  The study considers the usage of a probabilistic optimization method called
Cross-Entropy (CE). This is the version of the Monte Carlo method created by
Reuven Rubinstein (1997). It was developed in the context of determining rare
events. Here we will present the way in which the CE method can be used for
problems of optimization of epidemiological models, and more specifically the
optimization of the SIRC (Susceptible - Infectious - Recovered - Cross-immune)
model based on the functions supervising the care of specific groups in the
model. With the help of weighted sampling, an attempt was made to find the
fastest and most accurate version of the algorithm.
