Combining early hyperthermia detection with metaphylaxis for reducing antibiotics usage in newly received beef bulls at fattening operations: a simulation-based approach
| Autor: | Sebastien Picault, Pauline Ezanno, Sébastien Assié |
|---|---|
| Přispěvatelé: | Biologie, Epidémiologie et analyse de risque en Santé Animale (BIOEPAR), Institut National de la Recherche Agronomique (INRA), Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189 (CRIStAL), Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Ecole Centrale de Lille, FEDER Pays de la LoireINRA département Santé AnimalePSDR Sant'Innov (INRA, IRSTEA, régions Bretagne, Pays de la Loire, Normandie, Nouvelle Aquitaine), ANR: 10-BINF-0007,MIHMES,Modélisation multi-échelle, de l'Intra-Hôte animal à la Métapopulation, des mécanismes de propagation d'agents(2010), Institut National de la Recherche Agronomique (INRA)-École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), ANR-10-BINF-0007,MIHMES,Modélisation multi-échelle, de l'Intra-Hôte animal à la Métapopulation, des mécanismes de propagation d'agents(2010), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
[SDV.BA.MVSA]Life Sciences [q-bio]/Animal biology/Veterinary medicine and animal Health
epidemiological modelling antibiotics usage bovine respiratory disease [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie disease detection [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] |
| Zdroj: | SVEPM: Conference & Annual General Meeting SVEPM: Conference & Annual General Meeting, Mar 2019, Utrecht, Netherlands. pp.148-159 HAL |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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