Development of Logistic Regression Models for Binary Classification of Covid-19 and Statistical Prediction of Deaths (Research, Society and Development, 2024)
The present study aims to statistically research Covid-19 data to determine the profile greatest vulnerability of the disease, developing logistic regression models as a methodological strategy. Additionally, hypothesis testing, odds ratios and statistical prediction techniques are used to investigate the conditions of symptom exacerbation and to estimate the numbers of deaths and recoveries in different places. According to the results obtained from the multivariate models, it was defined that male individuals with pre-existing Hepatic, Neurological or Pneumopathy conditions represent the patients at greatest risk of death. Furthermore, a logistic regression model with a numerical independent variable was developed to predict the odds of belonging to the death class, thus determining the recovered and deceased cases. The model obtained positive results with significant accuracy in different municipalities and is available on the author's GitHub profile.