  Many theoretical works and tools on epidemiological field reflect the
emphasis on decision-making Tools by both public health and the scientific
community, which continues to increase. Indeed, in the epidemiological field,
modeling tools are proving a very important way in helping to make decision.
However, the variety, the large volume of data and the nature of epidemics lead
us to seek solutions to alleviate the heavy burden imposed on both experts and
developers. In this paper, we present a new approach: the passage of an
epidemic model realized in Bio-PEPA to a narrative language using the basics of
SBML language. Our goal is to allow on one hand, epidemiologists to verify and
validate the model, and the other hand, developers to optimize the model in
order to achieve a better model of decision making. We also present some
preliminary results and some suggestions to improve the simulated model.
