Study on the Methodology of Regressive Objective Regression According to the New SARS-CoV-2 COVID-19 Pandemic in the Municipality of Santa Clara and Cuba - Rigoberto Fimia-Duarte; Jorge Luis Contreras Vidal; David Del Valle Laveaga; Ricardo Osés Rodríguez; Rafael Armiñana García; María Patricia Zambrano Gavilanes (Issues and Development in Health Research Vol. 2, 2021)
The COVID-19 pandemic affecting planet Earth has had a peculiar development in our country. The objective of the research consisted in modeling by means of the methodology of the Regressive Objective Regression (ROR) a set of parameters (deaths, critical, severe, serious, confirmed and new cases) inherent to the SARS pandemic CoV-2 COVID-19, during the year 2020 in Cuba. The parameters analyzed were: deaths, severe, critical, confirmed and new cases in Santa Clara municipality, Villa Clara province and Cuba. The modeling used was Objective Regressive Regression (ORR), which is based on a combination of Dummy variables with ARIMA modeling. In the ROR methodology, dichotomic variables DS, DI and NoC are created in a first step, and then the module corresponding to the Regression analysis is executed, specifically the ENTER method where the predicted variable and the ERROR are obtained. Mathematical models were obtained by means of the ROR methodology which explain their behavior, depending on 6, 4, 10 and 14 days in advance depending on the variable to be studied, which made it possible to make long-term prognoses, allowing measures to be taken in the clinical services, thus avoiding and reducing the number of deaths and complications in patients with COVID-19. Although COVID-19 is a new disease in the world, it can be followed by means of mathematical ROR modeling, which allows to reduce the number of dead, severe and critical patients for a better management of the pandemic.