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...

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Main Authors: 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.
Other Authors: Asian School of the Environment
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/162600
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spelling sg-ntu-dr.10356-1626002022-11-05T23:32:01Z 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. Asian School of the Environment Campus for Research Excellence and Technological Enterprise (CREATE), Singapore Singapore Centre for Environmental Life Sciences and Engineering (SCELSE) Engineering::Environmental engineering Wastewater Surveillance Wastewater-Based Epidemiology 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. National Research Foundation (NRF) Published version This work was supported by the Center for Microbiome Informatics and Therapeutics and Intra-CREATE Thematic Grant (Cities) grant NRF2019-THE001–0003a to JT and EJA; National Institute on Drug Abuse of the National Institutes of Health award numbers K23DA044874 to PRC; and R44DA051106 to MM and PRC, Hans and Mavis Psychosocial Foundation funding, and e-ink corporation funding to PRC; funding from the Morris-Singer Foundation and NIH award R01AI106786 to WPH; funds from the Massachusetts Consortium on Pathogen Readiness and China Evergrande Group to TBE, PRC, MM, and EJA. 2022-11-01T01:25:37Z 2022-11-01T01:25:37Z 2022 Journal Article Xiao, A., Wu, F., Bushman, M., Zhang, J., Imakaev, M., Chai, P. R., Duvallet, C., Endo, N., Erickson, T. B., Armas, F., Arnold, B., Chen, H., Chandra, F., Ghaeli, N., Gu, X., Hanage, W. P., Lee, W. L., Matus, M., McElroy, K. A., ...Alm, E. J. (2022). Metrics to relate COVID-19 wastewater data to clinical testing dynamics. Water Research, 212, 118070-. https://dx.doi.org/10.1016/j.watres.2022.118070 0043-1354 https://hdl.handle.net/10356/162600 10.1016/j.watres.2022.118070 35101695 2-s2.0-85123608105 212 118070 en NRF2019-THE001-0003a Water Research © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Environmental engineering
Wastewater Surveillance
Wastewater-Based Epidemiology
spellingShingle Engineering::Environmental engineering
Wastewater Surveillance
Wastewater-Based Epidemiology
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
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.
author2 Asian School of the Environment
author_facet Asian School of the Environment
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.
format Article
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_sort Xiao, Amy
title 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_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_sort metrics to relate covid-19 wastewater data to clinical testing dynamics
publishDate 2022
url https://hdl.handle.net/10356/162600
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