Análisis estadístico y árboles de decisión para identificar factores de riesgo en la población mexicana por la pandemia de COVID-19

Itzel Paola Cervera Arguelles; Hermilo Sánchez Cruz

doi:10.56294/saludcyt2024790

Original

Published: 2024-05-07

DOI: https://doi.org/10.56294/saludcyt2024790

Statistical analysis and decision trees to identify risk factors in the Mexican population due to COVID-19 pandemic

Abstract

Introduction: The COVID-19 pandemic caused by the new SARS-CoV-2 virus was a big challenge to the world and was responsible for a vast number of deaths in a brief period; one of the countries with the greatest number of deaths was México. For this reason, studying this emergency is crucial.
Objective: study and compare the available statistics for Mexico about the COVID-19 pandemic and build a machine learning model that helps to identify the risk factors of the Mexican population.
Methods: This research is structured into three sections. Firstly, a worldwide and national statistical analysis, then a decision tree-based model, and lastly, research about the results of the vaccination campaign. Different databases were used to fulfill the objectives of each section.
Results: With international information, the number of cases and deaths were studied for a group of countries; in addition, this study compared daily cases and deceases in México, Colombia, and Spain. The national data was used to obtain different statistics and a decision tree-based model. For the vaccination campaign, various statistics were gathered.
Conclusions: Even though international statistics did not help determine if comorbidities had a significant effect on deceases, national statistics indicate that they were a risk factor for passing away due to COVID-19. Similarly, the decision tree model indicated that hospitalization was a common characteristic among deceased people. For the vaccination campaign, the lack of data was a problem in identifying the role this event had in the development of the pandemic; nevertheless, the international surveillance systems received an exceptional number of reports about adverse events; for this reason, each person should decide if they need a vaccine.

Keywords:

COVID-19 in México,

Statistics; Decision threes,

Risk factors,

Vaccination,

How to Cite

Cervera Arguelles IP, Sánchez Cruz H. Statistical analysis and decision trees to identify risk factors in the Mexican population due to COVID-19 pandemic. Salud, Ciencia y Tecnología [Internet]. 2024 May 7 [cited 2024 Jun. 6];4:790. Available from: https://revista.saludcyt.ar/ojs/index.php/sct/article/view/790

Copyright Notice

The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.

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