Mathematical model for understanding the relationship between diabetes and novel coronavirus
No Thumbnail Available
Date
2025
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
A new model is proposed to explore interactions between diabetes and novel coronavirus. The model accounted
for both the omicron variant and variants varying from omicron. The model investigated compartments such as
hospitalization, diabetes, co-infection, omicron variant, and quarantine. Additionally, the impact of different
vaccination doses is assessed. Sensitivity analysis is carried out to determine disease prevalence and control
options, emphasizing the significance of knowing epidemics and their characteristics. The model is validated
using actual data from Japan. The parameters are fitted with the help of ”Least Square Curve Fitting” method to
describe the dynamic behavior of the proposed model. Simulation results and theoretical findings demonstrate
the dynamic behavior of novel coronavirus and diabetes mellitus (DM). Biological illustrations that illustrate
impact of model parameters are evaluated. Furthermore, effect of vaccine efficacy and vaccination rates for the
vaccine’s first, second, and booster doses is conducted. The impact of various preventive measures, such as
hospitalization rate, quarantine or self-isolation rate, vaccine dose-1, dose-2, and booster dose, is considered for
diabetic individuals in contact with symptomatic or asymptomatic COVID-19 infectious people in the proposed
model. The findings demonstrate the significance of vaccine doses on people with diabetes and individuals in
fectious with omicron variant. The proposed work helps with subsequent prevention efforts and the design of a
vaccination policy to mitigate the effect of the novel coronavirus.