Abstract

In this paper we propose the balanced implicit numerical techniques for maintaining the nonnegative path of the solution in stochastic susceptible–infected–vaccinated–susceptible (SIVS) epidemic model. We can hardly acquire the explicit solution for the SIVS model, so we often use the numerical scheme to produce approximate solutions. The Euler–Maruyama (EM) method is a useful and effective means in producing numerical solutions of SIVS model. The EM method to simulate the stochastic SIVS model often results in the problem that the numerical solution is not positive. In order to eliminate the negative path of the solution in a stochastic SIVS epidemic model, we construct a numerical method preserving positivity for the SIVS model. It is proved that the balanced implicit method (BIM) can preserve positivity and we show the convergence of the BIM numerical approximate solution to the exact solution. Finally, a numerical example is offered to support the theoretical results and verify the availability of the approach.

Highlights

  • IntroductionRecent global infectious diseases (such as the outbreak of H7N9 influenza in 2013 and Ebola disease in 2014) resulted in a lot of biological deaths and substantial financial ruins

  • Recent global infectious diseases resulted in a lot of biological deaths and substantial financial ruins

  • The main purpose of this present paper is to structure a new method to maintain the nonnegative path of the solution for a stochastic epidemic SIVS model, which is the balanced implicit method

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Summary

Introduction

Recent global infectious diseases (such as the outbreak of H7N9 influenza in 2013 and Ebola disease in 2014) resulted in a lot of biological deaths and substantial financial ruins. The modeling of infection diseases is extremely important to research the mechanisms of diseases. A mathematical model is considered as an effective way to forecast the outbreak of disease. Stochastic epidemic models have come to play an important role in the control of diseases, which is an extremely significant tool to account for the real world. The SIVS epidemic model is one of the most important models in epidemiology and biomathematics. Many authors have analyzed the susceptible–infected– susceptible (SIS) epidemic model with vaccination. Shi et al [1] analyzed the effect of impulsive vaccination on a susceptible–infected–recovered (SIR) epidemic model. In [2], Nie et al presented the existence and orbital stability of an order-1 or order-2 periodic solution for the SIVS model. Omondi et al [4] analyzed a mathematical model

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