COVID-19 Patients Analysis using Superheat Map and Bayesian Network to identify Comorbidities Correlations under Different Scenarios.

BackgroundGiven the exposure risk of comorbidities in Mexican society, the new pandemic involves the highest risk for the population in the history. ObjectiveThis article presents an analysis of the COVID-19 risk from Mexicos regions. MethodThe study period runs from April 12 to June 29, 2020 (220,667 patients). The method has a nature applied and according to its level of deepening in the object of study it is framed in a descriptive and explanatory analysis type. The data used here has a quantitative and semi-quantitative characteristic because they are the result of a questionnaire instrument made up of 34 fields and the virus test. The instrument is of a deliberate type. According to the manipulation of the variables, this research is a secondary type of practices, and it has a factual inference from an inductive method because it is emphasizing the concomitant variations for each region of the country. ResultsRegion 1 and Region 4 have a higher percentage of hospitalized patients, while Region 2 has a minimum of them. The average age of non-hospitalized patients is around 40 years old, while the hospitalized patients age it is close to 55 years. The most sensitive comorbidities in hospitalized patients are three principal: obesity, diabetes mellitus and hypertension. The patients whose needed the mechanical respirator were in ranged from 7.45% to 10.79%. ConclusionsThere is a higher risk of lose their lives in the Region 1 and Region 4 territories than in the Region 2, this information was dictated by the statistical analysis..