ABSTRACT
The data unquestionably reflect the degree of impact it has had, not only on the mortality rate, but also on the economic indices of nations. In this context, the present study aims to analyze, from the theoretical mathematical models, what has been the contribution of this area of science to find and predict possible solutions to quell the effects of this global pandemic. For this purpose, statistical analyses based on three models will be used: non-linear phenomenological models, data modeling and the generalized logistic model, which are expected to contribute to a better evaluation and understanding of the measures taken to face this health crisis and, in the future, the importance of understanding the use of data and the technological tools available to mankind today in the face of any new virus. La modelación de datos es realizada por los modelos fenomenológicos más utilizados, para las enfermedades infecciosas;el modelo de Richards (RM) (1959), el modelo logístico generalizado (GLM) y el modelo de Richards generalizado (GRM) (1969), el primero de ellos es un modelo de crecimiento que considera cuatro variables, uno de sus parámetros permite modelar las curvas con mayor precisión, sin embargo, es criticado ya que este parámetro no tiene significado biológico.