Spatial Survival Model for COVID-19 in México

• Published in: Healthcare (Basel) Vol. 12; no. 3; p. 306
• Main Authors: Pérez-Castro, Eduardo, Guzmán-Martínez, María, Godínez-Jaimes, Flaviano, Reyes-Carreto, Ramón, Vargas-de-León, Cruz, Aguirre-Salado, Alejandro Iván
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.01.2024
• Subjects: Analysis; bayesian methodology; Chronic obstructive pulmonary disease; Comorbidity; COVID-19; Dengue fever; Diabetes; Health surveillance; Hypertension; Kidney diseases; Laboratories; Mortality; Pandemics; Parameter estimation; Patients; Pneumonia; Population density; proportional hazard frailty model; Risk factors; Severe acute respiratory syndrome coronavirus 2; Software; spatial correlation; Survival analysis; survival time; Mexico; Baja California Mexico; bayesian methodology; spatial correlation; survival time; proportional hazard frailty model
• ISSN: 2227-9032; 2227-9032
• DOI: 10.3390/healthcare12030306

A spatial survival analysis was performed to identify some of the factors that influence the survival of patients with COVID-19 in the states of Guerrero, México, and Chihuahua. The data that we analyzed correspond to the period from 28 February 2020 to 24 November 2021. A Cox proportional hazards frailty model and a Cox proportional hazards model were fitted. For both models, the estimation of the parameters was carried out using the Bayesian approach. According to the DIC, WAIC, and LPML criteria, the spatial model was better. The analysis showed that the spatial effect influences the survival times of patients with COVID-19. The spatial survival analysis also revealed that age, gender, and the presence of comorbidities, which vary between states, and the development of pneumonia increase the risk of death from COVID-19.