Author:
Nolasco-Jáuregui Oralia,Quezada-Téllez L. A.,Salazar-Flores Y.,Díaz-Hernández Adán
Abstract
In December 2019, the COVID-19 pandemic began, which has claimed the lives of millions of people around the world. This article presents a regional analysis of COVID-19 in Mexico. Due to comorbidities in Mexican society, this new pandemic implies a higher risk for the population. The study period runs from 12 April to 5 October 2020 761,665. This article proposes a unique methodology of random matrix theory in the moments of a probability measure that appears as the limit of the empirical spectral distribution by Wigner's semicircle law. The graphical presentation of the results is done with Machine Learning methods in the SuperHeat maps. With this, it was possible to analyze the behavior of patients who tested positive for COVID-19 and their comorbidities, with the conclusion that the most sensitive comorbidities in hospitalized patients are the following three: COPD, Other Diseases, and Renal Diseases.
Subject
Applied Mathematics,Statistics and Probability
Reference44 articles.
1. The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health, The latest 2019 novel coronavirus outbreak in Wuhan, China;Hui;Int J Infec Dis.,2020
2. COVID-19 por SARS-CoV-2: la nueva emergencia de salud2138
Miranda-NovalesMG
Vargas-AlmanzaI
Aragón-NogalesR
10.35366/91871.Revista Mexicana de Pediatr-a.862020
3. Another decade, another coronavirus;Perlman;N Engl J Med.,2020
4. Strong asymptotic freeness for Wigner and Wishart matrices;Capitaine;Indiana Univer Math J.,2007
5. Circular law for random matrices with exchangeable entries;Adamczak;Random Struct Algor.,2016