Numerical solution of rotavirus model using Runge-Kutta-Fehlberg method, differential transform method and Laplace Adomian decomposition method

Abstract

This paper explores the numerical analysis of a model for the challenging childhood disease named Rotavirus, by examining the impact of reducing risk. Specifically, the numerical approximation solution of the rotavirus model is investigated using three different numerical methods; the Runge-Kutta-Fehlberg technique, differential transformation method, and the Laplace Adomian decomposition method. The effectiveness and accuracy of these methods are compared, and conclusions are drawn regarding their suitability for obtaining approximate solutions to modeling problems. Additionally, the effect of reducing the risk of infection on the susceptible and vaccinated populations has been studied, leading to interesting findings. This research provides valuable insights into the application of numerical methods to model infectious diseases and may be useful for researchers.