Stationary distribution of stochastic SIRS epidemic model with standard incidence

6Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

We study stochastic versions of a deterministic SIRS(Susceptible, Infective, Recovered, Susceptible) epidemic model with standard incidence. We study the existence of a stationary distribution of stochastic system by the theory of integral Markov semigroup. We prove the distribution densities of the solutions can converge to an invariant density in L1. This shows the system is ergodic. The presented results are demonstrated by numerical simulations.

References Powered by Scopus

Mathematics of infectious diseases

4962Citations
N/AReaders
Get full text

An algorithmic introduction to numerical simulation of stochastic differential equations

2609Citations
N/AReaders
Get full text

Population biology of infectious diseases: Part I

2232Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Dynamical analysis of a stochastic SIS epidemic model with nonlinear incidence rate and double epidemic hypothesis

66Citations
N/AReaders
Get full text

Dynamics of a stochastic sir model with both horizontal and vertical transmission

45Citations
N/AReaders
Get full text

Threshold Dynamics of a Stochastic SIR Model with Vertical Transmission and Vaccination

45Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Zhao, Y., Lin, Y., Jiang, D., Mao, X., & Li, Y. (2016). Stationary distribution of stochastic SIRS epidemic model with standard incidence. Discrete and Continuous Dynamical Systems - Series B, 21(7), 2363–2378. https://doi.org/10.3934/dcdsb.2016051

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 4

67%

Professor / Associate Prof. 1

17%

Researcher 1

17%

Readers' Discipline

Tooltip

Mathematics 4

100%

Save time finding and organizing research with Mendeley

Sign up for free