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. Among the important steps of

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... modeling and simulation: model validation. It refers to the process of determining how well a model corresponds to the system that it intended to represent. So the question is: what happens if the model is invalid? Do we need to reproduce another one, or just optimize the existing one? In this paper, we present a new approach consisting on 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.