j.watres.2021.117438
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author Bibby, Kyle
Bivins, Aaron
Wu, Zhenyu
North, Devin
author_facet Bibby, Kyle
Bivins, Aaron
Wu, Zhenyu
North, Devin
author_sort Bibby, Kyle
collection PubMed
description Wastewater-based epidemiology (WBE) has emerged as a useful tool in the fight to track and contain COVID-19 spread within communities. One of the motives behind COVID-19 WBE efforts is the potential for ‘early warning’ of either the onset of disease in a new setting or changes in trends in communities where disease is endemic. Many initial reports of the early warning potential of WBE have relied upon retrospective sample analysis, and delays in WBE analysis and reporting should be considered when evaluating the early warning potential of WBE that enable public health action. Our purpose in this manuscript is to establish a framework to critique the potential of WBE to serve as an early warning system, with special attention to the onset of viral shedding and the differential between results reporting for WBE and clinical testing. While many uncertainties remain regarding both COVID-19 clinical presentation and technical factors influencing WBE results, our analysis suggests at most a modest lead time interval ranging from six days for clinical testing to four days for WBE during community-level wastewater surveillance where clinical testing is accessible on-demand with a rapid time to results. This potential lead time for WBE subsequently increases in settings with limited clinical testing capacity or utilization. Care should be taken when reporting ‘early detection’ of COVID-19 disease trends via WBE to consider underlying causes (e.g., clinical testing lag or delayed result reporting) to avoid misrepresenting WBE potential.
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spelling pubmed-82749732021-07-20 Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19 Bibby, Kyle Bivins, Aaron Wu, Zhenyu North, Devin Water Res Making Waves Wastewater-based epidemiology (WBE) has emerged as a useful tool in the fight to track and contain COVID-19 spread within communities. One of the motives behind COVID-19 WBE efforts is the potential for ‘early warning’ of either the onset of disease in a new setting or changes in trends in communities where disease is endemic. Many initial reports of the early warning potential of WBE have relied upon retrospective sample analysis, and delays in WBE analysis and reporting should be considered when evaluating the early warning potential of WBE that enable public health action. Our purpose in this manuscript is to establish a framework to critique the potential of WBE to serve as an early warning system, with special attention to the onset of viral shedding and the differential between results reporting for WBE and clinical testing. While many uncertainties remain regarding both COVID-19 clinical presentation and technical factors influencing WBE results, our analysis suggests at most a modest lead time interval ranging from six days for clinical testing to four days for WBE during community-level wastewater surveillance where clinical testing is accessible on-demand with a rapid time to results. This potential lead time for WBE subsequently increases in settings with limited clinical testing capacity or utilization. Care should be taken when reporting ‘early detection’ of COVID-19 disease trends via WBE to consider underlying causes (e.g., clinical testing lag or delayed result reporting) to avoid misrepresenting WBE potential. Published by Elsevier Ltd. 2021-09-01 2021-07-12 /pmc/articles/PMC8274973/ /pubmed/34333296 http://dx.doi.org/10.1016/j.watres.2021.117438 Text en © 2021 Published by Elsevier Ltd. 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 Making Waves
Bibby, Kyle
Bivins, Aaron
Wu, Zhenyu
North, Devin
Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19
title Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19
title_full Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19
title_fullStr Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19
title_full_unstemmed Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19
title_short Making waves: Plausible lead time for wastewater based epidemiology as an early warning system for COVID-19
title_sort making waves: plausible lead time for wastewater based epidemiology as an early warning system for covid-19
topic Making Waves
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8274973/
https://www.ncbi.nlm.nih.gov/pubmed/34333296
http://dx.doi.org/10.1016/j.watres.2021.117438
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