Investigation of spatial pattern formation involving CD4+ T cells in HIV/AIDS dynamics by a stochastic cellular automata model

Abstract

In recent years, discrete models have emerged to play an important role in the study of immune response especially in the problem involving human immunodeficiency virus (HIV) infection, leading to AIDS. As infection of target immune cells by HIV mainly takes place in the lymphoid tissue, cellular automata (CA) models thus represent a significant step toward understanding how the infected population is dispersed. Motivated by these considerations, we introduce a stochastic CA model for HIV dynamics and explore the spatiotemporal pattern of infection. The model is successful in reproducing typical evolution of HIV which is observed in the dynamics of CD4+T cells and infected CD+T cells in infected patients. The geographical result on cell distributions illustrates how infected cells can be dispersed by spatial communities. We have found the pattern formation is based on the relationship among cell states, the set of local transition rules, the conditions and the parameters in the systems. The main finding is that the emergence of dead cells barriers greatly controls the pattern formation in our system, by limiting infections and the manner in which the infection dynamics is brought to the last phase after the barrier is destroyed.