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Risk Factors Associated with COVID-19 Lethality: A Machine Learning Approach Using Mexico Database.

Alejandro Carvantes-Barrera1, Lorena Díaz-González2, Mauricio Rosales-Rivera3

  • 1Maestría en Optimización y Cómputo Aplicado, Universidad Autónoma del Estado de Morelos, Cuernavaca, 62209, Morelos, México.

Journal of Medical Systems
|August 19, 2023
PubMed
Summary
This summary is machine-generated.

Pneumonia and advanced age are key predictors of COVID-19 death. Medical unit type, like IMSS, and factors such as intubation and diabetes also significantly impact patient outcomes in Mexico.

Keywords:
Extreme Gradient Boosting (XGBoost)Human Development IndexPoint Biserial CorrelationProtective factorRisk factorSHapley additive exPlanation (SHAP)

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Area of Science:

  • Epidemiology
  • Public Health
  • Data Science

Background:

  • Identifying COVID-19 lethality risk factors is critical for pandemic control.
  • Mexico's diverse demographics and healthcare system present unique challenges.

Purpose of the Study:

  • To develop and analyze predictive models for COVID-19 lethality.
  • To identify key demographic, comorbidity, and healthcare-related risk factors for COVID-19 mortality in Mexico.

Main Methods:

  • Utilized Extreme Gradient Boosting (XGBoost) for predictive modeling.
  • Employed Shapley values to interpret feature importance.
  • Analyzed data from confirmed COVID-19 cases in Mexico (Feb 2020 - Apr 2022).

Main Results:

  • Pneumonia and advanced age were the strongest predictors of death across all epidemiological waves.
  • IMSS medical units were high-risk, while SSA units were protective. Intubation was a significant risk factor, especially in earlier waves.
  • Female gender and younger age groups (18-29) were protective factors; middle age (50-59), diabetes, obesity, hypertension, and low Human Development Index were risk factors.

Conclusions:

  • The study identified critical, wave-specific risk factors for COVID-19 lethality in Mexico.
  • Findings can inform targeted public health interventions to reduce mortality.
  • Healthcare system structure and socioeconomic factors play a significant role in COVID-19 outcomes.