Comparison of Some Numerical Simulation Techniques for COVID-19 Model in Iraq

Authors

  • Maha A. Mohammed Mathematical Department, College of Education for Pure Science (Ibn al-Haytham), University of Baghdad, Iraq
  • Mahdi A. Sabea Department of Mathematics, College of Education for Pure Science (Ibn al-Haytham), University of Baghdad,Iraq
  • Noor Fadiya Mohd Noor Institute of Mathematical Sciences Faculty of Science Universiti Malaya, Malaysia

DOI:

https://doi.org/10.30526/36.3.2945

Keywords:

Epidemic models, Coronavirus (COVID-19) model, Runge-Kutta method, Simulation process, Numerical simulation techniques.

Abstract

The aim of our study is to solve a nonlinear epidemic model, which is the COVID-19 epidemic model in Iraq, through the application of initial value problems in the current study. The model has been presented as a system of ordinary differential equations that has parameters that change with time. Two numerical simulation methods are proposed to solve this model as suitable methods for solving systems whose coefficients change over time. These methods are the Mean Monte Carlo Runge-Kutta method (MMC_RK) and the Mean Latin Hypercube Runge-Kutta method (MLH_RK). The results of numerical simulation methods are compared with the results of the numerical Runge-Kutta 4th order method (RK4) from 2021 to 2025 using the absolute error, which proves that the MLH_RK method is the best and closest to the expected values. The results have been discussed after being tabulated and represented graphically. Epidemic behavior for the next two years until 2025 has been projected using the proposed methods.

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Published

20-Jul-2023

Issue

Section

Mathematics

Publication Dates