Real data-based optimal control strategies for assessing the impact of the Omicron variant on heart attacks

Abstract

This paper presents an investigation into the relationship between heart attacks and the Omicron variant, employing a novel mathematical model. The model incorporates two adjustable control parameters to manage the number of infected individuals and individuals with the Omicron variant. The study examines the model's positivity and boundedness, evaluates the reproduction number (R0), and conducts a sensitivity analysis of the control parameters based on the reproduction number. The model's parameters are estimated using the widely utilized least squares curve fitting method, employing real COVID-19 cases from Türkiye. Finally, numerical simulations demonstrate the efficacy of the suggested controls in reducing the number of infected individuals and the Omicron population.