Evidence map›Paper›PMID 36380771›Full record

ArticleACS ES&T water2022

Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States.

Claire Duvallet, Fuqing Wu, Kyle A McElroy, Maxim Imakaev, Noriko Endo, Amy Xiao, Jianbo Zhang, Róisín Floyd-O'Sullivan, Morgan M Powell, Samuel Mendola and 10 more

Abstract read
In one paragraph

Article in ACS ES&T water, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed.

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  6. Coupling wastewater-based epidemiology with data-driven machine learning for managing public health risks.Risk analysis : an official publication of the Society for Risk Analysis · 2025
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  16. Inferring COVID-19 testing and vaccination behavior from New Jersey testing data.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Claire DuvalletBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.ORCID https://orcid.org/0000-0002-8093-8394
Fuqing WuCenter for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
Kyle A McElroyBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Maxim ImakaevBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Noriko EndoBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Amy XiaoCenter for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
Jianbo ZhangCenter for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.ORCID https://orcid.org/0000-0003-3526-4586
Róisín Floyd-O'SullivanBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Morgan M PowellBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Samuel MendolaBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Shane T WilsonBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Francis CruzBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Tamar MelmanBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States.
Chaithra Lakshmi SathyanarayanaBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Scott W OlesenBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Timothy B EricksonDepartment of Emergency Medicine, Harvard Medical School, Boston, Massachusetts 02115, United States.
Newsha GhaeliBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Peter ChaiDivision of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02115, United States.
Eric J AlmBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.
Mariana MatusBiobot Analytics, Inc., Cambridge, Massachusetts 02139, United States.ORCID https://orcid.org/0000-0002-2880-0339

Funding

A novel robotic wastewater analysis system to quantify opioid exposure and treatment in residential communitiesR44DA051106 · NIDA · BIOBOT ANALYTICS, INC. · PI CHAI, PETER R, MATUS GARCIA, MARIANA G · 2020 to 2022
$1.5M
Development of Ingestible Biosensors to Enhance PrEP Adherence in Substance UsersK23DA044874 · NIDA · BRIGHAM AND WOMEN'S HOSPITAL · PI CHAI, PETER R · 2018 to 2022
$1.0M
NIDA NIH HHS K23 DA044874NIDA NIH HHS R44 DA051106
6 · The paper itself

Abstract

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.

Identifiers

PMID36380771
PMCPMC9092192

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.