Modelling the effect of telegraph noise in the SIRS epidemic model using Markovian switching

Greenhalgh, D. and Liang, Y. and Mao, X. (2016) Modelling the effect of telegraph noise in the SIRS epidemic model using Markovian switching. Physica A: Statistical Mechanics and its Applications, 462. pp. 684-704. ISSN 0378-4371

[img]
Preview
Text (Greenhalgh-etal-PA-2016-effect-telegraph-noise-in-the-SIRS-epidemic-model)
Greenhalgh_etal_PA_2016_effect_telegraph_noise_in_the_SIRS_epidemic_model.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (568kB)| Preview

    Abstract

    We discuss the effect of introducing telegraph noise, which is an example of an environmental noise, into the susceptible-infectious-recovered-susceptible (SIRS) model by examining the model using a finite-state Markov Chain (MC). First we start with a two-state MC and show that there exists a unique nonnegative solution and establish the conditions for extinction and persistence. We then explain how the results can be generalised to a finite-state MC. The results for the SIR (Susceptible-Infectious-Removed) model with Markovian Switching (MS) are a special case. Numerical simulations are produced to confirm our theoretical results.