  The prediction of the behavior of the disease, the level of affectation in a
population and the ways to control it are the most important aspects studied by
epidemiology using tools such as historical data and mathematical models. So,
our objective is (1) to provide a tool capable of analyzing epidemiological
phenomena starting from the most common social interactions within a group of
individuals. (2) To provide a methodology to build epidemiological models from
patterns and logical rules. (3) Determine the impact of social interactions on
the spread of a disease. This paper describes the logical construction of two
epidemiological models in cellular automata together with two of their
variations based on topological and dynamical principles.
