Numerical modeling of HIV dynamics in CD4+ T-cells using fuzzy differential equations

Abstract

In this study, we use fuzzy differential equations (FDEs) to present a mathematical model for the dynamics of HIV infection in CD4+ T-cells. Uninfected cells, infected cells, and viral particles, all of which are represented as fuzzy dynamical systems, are the three main components of the model. We use ρ-cut techniques to convert the fuzzy system into a corresponding crisp system of differential equations to analyze the spread and control of HIV. Equilibrium points and eigenvalue-based criteria are used in stability analysis. In addition, we derive approximate solutions using the fifth-order Runge-Kutta numerical approach. The suggested method provides a more adaptable and practical framework for understanding the dynamics of HIV infection in an environment of uncertainty.