Abstract

This paper analyzes the first integrals and exact solutions of mathematical models of epidemiology via the partial Lagrangian approach by replacing the three first-order nonlinear ordinary differential equations by an equivalent system containing one second-order equation and a first-order equation. The partial Lagrangian approach is then utilized for the second-order ODE to construct the first integrals of the underlying system. We investigate the SIR and HIV models. We obtain two first integrals for the SIR model with and without demographic growth. For the HIV model without demography, five first integrals are established and two first integrals are deduced for the HIV model with demography. Then we utilize the derived first integrals to construct exact solutions to the models under investigation. The dynamic properties of these models are studied too. Numerical solutions are derived for SIR models by finite difference method and are compared with exact solutions.

Highlights

  • Epidemiology has become an exciting area for the modern application of mathematics

  • The results reported in the analysis of human immunodeficiency virus (HIV) transmission in San Francisco [10] were replicated through a mathematical model developed by Anderson [11]

  • The system of first-order ODEs is replaced by a system containing at least one second-order ODE in order to obtain a partial Lagrangian to the system

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Summary

Introduction

Epidemiology has become an exciting area for the modern application of mathematics. Mathematical models play a vital role in analyzing the spread and control of different diseases. The study of mathematical models of epidemiology is essential in order to uncover the essential aspects of infectious diseases spread and helps public health decision makers to compare, plan, evaluate, and implement different control programs [14, 15]. Leach and Andriopoulos [28] utilized the Lie group method to predict the cause of infectious diseases and compare the effects of different control strategies for SARS (Severe Acute Respiratory Syndrome) epidemic of 2002-2003. We utilize these first integrals to find the reductions and exact solutions of the model.

Preliminaries
An HIV-Transmission Model with and without Demography
Conclusions
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