Evidence map›Paper›PMID 30979836›Full record

ArticleApplied and environmental microbiology2019

Spiked Virus Level Needed To Correctly Assess Enteric Virus Recovery in Water Matrices.

Qiaozhi Li, Yuanyuan Qiu, Xiao L Pang, Nicholas J Ashbolt

Abstract read
In one paragraph

Article in Applied and environmental microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Qiaozhi LiSchool of Public Health, University of Alberta, Edmonton, AB, Canada.ORCID 0000-0002-0959-6846
Yuanyuan QiuAlberta Provincial Laboratory for Public Health, Edmonton, AB, Canada.
Xiao L PangAlberta Provincial Laboratory for Public Health, Edmonton, AB, Canada.
Nicholas J AshboltSchool of Public Health, University of Alberta, Edmonton, AB, Canada ashbolt@ualberta.ca.ORCID 0000-0002-3853-0096

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative microbial risk assessment (QMRA) identifies human enteric viruses in municipal wastewater as the pathogen group requiring the highest log reductions for various reuse applications. However, the performance of methods for estimating virus concentration is not well understood, and without performance assessment, actual risks are likely severely underestimated. To evaluate the efficiency of virus recovery from water, a water sample is often spiked with "known" amounts of virus, and the virus is then recovered after a series of analytical procedures. Yet for water matrices such as wastewater, due to the unknown background concentrations of targeted viruses in the matrix and the variable recovery efficiency between individual processes, only an approximation of the recovery efficiency may be obtained from such spike-and-recovery experiments. In this study, we demonstrated theoretically that for two widely used approximations, the error in estimating virus recovery should be less than the ratio of the amount of target virus in the background sample to that in the spike. Furthermore, we developed an applicable method, based on this new understanding, for deciding on the amount of virus for spiking before conducting a spike-and-recovery experiment, so that the approximation error is restricted to an acceptable level for each individual process. Finally, we applied the method to a set of experimental data for viruses in wastewater, demonstrating its utility and noting its general applicability to other pathogens or water matrices.

Indexed as

Waste Disposal, FluidWater PurificationEnterovirusEnvironmental MonitoringWastewaterWastewaterenteric virusesQMRArecoveryspikingwater reuse

Identifiers

PMID30979836
PMCPMC6544825

What OpenQuestion holds

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Registered trials

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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.