Studies in malaria control cover many areas such as medicine, sociology, biology, mathematics, physics, computer science and so forth. Researches in the realm of mathematics are conducted to predict the occurrence of the disease and to support the eradication process. Basically, the modeling methodology is predominantly deterministic and based on differential equations which take into account important clinical and biological features. Yet, if the individual characteristics matter when modeling the disease, the overall estimation of the epidemic evolution relies on a non-specified percentage of the global population : it is not based on the state of health of each individual. The goal of this paper is to propose a model that relies on a daily evolution of the individual’s state, which depends on their mobility and the characteristics of the area they visit. Thus, the mobility data of a single person moving from one area to another, gathered thanks to mobile networks, is the essential building block to predict the disease outcome. We implement our solution and demonstrate its effectiveness through empirical experiments. The results show how promising the model is in providing possible insights into the failure of the disease control in the Kedougou region.