Metrics to relate COVID-19 wastewater data to clinical testing dynamics

被引：64

作者：

Xiao, Amy ^{[1
,2
]}

Wu, Fuqing ^{[1
,2
]}

Bushman, Mary ^{[3
]}

Zhang, Jianbo ^{[1
,2
]}

Imakaev, Maxim ^{[4
]}

Chai, Peter R. ^{[5
,6
,7
,8
]}

Duvallet, Claire ^{[4
]}

Endo, Noriko ^{[4
]}

Erickson, Timothy B. ^{[5
,9
]}

Armas, Federica ^{[11
]}

Arnold, Brian ^{[12
,13
]}

Chen, Hongjie ^{[11
]}

Chandra, Franciscus ^{[11
]}

Ghaeli, Newsha ^{[4
]}

Gu, Xiaoqiong ^{[10
,11
]}

Hanage, William P. ^{[3
]}

Lee, Wei Lin ^{[10
,11
]}

Matus, Mariana ^{[4
]}

McElroy, Kyle A. ^{[4
]}

Moniz, Katya ^{[1
,2
]}

Rhode, Steven F. ^{[14
]}

Thompson, Janelle ^{[15
,16
]}

Alm, Eric J. ^{[1
,2
,10
,11
,17
]}

机构：

[1] MIT, Dept Biol Engn, Cambridge, MA 02139 USA

[2] MIT, Ctr Microbiome Informat & Therapeut, Cambridge, MA 02139 USA

[3] Harvard Univ, Harvard TH Chan Sch Publ Hlth, Cambridge, MA 02138 USA

[4] Biobot Analyt Inc, Cambridge, MA USA

[5] Harvard Med Sch, Brigham & Womens Hosp, Dept Emergency Med, Div Med Toxicol, Boston, MA 02115 USA

[6] Fenway Inst, Fenway Hlth, Boston, MA USA

[7] MIT, Koch Inst Integrated Canc Res, Cambridge, MA 02139 USA

[8] Dana Farber Canc Inst, Dept Psychosocial Oncol & Palliat Care, Boston, MA USA

[9] Harvard Univ, Harvard Humanitarian Initiat, Cambridge, MA 02138 USA

[10] Singapore MIT Alliance Res & Technol, Antimicrobial Resistance Interdisciplinary Res Gr, Singapore, Singapore

[11] Campus Res Excellence & Technol Enterprise CREATE, Singapore, Singapore

[12] Princeton Univ, Dept Comp Sci, Princeton, NJ 08544 USA

[13] Princeton Univ, Ctr Stat & Machine Learning, Princeton, NJ 08544 USA

[14] Massachusetts Water Resources Author, Boston, MA USA

[15] Nanyang Technol Univ, Singapore Ctr Environm Life Sci Engn, Singapore, Singapore

[16] Nanyang Technol Univ, Asian Sch Environm, Singapore, Singapore

[17] Broad Inst MIT & Harvard, Cambridge, MA 02142 USA

来源：

WATER RESEARCH | 2022年 / 212卷

基金：

美国国家卫生研究院;

关键词：

Wastewater surveillance; Wastewater-based epidemiology; SARS-CoV-2; Temporal dynamics; B.1.1.7;

D O I：

10.1016/j.watres.2022.118070

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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 dy-namics, 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.

引用

页数：13

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