Local interactions between individual organisms influence the population dynamics of species and impact their evolution. We describe high-performance simulation of evolutionary aspects of epidemics in spatially explicit, individual based models of multi-species habitat. Evolution consists of two processes, selection between genotypes and mutations producing novel genotypes. In this paper we focus on the effects of selection between genotypes in a model with a single host species and two competing pathogens with fixed (i.e. non-evolving) genotypes. We present the foundations of a model that represents two competing host species, a parasite serving as a disease vector, and a vector borne pathogen. The model is implemented as cellular automaton that tracks individual organisms to account for heterogeneity of the habitat. The implementation targets parallel distributed memory machines (including IBM SP-2 and a network of workstations) and NUMA shared memory architectures (SGI Origin 2000). We demonstrate also that this model yields qualitatively new biological results.