Evidence map›Paper›PMID 31791320›Full record

ArticleBMC veterinary research2019

Use of a voluntary testing program to study the spatial epidemiology of Johne's disease affecting dairy herds in Minnesota: a cross sectional study.

K S T Kanankege, G Machado, L Zhang, B Dokkebakken, V Schumann, S J Wells, A M Perez, J Alvarez

Open access · goldAbstract read
In one paragraph

Article in BMC veterinary research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 32% 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

2 citing papers in PubMed, 4 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

8 authors at 4 institutions in 2 countries.

K S T KanankegeDepartment of Population Medicine, College of VeterinaryMedicine, University of Minnesota, 1365, Gortner Avenue, St. Paul, MN, 55108, USA. kanan009@umn.edu.ORCID http://orcid.org/0000-0002-5931-1634
G MachadoDepartment of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, USA.
L ZhangDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, USA.
B DokkebakkenMinnesota Dairy Herd Improvement Association, Buffalo, USA.
V SchumannMinnesota Dairy Herd Improvement Association, Buffalo, USA.
S J WellsDepartment of Population Medicine, College of VeterinaryMedicine, University of Minnesota, 1365, Gortner Avenue, St. Paul, MN, 55108, USA.
A M PerezDepartment of Population Medicine, College of VeterinaryMedicine, University of Minnesota, 1365, Gortner Avenue, St. Paul, MN, 55108, USA.
J AlvarezCentro de Vigilancia Sanitaria Veterinaria (VISAVET), Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad Complutense, Madrid, Spain.
University of Minnesota · USAmerican Dairy Science Association · USNorth Carolina State University · USUniversidad Complutense de Madrid · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOne of the key steps in the management of chronic diseases in animals including Johne's disease (JD), caused by Mycobacterium avium subsp. paratuberculosis (MAP), is the ability to track disease incidence over space and time. JD surveillance in the U.S. dairy cattle is challenging due to lack of regulatory requirements, imperfect diagnostic tests, and associated expenses, including time and labor. An alternative approach is to use voluntary testing programs. Here, data from a voluntary JD testing program, conducted by the Minnesota Dairy Herd Improvement Association, were used to: a) explore whether such a program provides representative information on JD-prevalence in Minnesota dairy herds, b) estimate JD distribution, and, c) identify herd and environmental factors associated with finding JD-positive cows. Milk samples (n = 70,809) collected from 54,652 unique cows from 600 Minnesota dairy herds between November 2014 and April 2017 were tested using a MAP antibody ELISA. Participant representativeness was assessed by comparing the number of JD-tested herds with the number of herds required to estimate the true disease prevalence per county based on official statistics from the National Agricultural Statistical Services. Multivariable logistic regression models, with and without spatial dependence between observations, were then used to investigate the association between herd status to JD (positive/negative), as indicated by milk ELISA results, and available covariates at the herd level.

resultsWithin the study population, at least one test-positive cow was found in 414 of 600 (69%) herds. Results indicated that large herds that test frequently and herds located in loamy or silt soils are more likely to have at least one MAP test-positive cow. After adjusting for herd size, testing frequency, and soil type, there was no spatial dependence in JD risk between neighboring dairies within 5 to 20 km. Furthermore, the importance of collecting data on herd management, feed, and biosecurity for insightful interpretations was recognized. The study suggested that, although limited, the voluntary testing database may support monitoring JD status.

conclusionsResults presented here help elucidate the spatial characteristics of JD in Minnesota and the study may ultimately contribute to the design and implementation of surveillance programs for the disease.

Indexed as

Animal HusbandryAnimalsAntibodies, BacterialCattleCattle DiseasesCross-Sectional StudiesDairyingEnzyme-Linked Immunosorbent AssayFemaleMilkMinnesotaMycobacterium avium subsp. paratuberculosisParatuberculosisSoilAntibodies, BacterialSoilCAR modelMilk ELISAParatuberculosisPassive surveillanceRegressionSpatial epidemiology

Identifiers

PMID31791320
PMCPMC6889654
OpenAlexW2989576640

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.