  The susceptible-infected-susceptible (SIS) agent-based model is usually
employed in the investigation of epidemics. The model describes a Markov
process for a single communicable disease among susceptible (S) and infected
(I) agents. However, the disease spreading forecasting is often restricted to
numerical simulations, while analytic formulations lack both general results
and perturbative approaches since they are subjected to asymmetric time
generators. Here, we discuss perturbation theory, approximations and
application of many-body techniques in epidemic models in the framework for
squared norm of probability vector $|P(t)| ^2$, in which asymmetric time
generators are replaced by their symmetric counterparts.
