The steady state properties of the mean density population of infected cells in a viral spread is simulated by a general forest fire like cellular automaton model with two distinct populations of cells permissive and resistant ones) and studied in the framework of the mean field approximation. Stochastic dynamical ingredients are introduced in this model to mimic cells regeneration (with probability it p) and to consider infection processes by other means than contiguity (with probability it f). Simulations are carried on a L times L square lattice considering the eigth first neighbors. The mean density population of infected cells (Di) is measured as function of the regeneration probability it p, and analized for small values of the ratio it f/p and for distinct degrees of the cell resistance. The results obtained by a mean field like approach recovers the simulations results. The role of the resistant parameter R (R geq 2) on the steady state properties is investigated and discussed in comparision with the R=1 monocell case which corresponds to the em self organized critical forest fire model. The fractal dimension of the dead cells ulcers contours were also estimated and analised as function of the model parameters.
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