Evidence map›Paper›PMID 37519995›Full record

ArticleFrontiers in veterinary science2023

Disentangling transport movement patterns of trucks either transporting pigs or while empty within a swine production system before and during the COVID-19 epidemic.

Catalina Picasso-Risso, Carles Vilalta, Juan Manuel Sanhueza, Mariana Kikuti, Mark Schwartz, Cesar A Corzo

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2023. 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

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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

6 authors.

Catalina Picasso-RissoDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States.
Carles VilaltaDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States.
Juan Manuel SanhuezaDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States.
Mariana KikutiDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States.
Mark SchwartzDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States.
Cesar A CorzoDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transport of pigs between sites occurs frequently as part of genetic improvement and age segregation. However, a lack of transport biosecurity could have catastrophic implications if not managed properly as disease spread would be imminent. However, there is a lack of a comprehensive study of vehicle movement trends within swine systems in the Midwest. In this study, we aimed to describe and characterize vehicle movement patterns within one large Midwest swine system representative of modern pig production to understand movement trends and proxies for biosecurity compliance and identify potential risky behaviors that may result in a higher risk for infectious disease spread. Geolocation tracking devices recorded vehicle movements of a subset of trucks and trailers from a production system every 5 min and every time tracks entered a landmark between January 2019 and December 2020, before and during the COVID-19 pandemic. We described 6,213 transport records from 12 vehicles controlled by the company. In total, 114 predefined landmarks were included during the study period, representing 5 categories of farms and truck wash facilities. The results showed that trucks completed the majority (76.4%, 2,111/2,762) of the recorded movements. The seasonal distribution of incoming movements was similar across years (

Indexed as

disease surveillanceMidwestnetwork analysispork industrytransportUSA

Identifiers

PMID37519995
PMCPMC10376687

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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.