Titre :

Combining early hyperthermia detection with metaphylaxis for reducing antibiotics usage in newly received beef bulls at fattening operations: a simulation-based approach

Auteur(s) :

Picault, Sebastien [Auteur]
Biologie, Epidémiologie et analyse de risque en Santé Animale [BIOEPAR]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ezanno, Pauline [Auteur]
Biologie, Epidémiologie et analyse de risque en Santé Animale [BIOEPAR]
Assié, Sébastien [Auteur]
Biologie, Epidémiologie et analyse de risque en Santé Animale [BIOEPAR]

Titre de la manifestation scientifique :

SVEPM: Conference & Annual General Meeting

Ville :

Utrecht

Pays :

Pays-Bas

Date de début de la manifestation scientifique :

2019-03-27

Titre de l’ouvrage :

SVEPM: Conference & Annual General Meeting

Titre de la revue :

Proceedings of the SVEPM: Conference & Annual General Meeting

Date de publication :

2019-03

Mot(s)-clé(s) en anglais :

bovine respiratory disease
antibiotics usage
epidemiological modelling
disease detection

Discipline(s) HAL :

Informatique [cs]/Modélisation et simulation
Sciences du Vivant [q-bio]/Biologie animale/Médecine vétérinaire et santé animale
Sciences du Vivant [q-bio]/Santé publique et épidémiologie
Informatique [cs]/Intelligence artificielle [cs.AI]

Résumé en anglais : [en]

Bovine Respiratory Disease (BRD) dramatically affects fattened young beef bull pens. How metaphylaxis and early detection help balance disease duration and antibiotics usage remains unclear. Our goal was to determine ...
Lire la suite >Bovine Respiratory Disease (BRD) dramatically affects fattened young beef bull pens. How metaphylaxis and early detection help balance disease duration and antibiotics usage remains unclear. Our goal was to determine efficient control strategies, assessed on disease duration, antibiotics doses, and true positives, for various infection forces accounting for BRD pathogen diversity. A stochastic mechanistic individual-based model combined infectious processes, detection methods, and treatment protocols in a realistic simulated small-size pen. To enable veterinary experts to assess and revise model assumptions, a new artificial intelligence framework, EMULSION, was used to describe model features in an explicit and intelligible form. Parameters were calibrated from observed data. Overpassing on-farm reference scenario using boluses required to very early detect the first case while using longer hyperthermia for subsequent detections. Metaphylaxis was efficient only for high pathogen transmission. Besides concrete recommendations to farmers, EMULSION models could easily address other farming systems, treatments, and diseases.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Projet ANR :

Modélisation multi-échelle, de l'Intra-Hôte animal à la Métapopulation, des mécanismes de propagation d'agents

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL