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Which phenotypic traits of resistance should be improved in cattle to control paratuberculosis dynamics in a dairy herd: a modelling approach

Overview of attention for article published in Veterinary Research, October 2017
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Title
Which phenotypic traits of resistance should be improved in cattle to control paratuberculosis dynamics in a dairy herd: a modelling approach
Published in
Veterinary Research, October 2017
DOI 10.1186/s13567-017-0468-8
Pubmed ID
Authors

Racem Ben Romdhane, Gaël Beaunée, Guillaume Camanes, Raphaël Guatteo, Christine Fourichon, Pauline Ezanno

Abstract

Paratuberculosis is a worldwide disease causing production losses in dairy cattle herds. Variability of cattle response to exposure to Mycobacterium avium subsp. paratuberculosis (Map) has been highlighted. Such individual variability could influence Map spread at larger scale. Cattle resistance to paratuberculosis has been shown to be heritable, suggesting genetic selection could enhance disease control. Our objective was to identify which phenotypic traits characterising the individual course of infection influence Map spread in a dairy cattle herd. We used a stochastic mechanistic model. Resistance consisted in the ability to prevent infection and the ability to cope with infection. We assessed the effect of varying (alone and combined) fourteen phenotypic traits characterising the infection course. We calculated four model outputs 25 years after Map introduction in a naïve herd: cumulative incidence, infection persistence, and prevalence of infected and affected animals. A cluster analysis identified influential phenotypes of cattle resistance. An ANOVA quantified the contribution of traits to model output variance. Four phenotypic traits strongly influenced Map spread: the decay in susceptibility with age (the most effective), the quantity of Map shed in faeces by high shedders, the incubation period duration, and the required infectious dose. Interactions contributed up to 12% of output variance, highlighting the expected added-value of improving several traits simultaneously. Combinations of the four most influential traits decreased incidence to less than one newly infected animal per year in most scenarios. Future genetic selection should aim at improving simultaneously the most influential traits to reduce Map spread in cattle populations.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 33%
Student > Ph. D. Student 4 19%
Professor 2 10%
Librarian 1 5%
Other 1 5%
Other 2 10%
Unknown 4 19%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 6 29%
Agricultural and Biological Sciences 4 19%
Environmental Science 1 5%
Biochemistry, Genetics and Molecular Biology 1 5%
Psychology 1 5%
Other 2 10%
Unknown 6 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 October 2017.
All research outputs
#14,034,596
of 15,916,110 outputs
Outputs from Veterinary Research
#868
of 959 outputs
Outputs of similar age
#239,660
of 281,641 outputs
Outputs of similar age from Veterinary Research
#7
of 8 outputs
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So far Altmetric has tracked 959 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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