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Endemic diseases are constantly circulating and can cause heavy losses in animal husbandry in the medium to long term. Controlling these diseases is essential for sustainable agriculture and competitive agri-food chains. Interdisciplinary scientific collaborations between biologists, economists and modellers have highlighted how mathematical modelling in epidemiology contributes to a better understanding and prediction of the circulation of these diseases, as well as to guiding their control at all scales, from the animal to the territory and the primary production chain. The scientific and methodological challenges that still exist in proposing targeted control options and assessing their impact were identified. The strategic decision-making of farmers needs to be included in order to better understand the trade-off between individual and collective management and to better orient incentives. Integrating the immune response of hosts to the infection would also make it possible to refine interventions, particularly therapeutic and preventive (vaccination). Finally, feeding the models with observable data from animal husbandry would increase their realism and practical usefulness, to support public or private collective policies.

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Epidemic infectious diseases (red) cause significant losses over short periods of time, while endemic infectious diseases (orange) persist and can result in significant cumulative incidence. Data collection is necessary to assess the impact of diseases and evaluate the effectiveness of control strategies.