Dynamics of HIV infection: a cellular automata approach.

We use a cellular automata model to study the evolution of human immunodeficiency virus (HIV) infection and the onset of acquired immunodeficiency syndrome (AIDS). The model takes into account the global features of the immune response to any pathogen, the fast mutation rate of the HIV, and a fair amount of spatial localization, which may occur in the lymph nodes. Our results reproduce the three-phase pattern observed in T cell and virus counts of infected patients, namely, the primary response, the clinical latency period, and the onset of AIDS. The dynamics of real experimental data is related to the transient behavior of our model and not to its steady state. We have also found that the infected cells organize themselves into spatial structures, which are responsible for the decrease on the concentration of uninfected cells, leading to AIDS.