Evidence map›Paper›PMID 39340381›Full record

ArticleJournal of water and health2024

Wastewater surveillance for antibiotic resistance genes during the late 2020 SARS-CoV-2 peak in two different populations.

Sarah E Philo, Sílvia Monteiro, Erica R Fuhrmeister, Ricardo Santos, John Scott Meschke

Abstract read
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In one paragraph

Article in Journal of water and health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Sarah E PhiloDepartment of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA.ORCID https://orcid.org/0000-0002-9894-0425
Sílvia MonteiroLaboratório de Análises, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal.
Erica R FuhrmeisterDepartment of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA.
Ricardo SantosLaboratório de Análises, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal.
John Scott MeschkeDepartment of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA E-mail: jmeschke@uw.edu.ORCID https://orcid.org/0000-0002-8983-9042

Funding

Biostatistics, Epidemiologic & Bioinformatic Training in Environmental HealthT32ES015459 · NIEHS · UNIVERSITY OF WASHINGTON · PI June T. Spector · 2009 to 2026
$10.6M
Fulbright U.S. Student ProgramFundação para a Ciência e Tecnologia SAICTCOVID/72536/2020 da FCTJoint Programming Initiative on Antimicrobial Resistance Aquatic/006/2020NIEHS NIH HHS T32ES015459Programa Operacional de Competitividade e Internacionalização, Programa Operacional Regional de Lisboa, Programa Operacional Regional do Norte COVIDETECT, ref. 048467
6 · The paper itself

Abstract

The United States Centers for Disease Control and Prevention reported a rise in resistant infections after the coronavirus disease 2019 (COVID-19) pandemic started. How and if the pandemic contributed to antibiotic resistance in the larger population is not well understood. Wastewater treatment plants are good locations for environmental surveillance because they can sample entire populations. This study aimed to validate methods used for COVID-19 wastewater surveillance for bacterial targets and to understand how rising COVID-19 cases from October 2020 to February 2021 in Portugal (PT) and King County, Washington contributed to antibiotic resistance genes in wastewater. Primary influent wastewater was collected from two treatment plants in King County and five treatment plants in PT, and hospital effluent was collected from three hospitals in PT. Genomic extracts were tested with the quantitative polymerase chain reaction for antibiotic resistance genes conferring resistance against antibiotics under threat. Random-effect models were fit for log-transformed gene abundances to assess temporal trends. All samples collected tested positive for multiple resistance genes. During the sampling period,

Indexed as

COVID-19SARS-CoV-2WastewaterDrug Resistance, BacterialDrug Resistance, MicrobialEnvironmental MonitoringGenes, BacterialHumansPandemicsPortugalWashingtonWastewaterantibiotic resistanceCOVID-19wastewater-based epidemiologywastewater surveillance

Identifiers

PMID39340381

What OpenQuestion holds

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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.