Evidence map›Paper›PMID 32581260›Full record

ArticleScientific reports2020

Pooled samples and eDNA-based detection can facilitate the "clean trade" of aquatic animals.

Jesse L Brunner

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

3 citing papers in PubMed, 22 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

1 author at 1 institution in 1 country.

Jesse L BrunnerWashington State University, School of Biological Sciences, Pullman, WA, 99164, USA. jesse.brunner@wsu.edu.ORCID http://orcid.org/0000-0003-4894-8274
Washington State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The regional and international trade of live animals facilitates the movement, spillover, and emergence of zoonotic and epizootic pathogens around the world. Detecting pathogens in trade is critical for preventing their continued movement and introduction, but screening a sufficient fraction to ensure rare infections are detected is simply infeasible for many taxa and settings because of the vast numbers of animals involved-hundreds of millions of live animals are imported into the U.S.A. alone every year. Batch processing pools of individual samples or using environmental DNA (eDNA)-the genetic material shed into an organism's environment-collected from whole consignments of animals may substantially reduce the time and cost associated with pathogen surveillance. Both approaches, however, lack a framework with which to determine sampling requirements and interpret results. Here I present formulae for pooled individual samples (e.g,. swabs) and eDNA samples collected from finite populations and discuss key assumptions and considerations for their use with a focus on detecting Batrachochytrium salamandrivorans, an emerging pathogen that threatens global salamander diversity. While empirical validation is key, these formulae illustrate the potential for eDNA-based detection in particular to reduce sample sizes and help bring clean trade into reach for a greater number of taxa, places, and contexts.

Indexed as

CommerceAnimal DiseasesAnimalsBatrachochytriumCaudataDNA, EnvironmentalInternationalitySample SizeDNA, Environmental

Identifiers

PMID32581260
PMCPMC7314758
OpenAlexW3037464547

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.