2020
DOI: 10.1155/2020/9676501
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Ergodic Stationary Distribution of a Stochastic Hepatitis B Epidemic Model with Interval-Valued Parameters and Compensated Poisson Process

Abstract: Hepatitis B epidemic was and is still a rich subject that sparks the interest of epidemiological researchers. The dynamics of this epidemic is often modeled by a system with constant parameters. In reality, the parameters associated with the Hepatitis B model are not certain, but the interval in which it belongs to can readily be determined. Our paper focuses on an imprecise Hepatitis B model perturbed by Lévy noise due to unexpected environmental disturbances. This model has a global positive solution. Under … Show more

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Cited by 25 publications
(9 citation statements)
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“…Herein, we construct a suitable stochastic Lyapunov function to study the existence of a unique ergodic stationary distribution [ 29 , 30 ] of the positive solutions to the system (2).…”
Section: Stationary Distributionmentioning
confidence: 99%
“…Herein, we construct a suitable stochastic Lyapunov function to study the existence of a unique ergodic stationary distribution [ 29 , 30 ] of the positive solutions to the system (2).…”
Section: Stationary Distributionmentioning
confidence: 99%
“…In order to discuss the impact of body environmental factors on the dynamics of cancer infection, we could extend the deterministic description of the tumor-immune interaction to include stochastic forcing, either additively or multiplicatively. Several researchers have studied mathematical models for studying epidemics in environmental noise, such as [27].…”
Section: Stochastic Model For Tumor-immune Interactionmentioning
confidence: 99%
“…), these disturbances can brutally affect the solution in some cases, thus breaking its continuity [57] , [58] , [59] . Moreover, the impact of human interventions, economic crises, and uncontrolled flow of people may have cruel consequences on epidemiological systems and this cannot be described by using differential systems driven by white noise [60] , [61] , [62] , [63] , [64] . Consequently, we should employ the stochastic differential equation with significant discontinuities, so-called jumps [65] .…”
Section: Introductionmentioning
confidence: 99%