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Complex farming systems (such as swine banding) rely on a high degree of population structuring in space and time. Writing mechanistic epidemiological models to understand, predict and control the spread of pathogens in such systems can be long, difficult and not very reusable. Methods at the confluence of artificial intelligence and software engineering have been developed to provide generic solutions for explicitly formalising such models in a form that is readable by non-modelling scientists. This provides modellers with a flexible framework for expressing the organisation and constraints of the populations under study in a very fine-grained way, with these specifications then being processed automatically by a simulation engine. These original methods were published at ICAART (international conference in AI with reading committee and proceedings) and will be applied to the modelling of the impact of swine banding on swine diseases (influenza and porcine reproductive and respiratory syndrome), in collaboration with the Anses.

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Organisational system applied to a farrow-to-finish pig farm, to represent social structuring in bands/litter and spatial structuring in sectors/barns.
The same mechanisms are used for both types of organisation.