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Abstract :

Animals trade movements form complex and dynamic networks of contacts between herds, and are the major mechanism of pathogens spread. Bovine paratuberculosis, due to Mycobacterium avium subsp. paratuberculosis (Map), is a widespread endemic disease, transmitted among cattle through trade movements of undetected infected animals. This disease with a strong economic impact induces production losses and premature culling. This chronic disease is characterized by a long incubation period and poorly sensitive screening tests. Therefore, field observation of Map spread is barely possible and its control remains a major challenge. The objective of this thesis is to better understand the spread of Map at a regional scale using a modeling approach, and compare control strategies combining internal and external biosecurity measures. Our model is the first multiscale mechanistic model of Map spread between dairy cattle
herds, considering stochastic intra-herd dynamics (demography and infection), explicit indirect transmission, and heterogeneity of herds characteristics and livestock trade movements based on field data. Our results provide the essential foundation for a better understanding of Map spread in an endemic area, highlighting the importance of wholesalers holdings. Applied to the Britanny region, the model allows the assessment of the effectiveness of a large panel of control measures used alone and in combination, highlighting the key role of calf management. Using Bayesian inference from epidemiological data allowed to inform on the risk of introducting an infected animal through animal purchase and the within-herd transmission rate. The effectiveness of controlling Map will depend on an efficient coordination of interventions and available diagnostic tools.

Key words :

Epidemiological model, multiscale modeling, metapopulation, contact network, Bayesian inference, paratuberculosis, Mycobacterium avium subsp. paratuberculosis, control strategies