Assessing the Nationwide COVID-19 Risk in Mexico through the Lens of Comorbidity by an XGBoost-Based Logistic Regression Model

Abstract

The outbreak of the new COVID-19 disease is a serious health problem that has affected a large part of the world population, especially older adults and people who suffer from a previous comorbidity. In this work, we proposed a classifier model that allows for deciding whether or not a patient might suffer from the COVID-19 disease, considering spatio-temporal variables, physical characteristics of the patients and the presence of previous diseases. We used XGBoost to maximize the likelihood function of the multivariate logistic regression model. The estimated and observed values of percentage occurrence of cases were very similar, and indicated that the proposed model was suitable to predict new cases (AUC = 0.75). The main results revealed that patients without comorbidities are less likely to be COVID-19 positive, unlike people with diabetes, obesity and pneumonia. The distribution function by age group showed that, during the first and second wave of COVID-19, young people aged ≤20 were the least affected by the pandemic, while the most affected were people between 20 and 40 years, followed by adults older than 40 years. In the case of the third and fourth wave, there was an increased risk for young individuals (under 20 years), while older adults over 40 years decreased their chances of infection. Estimates of positive COVID cases with both the XGBoost-LR model and the multivariate logistic regression model were used to create maps to visualize the spatial distribution of positive cases across the country. Spatial analysis was carried out to determine, through the data, the main geographical areas where a greater number of positive cases occurred. The results showed that the areas most affected by COVID-19 were in the central and northern regions of Mexico.

Risk Factors Associated with COVID-19 and Gastrointestinal Manifestations in Older Adult Patients

“…Similarly, studies in Mexico have reported that diabetes and pneumonia increase the risk of COVID-19 in both adult and older populations [2,39]. They also report that obesity and smoking increase the risk of COVID-19 [2,39]. However, our study shows that hypertension increases the risk of COVID-19, unlike other studies conducted on the Mexican population [2].…”

“…In our study population, type 2 diabetes, hypertension, and respiratory diseases were associated with an increased risk of developing COVID-19. Similarly, studies in Mexico have reported that diabetes and pneumonia increase the risk of COVID-19 in both adult and older populations [2,39]. They also report that obesity and smoking increase the risk of COVID-19 [2,39].…”

COVID-19 infection and mortality among non-pregnant indigenous adults in Mexico 2020-2022: Impact of marginalisation

“…In our model, asthma lowered the probability 1.09-fold of COVID-19 fatality, possibly related to glucocorticoid asthma treatments available over the counter in Mexico. Other analyses of COVID-19 mortality in Mexico have reported reduced risk of hospitalisation among asthmatics [ 27 ], or no significant effect of asthma on mortality [ 39 ]. A systematic review and meta-analysis of 62 studies that included 2 457 205 individuals found a reduced risk of mortality among individuals with asthma [ 40 ].…”

Hospitalized COVID‐19 patients with diabetes have an increased risk for pneumonia, intensive care unit requirement, intubation, and death: A cross‐sectional cohort study in Mexico in 2020

“…2,3 Latin America continues to a high burden of active COVID-19 cases. [4][5][6] Most COVID-19 infected individuals recover without the need for specialized medical care, and many do not exhibit any symptoms. 7,8 The severity of the disease is modulated by coexisting medical disorders.…”

“…Over 200,000,000 individuals, or roughly 75% of the world's population, have gotten at least one dose of a vaccination 2,3 . Latin America continues to a high burden of active COVID‐19 cases 4‐6 …”