Computer simulation of a cellular automata model for the immune response in a retrovirus system

Abstract

Immune response in a retrovirus system is modeled by a network of three binary cell elements to take into account some of the main functional features of T4 cells, T8 cells, and viruses. Two different intercell interactions are introduced, one of which leads to three fixed points while the other yields bistable fixed points oscillating between a healthy state and a sick state in a mean field treatment. Evolution of these cells is studied for quenched and annealed random interactions on a simple cubic lattice with a nearest neighbor interaction using inhomogenous cellular automata. Populations of T4 cells and viral cells oscillate together with damping (with constant amplitude) for annealed (quenched) interaction on increasing the value of mixing probabilityB from zero to a characteristic valueB _ca (B _cq). For higherB, the average number of T4 cells increases while that of the viral infected cells decreases monotonically on increasingB, suggesting a phase transition atB _ca (B _cq).