@article{9b6a998fa94c45f69f86e58e17e6b2cc,
title = "SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases",
abstract = "Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we quantify the SARS-CoV-2 concentration and track its dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4–10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral load as a convolution of back-dated new clinical cases with the average population-level viral shedding function. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. This finding suggests that SARS-CoV-2 concentrations in wastewater may be primarily driven by viral shedding early in infection. This work shows that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and infer early viral shedding dynamics for newly infected individuals, which are difficult to capture in clinical investigations.",
keywords = "Convolution model, Foreshadow, Longitudinal, SARS-CoV-2, Viral shedding, Wastewater surveillance",
author = "Fuqing Wu and Amy Xiao and Jianbo Zhang and Katya Moniz and Noriko Endo and Federica Armas and Richard Bonneau and Brown, {Megan A.} and Mary Bushman and Chai, {Peter R.} and Claire Duvallet and Erickson, {Timothy B.} and Katelyn Foppe and Newsha Ghaeli and Xiaoqiong Gu and Hanage, {William P.} and Huang, {Katherine H.} and Lee, {Wei Lin} and Mariana Matus and McElroy, {Kyle A.} and Jonathan Nagler and Rhode, {Steven F.} and Mauricio Santillana and Tucker, {Joshua A.} and Stefan Wuertz and Shijie Zhao and Janelle Thompson and Alm, {Eric J.}",
note = "Funding Information: We thank the management and sampling team at the Massachusetts wastewater treatment facility who worked with us in providing the samples for analysis, in particular Conor Donovan, Jim Fitzgerald, Louis Logan, Nicole Mangano, Keith Stocks, Sean Winter, and David Wu. We thank Lisa Wong (MWRA) for providing flow data, and Stephen Estes-Smargiassi (MWRA) and Betsy Reilley (MWRA) for helpful discussion. We thank Penny Chisholm (MIT) and Allison Coe (MIT) for access to equipment and other supplies, Mathilde Poyet (MIT) and Shandrina Burns (MIT) for logistical support, Andrew Tang (Broad Institute) for assistance with Fig. 2, Nicholas Santos-Powell for thoughtful comments on the manuscript, Kyle Bibby (University of Notre Dame) for suggestions on PMMoV, and Karina Gin (National University of Singapore) and Lee Ching Ng (National Environmental Agency, Singapore) for helpful discussion and for sharing the Amicon protocol. We also thank Dr. Victor M. Corman (Charit? Universit?tsmedizin, Germany) for sharing data of viral concentrations in patients' stool samples, and the SafeGraph team for providing free access to their data for COVID-19-related research. Finally, we express our deep gratitude to all healthcare professionals and first-line responders who have been caring for patients with COVID-19. 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; 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; funding from the Ministry of Education - Singapore and National Research Foundation through an RCE award to Singapore Centre for Environmental Life Sciences Engineering (SCELSE) to SW and JT; and a National Institute of General Medical Sciences of the National Institutes of Health award, number R01GM130668, to MS. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding institutions. Funding Information: 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 ; 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; funding from the Ministry of Education - Singapore and National Research Foundation through an RCE award to Singapore Centre for Environmental Life Sciences Engineering (SCELSE) to SW and JT; and a National Institute of General Medical Sciences of the National Institutes of Health award, number R01GM130668 , to MS. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding institutions. Publisher Copyright: {\textcopyright} 2021",
year = "2022",
month = jan,
day = "20",
doi = "10.1016/j.scitotenv.2021.150121",
language = "English (US)",
volume = "805",
journal = "Science of the Total Environment",
issn = "0048-9697",
publisher = "Elsevier",
}