Evidence map›Paper›PMID 36519006›Full record

ArticleTranslational animal science2022

Evaluating dry vs. wet disinfection in boot baths on detection of porcine epidemic diarrhea virus and porcine reproductive and respiratory virus RNA.

Olivia L Harrison, Grace E Houston, Allison K Blomme, Haley K Otott, Jianfa Bai, Elizabeth G Poulsen Porter, Jason C Woodworth, Chad B Paulk, Jordan T Gebhardt, Cassandra K Jones

Open access · goldAbstract read
In one paragraph

Article in Translational animal science, 2022. 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, top 85% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

10 authors at 1 institution in 1 country.

Olivia L HarrisonDepartment of Animal Sciences and Industry, Kansas State University, Manhattan, KS, USA.
Grace E HoustonDepartment of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS, USA.
Allison K BlommeDepartment of Grain Science and Industry, Kansas State University, Manhattan, KS, USA.
Haley K OtottDepartment of Grain Science and Industry, Kansas State University, Manhattan, KS, USA.
Jianfa BaiDepartment of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS, USA.
Elizabeth G Poulsen PorterDepartment of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS, USA.
Jason C WoodworthDepartment of Animal Sciences and Industry, Kansas State University, Manhattan, KS, USA.ORCID https://orcid.org/0000-0001-7268-4278
Chad B PaulkDepartment of Grain Science and Industry, Kansas State University, Manhattan, KS, USA.
Jordan T GebhardtDepartment of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS, USA.ORCID https://orcid.org/0000-0002-6144-6714
Cassandra K JonesDepartment of Animal Sciences and Industry, Kansas State University, Manhattan, KS, USA.ORCID https://orcid.org/0000-0002-0671-8879
Kansas State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Maintaining biosecurity between swine barns is challenging, and boot baths are an easily implementable option some utilize to limit pathogen spread. However, there are concerns regarding their efficacy, especially when comparing wet or dry disinfectants. The objective of this study was to evaluate the efficacy of boot baths in reducing the quantity of detectable porcine epidemic diarrhea virus (

Indexed as

boot bathPEDVPRRSVswine

Identifiers

PMID36519006
PMCPMC9744243
OpenAlexW4308826649

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.