Control strategies for examining the effects of the Omicron variant on heart attacks by utilizing real data

Abstract

An investigation of the correlation between heart attack and the Omicron variant is presented in this paper using a novel mathematical model. In the model, in order to control both the number of infected individuals and the number of those with the Omicron variant, two control parameters are meant to be adjusted. Additionally, the model’s positivity and boundedness are investigated. The reproduction number (R0) is assessed, and the control parameter sensitivity analysis is carried out in accordance with the reproduction number. Using the least squares curve fitting method, which is one of the most popular methods of estimating the model’s parameters, the values of the model’s parameters are determined. The model’s total 16 parameter values are estimated utilizing real COVID-19 cases from Tu¨rkiye. Lastly, numerical simulations are presented for the purpose of analyzing the system’s dynamical behavior. Numerical simulations have shown that the suggested controls are successful in reducing the number of infected and Omicron population.