Abstract

The COVID-19 pandemic affecting planet Earth has had a peculiar development in Cuba. The objective of the research consisted in modeling by means of the methodology of the Regressive Objective Regression (ROR) two parameters/variables (age and number of contacts) inherent to the SARS-CoV-2 pandemic causing the COVID-19, during the year 2020 and so far in 2021 in Villa Clara province, Cuba. Mathematical models were obtained by means of the ROR methodology that explain their behavior, being able to extract information from a white noise, which made it possible to make a long-term prognosis of contact cases, which can be estimated up to 13 steps ahead, allowing to take measures in clinical services, and thus avoid and decrease the number of deaths and complications in patients, since patients can be detected and treated with medication faster. The age of suspects can also be estimated using the ROR methodology, where the trend of age was increasing for contact cases, where all variables were significant, indicating that there is an increasing tendency for cases to decrease if control measures are increased. It is concluded that COVID-19, despite being a new disease, can be followed by means of mathematical modeling ROR, a better management of the pandemic, so we hope that this prognosis can help in decision making for the prediction age, suspects and contacts of COVID-19 in the Villa Clara province and Cuba.

Keywords: COVID-19; Age; Prognosis; Objective Regression Regression (ORR); Suspects

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