SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases

Fuqing Wu, Amy Xiao, Jianbo Zhang, Katya Moniz, Noriko Endo, Federica Armas, Richard Bonneau, Megan A. Brown, Mary Bushman, Peter R. Chai, Claire Duvallet, Timothy B. Erickson, Katelyn Foppe, Newsha Ghaeli, Xiaoqiong Gu, William P. Hanage, Katherine H. Huang, Wei Lin Lee, Mariana Matus, Kyle A. McElroyJonathan Nagler, Steven F. Rhode, Mauricio Santillana, Joshua A. Tucker, Stefan Wuertz, Shijie Zhao, Janelle Thompson, Eric J. Alm

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number150121
JournalScience of the Total Environment
Volume805
DOIs
StatePublished - Jan 20 2022

Keywords

  • Convolution model
  • Foreshadow
  • Longitudinal
  • SARS-CoV-2
  • Viral shedding
  • Wastewater surveillance

ASJC Scopus subject areas

  • Environmental Engineering
  • Environmental Chemistry
  • Waste Management and Disposal
  • Pollution

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