Fuzzy rules in asymptomatic HIV virus infected individuals model

The purpose of this paper is to study of the evolution of positive HIV population for manifestation of AIDS (Acquired Immunideficiency Syndrome). Our main interest is to model the transference rate in this stage. For this purpose, we use expert information on transference rate because it strongly depends of the viral load and of the level 4 CD +of the infected individuals. More specifically, the transference rate is modeled as a fuzzy set that depends of the knowledge on viral load and 4 CD + , respectively. The main difference between this model and the classic one relies on the biological meaning of the transference rate λ. Medical science uses linguistic notions to characterize disease stages and to specify anti-retroviral therapy. Fuzzy set theory provides the formal framework to model linguistic descriptions such as the transference rate λ using expert knowledge.