Interactive epidemic models have been intensively studied to describe the spreading of a disease not only by its intrinsic behavior, but by its interaction with other diseases. Previous work has been focused on static aspects of these interactions such as the epidemic threshold, final size (prevalence), etc. But, to the best of our knowledge, there is no work done in modeling how interacting diseases react when they are affected by changes in its dynamical aspects, such as faster or slower variations in the number of people infected. In this thesis we introduce a unified approach for the interaction of two diseases which takes into account cooperation, competition and independence between them. We analyze the effect of changes in their dynamical properties in the presence of a unidirectional coupling, proposing measures like the proportion of infected subjects and its peak time occurrence.