Gegenbauer Wavelet Solutions of the Sir and Sitr Systems of the Covid-19 Disease

Abstract

This study aimed to investigate the influence of various parameters on the solutions of the susceptible-infected-recovered (SIR) and susceptible-treated-infectious-recovering (SITR) models to describe the spread of COVID-19. To achieve this, we employ the Gegenbauer wavelet technique to convert the system of nonlinear differential equations into a system of nonlinear algebraic equations. This approach has the advantage of not requiring the linearization of the nonlinear expressions, which significantly reduces truncation errors commonly associated with other methods. We conduct a thorough comparison of the absolute and residual errors generated by this technique against those produced by other numerical methods, finding that our results demonstrate a high level of accuracy. Additionally, the Gegenbauer wavelet technique is not only efficient but also straightforward to implement, contributing to a lower CPU time requirement. Overall, this study highlights the effectiveness of the Gegenbauer wavelet technique in accurately modeling the dynamics of COVID-19 transmission while offering practical computational advantages.