Evidence map›Paper›PMID 37033057›Full record

ArticleFrontiers in public health2023

Analysis of metatranscriptomic methods to enable wastewater-based biosurveillance of all infectious diseases.

Rachel R Spurbeck, Lindsay A Catlin, Chiranjit Mukherjee, Anthony K Smith, Angela Minard-Smith

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
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

7 citing papers in PubMed, 13 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Rachel R SpurbeckHealth Business Unit, Drug Development and Precision Diagnostics Division, Life Sciences Research Business Line, Battelle Memorial Institute, Columbus, OH, United States.
Lindsay A CatlinNational Security Business Unit, Bioscience Center, CBRNE Business Line, Battelle Memorial Institute, Columbus, OH, United States.
Chiranjit MukherjeeHealth Business Unit, Health Analytics Division, Health Outcomes and Biotechnology Solutions Business Line, Battelle Memorial Institute, Columbus, OH, United States.
Anthony K SmithNational Security Business Unit, Bioscience Center, CBRNE Business Line, Battelle Memorial Institute, Columbus, OH, United States.
Angela Minard-SmithHealth Business Unit, Health Analytics Division, Health Outcomes and Biotechnology Solutions Business Line, Battelle Memorial Institute, Columbus, OH, United States.
Battelle · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Wastewater-based surveillance emerged during the COVID-19 pandemic as an efficient way to quickly screen large populations, monitor infectious disease transmission over time, and identify whether more virulent strains are becoming more prevalent in the region without burdening the health care system with individualized testing. Ohio was one of the first states to implement wastewater monitoring through its Ohio Coronavirus Wastewater Monitoring Network (OCWMN), originally tracking the prevalence of COVID-19 by quantitative qPCR from over 67 sites across the state. The OCWMN evolved along with the pandemic to include sequencing the SARS-CoV-2 genome to assess variants of concern circulating within the population. As the pandemic wanes, networks such as OCWMN can be expanded to monitor other infectious diseases and outbreaks of interest to the health department to reduce the burden of communicable diseases. However, most surveillance still utilizes qPCR based diagnostic tests for individual pathogens, which is hard to scale for surveillance of multiple pathogens. Methods: Here we have tested several genomic methods, both targeted and untargeted, for wastewater-based biosurveillance to find the most efficient procedure to detect and track trends in reportable infectious diseases and outbreaks of known pathogens as well as potentially novel pathogens or variants on the rise in our communities. RNA extracts from the OCWMN were provided weekly from 10 sites for 6 weeks. Total RNA was sequenced from the samples on the Illumina NextSeq and on the MinION to identify pathogens present. The MinION long read platform was also used to sequence SARS-CoV-2 with the goal of reducing the complexity of variant calling in mixed populations as occurs with short Illumina reads. Finally, a targeted hybridization approach was tested for compatibility with wastewater RNA samples. Results and discussion: The data analyzed here provides a baseline assessment that demonstrates that wastewater is a rich resource for infectious disease epidemiology and identifies technology gaps and potential solutions to enable this resource to be used by public health laboratories to monitor the infectious disease landscape of the regions they serve.

Indexed as

BiosurveillanceCommunicable DiseasesCOVID-19HumansPandemicsRNASARS-CoV-2WastewaterRNAWastewaterbiosurveillancegenomicsinfectious diseasemetatranscriptomicssequencingwastewater-based epidemiology

Identifiers

PMID37033057
PMCPMC10073511
OpenAlexW4353081980

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.