Introduction:

The mathematical models are abstractions of the reality that allow for the description of important characteristics of the phenomena studied. Among these, the epidemic models are considered one of the most powerful tools to analyze and understand epidemic propagation and control. Objective: A model for the forecast of spread scenarios of the COVID-19 has been developed.

Methods:

A proposed population model inspired by analogy by hydrologic routing in rivers, an autoregressive integrated moving average model (ARIMA) and a transition model were combined in order to evaluate three possible spread scenarios and their temporary evolution during the development of COVID-19 pandemic.

Results:

In this contribution, 27 countries having coronavirus daily reports until April 16th, 2020 were studied. They were grouped by quartiles according to rates of recovered and deceased people. This information permitted the establishment of criteria for the parameters involved in the proposed model for Cuba as a case study. The favorable, not very favorable and critical epidemic spread scenarios were generated from ARIMA up to April 29th, 2020 and the transition model extended to 120 days. The results of the model implementation were compared with the real data of the pandemic evolution in Cuba up to May 22nd, 2020, resulting in a satisfactory correspondence between the real daily reports and the scenarios of active cases. This model could be used in the same way for other American countries that also have a delay with regard to the countries selected for this study.

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