Abstract
In order to recommend better control measures in public or animal health, epidemiologists incorporate ever-finer details in their models, from individual diversity to public policies, which often involve several observation scales. Due to the variety of modelling paradigms, it becomes more and more difficult to compare hypotheses and outcomes, all the more that the increased complexity of simulation programs is not yet counterbalanced by design principles nor by software engineering methods. We propose in this paper to use the multi-level agent-based paradigm to integrate existing methods within a common interface, provide a separation between concerns and reduce the part of code devoted to model designers. We illustrate our approach with an application to the Q fever disease in cattle.
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Notes
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EMuLSion stands for “Epidemiological MUlti-Level SimulatION framework”.
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Acknowledgements
Project MIHMES is funded by the French Research Agency, Program Investments for the Future (ANR-10-BINF-07) and the European fund for the Regional Development (FEDER) of Pays-de-la-Loire. The research work presented here is also funded by the Animal Health Division of the French National Institute for Agricultural Research (INRA).
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Picault, S., Huang, YL., Sicard, V., Beaudeau, F., Ezanno, P. (2017). A Multi-Level Multi-Agent Simulation Framework in Animal Epidemiology. In: Demazeau, Y., Davidsson, P., Bajo, J., Vale, Z. (eds) Advances in Practical Applications of Cyber-Physical Multi-Agent Systems: The PAAMS Collection. PAAMS 2017. Lecture Notes in Computer Science(), vol 10349. Springer, Cham. https://doi.org/10.1007/978-3-319-59930-4_17
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