Numerical Solution of Stochastic SEIQR epidemic model with Differential Transformation Method

Abstract

In this we solve the Policy Decision-Making for quarantine Policy. The quarantine variable in the SEIQR model enables the policy-makers to examine the relative impact of isolation measures on controlling disease transmission. Real-World Disease Modeling can be used to model different infectious diseases like COVID-19, SARS, MERS and influenza, where quarantine is an important factor. The Reproduction Number and Disease Dynamics, derivation of equilibrium points under which a disease dies out or continues to multiple. The research compares (DTM) with the (RK4) method to determine its accuracy and efficiency. The aim of this research is to examine the application of the differential transformation to determine the approximate solutions to the SEIQR epidemiology model. In solving differential and integral equations, numerical and semi-analytical techniques are employed respectively through this method. Through the application of the DTM (Differential Transformation Method), a SEIQR model was solved and two cases were discussed, one of which is endemic and another is disease-free case. In addition, we solve the solutions using Runge-Kutta method of order four. At last, we compare both the solutions obtained by using Differential Transformation Method (DTM) and the (RK4) method. The solution, so obtained is more precise to use than DTM.