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1 GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen 2 BIOEPAR - Bioagression, Epidémiologie et Analyse de Risques 3 Equipe MAD - Laboratoire GREYC - UMR6072 GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen

Abstract : A strategy to control an animal disease within an area is often based on one or more actions systematically implemented. In this paper, we illustrate how to use a Markov Decision Process MDP to compute an adaptive strategy depending on the pathogen spread within a group of farmers with only one decisionmaker for the group. The objective at the group level is to decrease the cost of the disease and its control. Status for each farm is assumed to be exactly known each year by the decision-maker. Possible actions each year are Doing nothing or Vaccinating. The computed MDP policy results in a non-systematic vaccination. Although the objective is only based on the total costs, the computed MDP policy reduces the prevalence, that is the amount of infected herds, compared to a systematically Doing nothing strategy

keyword : Artificial intelligence Epidemiology Policy Vaccination Animal





Autor: Anne-France Viet - Laurent Jeanpierre - Maroua Bouzid - Abdel-Illah Mouaddib -

Fuente: https://hal.archives-ouvertes.fr/



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