2018
DOI: 10.1002/mma.5115
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Dynamics of DS‐I‐A epidemic model with multiple stochastic perturbations

Abstract: In this paper, we investigate the dynamics behavior of DS-I-A epidemic model with multiple stochastic perturbations. Sufficient conditions for extinction of disease are established. Especially, we conclude that there is a stationary distribution for the stochastic system and it has ergodicity under appropriate conditions. At last, some examples and simulations are provided to illustrate our results.KEYWORDS ergodicity, extinction, infectious disease models, multiple stochastic perturbations, stationary Markov … Show more

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Cited by 2 publications
(2 citation statements)
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“…Similarly to the first part, we can obtain for R ′ (g) > 0 and ρ large enough Therefore, to complete the proof, it suffices to use Rayleigh's principle in [17] and [18]. □…”
Section: □ 4 Stationary Distributionmentioning
confidence: 76%
“…Similarly to the first part, we can obtain for R ′ (g) > 0 and ρ large enough Therefore, to complete the proof, it suffices to use Rayleigh's principle in [17] and [18]. □…”
Section: □ 4 Stationary Distributionmentioning
confidence: 76%
“…Motivated by such a fact, the extension of deterministic models to the stochastic case by adding different types of noise has been established by many researchers. In the context of Gaussian white noise, we refer, for instance, to earlier studies [11][12][13][14][15][16][17][18], in which the authors considered a Gaussian white noise in the disease transmission rate, while we refer to other works [19][20][21][22][23][24][25], in which a multiplicative Gaussian white noise was chosen. One limitation of the previous type of noise is its incapacity to incorporate the sudden severe changes within the studied population; such changes are exhibited for instance by earthquakes, hurricanes and volcanoes [26].…”
Section: Introductionmentioning
confidence: 99%