Diabetes‎, ‎Hypertension‎, ‎Obesity‎, ‎and Age as Predictors of Severe COVID-۱۹‎: ‎A Mathematical Modeling Study

Objective: To analyze an epidemiological model of coronavirus disease ۲۰۱۹ (COVID-۱۹) transmission and identify patient characteristics associated with disease severity‎.‎Materials and Methods: An extended SIR-based compartmental model was developed‎, ‎incorporating asymptomatic/symptomatic classes‎, ‎hospitalization‎, ‎ intensive care unit (ICU) admission‎, ‎mortality‎, ‎reinfection‎, ‎and environmental transmission‎. ‎The basic reproduction number ‎ ) was derived‎, ‎and stability analysis was performed using Routh-Hurwitz and Castillo-Chavez criteria‎. ‎Numerical simulations were conducted using MATLAB with data from Mashhad University of Medical Sciences‎.Results: The disease-free equilibrium is stable when ‎ <۱‎. ‎Clinical findings show‎: ‎diabetic patients are twice as likely to develop severe symptoms; hypertensive patients have a ۳.۵-fold higher risk (۲۰% mortality vs‎. ‎۰.۷%); men have seven-fold higher mortality than women; older adults (>۴۰ years) show increased severity; and obese patients (BMI ≥۳۰) have worse outcomes‎.Conclusion: is a critical parameter for disease-free equilibrium stability‎. ‎Comorbidities (diabetes‎, ‎hypertension‎, ‎obesity) and demographic factors (older age‎, ‎male gender) significantly increase the risk of severe COVID-۱۹ outcomes‎.

کلیدواژه ها:

COVID-۱۹ ، Diabetes ، Hypertension ، mathematical modeling ، stability analysis