In this paper some innovative aspects of the mathematical modelling of classic epidemiology problems for the study of models related to the COVID-19 pandemic dynamics are presented. In addition, they are compared to real-world data using numerical methods in order to approximate the solutions. One of these models includes a non-transmitting compartment and another one, a delay-differential equation in the SIR-type method. Finally, a comparative discussion of the results is also presented.

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This paper presents a new operation of multiplication between linearly correlated fuzzy numbers based on the concept of cross product, set for fuzzy numbers in general. It is proved that this operation is closed in the set of linearly correlated fuzzy numbers. Some properties of the multiplication are listed, and an application on the delayed logistic model, the Hutchinson equation, is provided when considering the population an autocorrelated fuzzy process. Lastly, an analysis of the stability of the solution and biological interpretations are established.