Foundation:

on the pandemic caused by the new SARS-CoV-2 coronavirus, it is important to estimate the growth of infested cases and deaths of the Cuban population.

Objective:

to obtain predictions for the peak of confirmed and deceased cases in Cuba by COVID-19, using statistical and computer tools.

Methods:

the least squares method was used to obtain the parameters using linear (MCL) and nonlinear (MCNL) models. Logistic and exponential models, such as the logistic growth curve, used to model population growth (Gompertz growth models), were applied to the growth prediction of infected cases and / or deaths, respectively.

Results:

there is an adequacy of the presented models with respect to the predicted and the real values which allow their reliability for the predictions made for Cuba.

Conclusions:

statistical prediction models obtained give very significant results for the COVID-19 pandemic study in Cuba.

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