Introduction:

Studies based on statistical models play an important role for predictions about COVID-19.

Objective:

To carry out a statistical modeling analysis combining 6 forecast models to predict the appearance of daily positive cases, active and deceased by COVID-19 in Cuba.

Method:

Data reported daily from March 11 to May 25 from the CUBADEBATE website were used, which were processed and analyzed. The performance of the models was calculated: Mean absolute error (MAE), root of the mean square error (RMSE), percent of mean absolute error (MAPE) and the mean error (ME) as well as the residual analysis.

Results:

Models A and B gave a constant trend between 8 and 9 cases of until July 22. Model C indicated a decrease in cases with 4 that same day and model D indicated a raise to 19 cases. Model E indicated a minimum of 126 cases on June E and then a raise to 374 hospitalized cases. Deceases cases had a constant tendency in deceases numbers above of 80 cases in first 15 days of July.

Conclusions:

The 6 models studied meet the statistical , performance and residual tests. Their data provides a forecast for COVID2019, representing a valid tool.

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