Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020

Fuqing Wu¹, Amy Xiao¹, Jianbo Zhang¹, Katya Moniz¹, Noriko Endo², Federica Armas³, Mary Bushman⁴, Peter R Chai⁵, Claire Duvallet², Timothy B Erickson⁶, Katelyn Foppe², Newsha Ghaeli², Xiaoqiong Gu³, William P Hanage⁴, Katherine H Huang⁷, Wei Lin Lee³, Kyle A McElroy², Steven F Rhode⁸, Mariana Matus², Stefan Wuertz⁹, Janelle Thompson¹⁰, Eric J Alm¹¹

Affiliations

¹ Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
² Biobot Analytics, Inc., Cambridge, MA, USA.
³ Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore.
⁴ Harvard T.H. Chan School of Public Health, Harvard University, USA.
⁵ Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, USA; The Fenway Institute, Fenway Health, Boston, MA, USA.
⁶ Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, USA; The Koch Institute for Integrated Cancer Research, Massachusetts Institute of Technology, USA; Harvard Humanitarian Initiative, Harvard University.
⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Massachusetts Water Resources Authority, Boston, MA, USA.
⁹ Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Civil and Environmental Engineering, Nanyang Technological University, Singapore.
¹⁰ Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore.
¹¹ Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: ejalm@mit.edu.

PMID: 34274898
PMCID: PMC8249441
DOI: 10.1016/j.watres.2021.117400

Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020

Fuqing Wu et al. Water Res. 2021.

. 2021 Sep 1:202:117400.

doi: 10.1016/j.watres.2021.117400. Epub 2021 Jul 2.

Authors

Affiliations

¹ Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
² Biobot Analytics, Inc., Cambridge, MA, USA.
³ Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore.
⁴ Harvard T.H. Chan School of Public Health, Harvard University, USA.
⁵ Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, USA; The Fenway Institute, Fenway Health, Boston, MA, USA.
⁶ Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, USA; The Koch Institute for Integrated Cancer Research, Massachusetts Institute of Technology, USA; Harvard Humanitarian Initiative, Harvard University.
⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Massachusetts Water Resources Authority, Boston, MA, USA.
⁹ Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Civil and Environmental Engineering, Nanyang Technological University, Singapore.
¹⁰ Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore; Asian School of the Environment, Nanyang Technological University, Singapore.
¹¹ Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Singapore-MIT Alliance for Research and Technology, Antimicrobial Resistance Interdisciplinary Research Group, Singapore; Campus for Research Excellence and Technological Enterprise (CREATE), Singapore; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: ejalm@mit.edu.

PMID: 34274898
PMCID: PMC8249441
DOI: 10.1016/j.watres.2021.117400

Abstract

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

Keywords: Detection rate; SARS-CoV-2; Spatiotemporal dynamics; United States; Wastewater surveillance.

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Conflict of interest statement

MM and NG are cofounders of Biobot Analytics. EJA is advisor to Biobot Analytics. CD, KAM, KF, and NE are employees at Biobot Analytics, and all these authors hold shares in the company. PRC and TBE have a financial interest in Biobot Analytics, a company engaged in the collection and analysis of wastewater to develop epidemiological data. PRC and TBE’s interests were reviewed and are managed by Brigham and Women’s Hospital and Mass General Brigham in accordance with their conflict of interest policies.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image, graphical abstract — **Graphical abstract**

Fig 1 — **Fig. 1**
**SARS-CoV-2 RNA gene copies in wastewater samples from 40 U.S. states.** (a) Temporal profile of SARS-CoV-2 viral RNA gene copies (viral titers) in the wastewater samples collected from February 18 to June 2, 2020. Each grey point represents a sample, and the grey line connects samples collected from the same catchment. Temporal dynamics of mean viral titers from five U.S. states are highlighted. Negative samples (SARS-CoV-2 not detected) were assigned to ‘0’. (b-c) Mean viral titers for each state in April (b) and May (c). All the samples in April or May were aggregated by state. NA: data is not available for the state. (d) Temporal dynamics for the mean viral titers, daily new COVID-19 cases, and new deaths. Viral concentrations (red line) from positive wastewater samples were aggregated by date, and new cases (green line) and COVID-19-related new deaths (blue line) from the wastewater sample originated counties were also aggregated and averaged by date. (e) Association between viral titers in wastewater samples and the reported daily incidence rate in each sampled counties. (f) Association between the total viral load and estimated new cases in each of the catchment areas. Total viral load of SARS-CoV-2 in wastewater (copies/day) was calculated by multiplying SARS-CoV-2 concentration (copies/ml) by the daily average influent flow (ml/day) reported by the WWTP. Population weighted new cases was calculated as county new cases * catchment population / county population. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig 2 — **Fig. 2**
**Detection rate and accuracy of wastewater-based SARS-CoV-2 surveillance.** (a) Detection rate for varying daily incidence of COVID-19 cases. Each dot represents the percentage of positive wastewater samples for a constant incidence interval, and the red line is the nonlinear fit. The vertical dashed line indicates the incidence (x = 13) above which the fitted detection rate exceeds 0.8. (b) The distribution of daily incidence for the counties where SARS-CoV-2 was detected in the wastewater samples. Blue line is the Kernel density estimation of the daily incidence's distribution. The median of the incidence is 3.7 cases per 100,000 people). (c) Relationship between the detection rate of positive wastewater samples from a given treatment plant and the population size served by that plant. Detection rate is binned by population size, and colored by the incidence intervals. (d) Detection status for all the samples (n = 1,687). Wx.Cx (x = 1 or 0): consistent results between wastewater data and clinical reports. W1.C1: SARS-CoV-2 detected in Wastewater (W1) and new Clinical cases reported (C1); W0.C0: no Wastewater detection (W0) and no new Clinical cases reported (C0); W0.C1: no Wastewater detection (W0) but new Clinical cases reported (C1); W1.C0: Wastewater detection (W1) but no new Clinical cases reported (C0). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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Update of

Wastewater Surveillance of SARS-CoV-2 across 40 U.S. states.
Wu F, Xiao A, Zhang J, Moniz K, Endo N, Armas F, Bushman M, Chai PR, Duvallet C, Erickson TB, Foppe K, Ghaeli N, Gu X, Hanage WP, Huang KH, Lee WL, Matus M, McElroy KA, Rhode SF, Wuertz S, Thompson J, Alm EJ. Wu F, et al. medRxiv [Preprint]. 2021 Mar 14:2021.03.10.21253235. doi: 10.1101/2021.03.10.21253235. medRxiv. 2021. Update in: Water Res. 2021 Sep 1;202:117400. doi: 10.1016/j.watres.2021.117400. PMID: 33758888 Free PMC article. Updated. Preprint.

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Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020

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Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020

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