  We present an algorithm which explores permutation symmetries to describe the
time evolution of agent-based epidemic models. The main idea to improve
computation times relies on restricting the stochastic process to one sector of
the vector space, labeled by a single permutation eigenvalue. In this scheme,
the transition matrix reduces to block diagonal form, enhancing computational
performance.
