SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.
Convolution model
Foreshadow
Longitudinal
SARS-CoV-2
Viral shedding
Wastewater surveillance
Journal
The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500
Informations de publication
Date de publication:
20 Jan 2022
20 Jan 2022
Historique:
received:
19
06
2021
revised:
30
08
2021
accepted:
31
08
2021
pubmed:
18
9
2021
medline:
25
11
2021
entrez:
17
9
2021
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 34534872
pii: S0048-9697(21)05196-2
doi: 10.1016/j.scitotenv.2021.150121
pmc: PMC8416286
pii:
doi:
Substances chimiques
RNA, Viral
0
Waste Water
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
150121Subventions
Organisme : NIDA NIH HHS
ID : K23 DA044874
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI106786
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM130668
Pays : United States
Organisme : NIDA NIH HHS
ID : R44 DA051106
Pays : United States
Informations de copyright
Copyright © 2021. Published by Elsevier B.V.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: 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.
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