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Metrics to relate COVID-19 wastewater data to clinical testing dynamics
Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the co...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758950/ https://www.ncbi.nlm.nih.gov/pubmed/35101695 http://dx.doi.org/10.1016/j.watres.2022.118070 |
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author | Xiao, Amy Wu, Fuqing Bushman, Mary Zhang, Jianbo Imakaev, Maxim Chai, Peter R Duvallet, Claire Endo, Noriko Erickson, Timothy B Armas, Federica Arnold, Brian Chen, Hongjie Chandra, Franciscus Ghaeli, Newsha Gu, Xiaoqiong Hanage, William P Lee, Wei Lin Matus, Mariana McElroy, Kyle A Moniz, Katya Rhode, Steven F Thompson, Janelle Alm, Eric J |
author_facet | Xiao, Amy Wu, Fuqing Bushman, Mary Zhang, Jianbo Imakaev, Maxim Chai, Peter R Duvallet, Claire Endo, Noriko Erickson, Timothy B Armas, Federica Arnold, Brian Chen, Hongjie Chandra, Franciscus Ghaeli, Newsha Gu, Xiaoqiong Hanage, William P Lee, Wei Lin Matus, Mariana McElroy, Kyle A Moniz, Katya Rhode, Steven F Thompson, Janelle Alm, Eric J |
author_sort | Xiao, Amy |
collection | PubMed |
description | Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics. |
format | Online Article Text |
id | pubmed-8758950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Authors. Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87589502022-01-14 Metrics to relate COVID-19 wastewater data to clinical testing dynamics Xiao, Amy Wu, Fuqing Bushman, Mary Zhang, Jianbo Imakaev, Maxim Chai, Peter R Duvallet, Claire Endo, Noriko Erickson, Timothy B Armas, Federica Arnold, Brian Chen, Hongjie Chandra, Franciscus Ghaeli, Newsha Gu, Xiaoqiong Hanage, William P Lee, Wei Lin Matus, Mariana McElroy, Kyle A Moniz, Katya Rhode, Steven F Thompson, Janelle Alm, Eric J Water Res Article Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics. The Authors. Published by Elsevier Ltd. 2022-04-01 2022-01-14 /pmc/articles/PMC8758950/ /pubmed/35101695 http://dx.doi.org/10.1016/j.watres.2022.118070 Text en © 2022 The Authors. 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 | Article Xiao, Amy Wu, Fuqing Bushman, Mary Zhang, Jianbo Imakaev, Maxim Chai, Peter R Duvallet, Claire Endo, Noriko Erickson, Timothy B Armas, Federica Arnold, Brian Chen, Hongjie Chandra, Franciscus Ghaeli, Newsha Gu, Xiaoqiong Hanage, William P Lee, Wei Lin Matus, Mariana McElroy, Kyle A Moniz, Katya Rhode, Steven F Thompson, Janelle Alm, Eric J Metrics to relate COVID-19 wastewater data to clinical testing dynamics |
title | Metrics to relate COVID-19 wastewater data to clinical testing dynamics |
title_full | Metrics to relate COVID-19 wastewater data to clinical testing dynamics |
title_fullStr | Metrics to relate COVID-19 wastewater data to clinical testing dynamics |
title_full_unstemmed | Metrics to relate COVID-19 wastewater data to clinical testing dynamics |
title_short | Metrics to relate COVID-19 wastewater data to clinical testing dynamics |
title_sort | metrics to relate covid-19 wastewater data to clinical testing dynamics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758950/ https://www.ncbi.nlm.nih.gov/pubmed/35101695 http://dx.doi.org/10.1016/j.watres.2022.118070 |
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