Modeling and sensitivity analysis of HBV epidemic model with convex incidence rate

Khan, Amir; Zarin, Rahat; Hussain, Ghulam; Usman, Auwalu Hamisu; Humphries, Usa Wannasingha; Gómez‐Aguilar, J.F.

doi:10.1016/j.rinp.2021.103836

Cited by 28 publications

(12 citation statements)

References 23 publications

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“…initial value: (u 10 (x), u 20 (x), u 30 (x)) = (sin πx 60 , sin πx 60 , sin πx 60 ). In Figure 1, we can see the existence of the stationary distribution of the solution of system (8). The two-dimensional figure on the right shows the changes in time of the solution in different Spaces, and it can be seen that the stationary distribution of the solution is different in different Spaces.…”

Section: Numerical Simulationsmentioning

confidence: 96%

“…Next, we introduce a lemma that gives a criterion for the existence of an ergodic stationary distribution to system (8).…”

Section: Existence and Unique Of Solutionmentioning

confidence: 99%

“…Lemma 3.1. For any initial data (u 10 , u 20 , u 30 ), the solution u(x, t) = (u 1 (x, t), u 2 (x, t), u 3 (x, t)) of system (8), satisfies that…”

Section: Existence and Unique Of Solutionmentioning

confidence: 99%

“…Meanwhile, much work can be found on the dynamic behavior of HBV infection model [1][2][3][4][5][6][7][8][9][10]. For example, Din and Li [4] built stochastic HBV model with Markov switching and white noise, and verified the results of the theorem using runge Kutta method.…”

Section: Introductionmentioning

confidence: 99%

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Stationary distribution of a reaction-diffusion hepatitis B virus infection model driven by Ornstein-Uhlenbeck process

Liang

Chang

2022

Preprint

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In this paper, we investigate a reaction-diffusion hepatitis B virus (HBV) infection model with mean-reverting Ornstein-Uhlenbeck process. For the model, the existence and uniqueness of the positive solution are proved, and the sufficient conditions is given of stationary distribution of solution. Finally, the existence of the stationary distribution is verified by numerical simulation, and the influence of noise intensity on disease was given. At the same time, it can also be observed that infected cells and viruses are susceptible to stochastic factors. Therefore, in order to better control the development of the disease, external interference of viruses and infected cells can be avoided or reduced as much as possible.

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Section: Numerical Simulationsmentioning

confidence: 96%

“…Next, we introduce a lemma that gives a criterion for the existence of an ergodic stationary distribution to system (8).…”

Section: Existence and Unique Of Solutionmentioning

confidence: 99%

“…Lemma 3.1. For any initial data (u 10 , u 20 , u 30 ), the solution u(x, t) = (u 1 (x, t), u 2 (x, t), u 3 (x, t)) of system (8), satisfies that…”

Section: Existence and Unique Of Solutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Stationary distribution of a reaction-diffusion hepatitis B virus infection model driven by Ornstein-Uhlenbeck process

Liang

Chang

2022

Preprint

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“…After The first attempt of Mckendrick and Kermack [7] , [8] the said models were highly analyzed for controlling of different diseases. Using this gate way and basic concepts, different researchers analyzed the epidemic models of SEIS, SEIRS, SIRS, vaccinated models and delay-models by including different parameter for vaccination and delay-time [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] .…”

Section: Introductionmentioning

confidence: 99%

Stochastic COVID-19 SEIQ epidemic model with time-delay

et al. 2021

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In this work, we consider an epidemic model for corona-virus (COVID-19) with random perturbations as well as time delay, composed of four different classes of susceptible population, the exposed population, the infectious population and the quarantine population. We investigate the proposed problem for the derivation of at least one and unique solution in the positive feasible region of non-local solution. For one stationary ergodic distribution, the necessary result of existence is developed by applying the Lyapunov function in the sense of delay-stochastic approach and the condition for the extinction of the disease is also established. Our obtained results show that the effect of Brownian motion and noise terms on the transmission of the epidemic is very high. If the noise is large the infection may decrease or vanish. For validation of our obtained scheme, the results for all the classes of the problem have been numerically simulated.

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Modeling and analysis of the fractional-order epidemic model to investigate mutual influence in HIV/HCV co-infection

Naik,

Yeolekar,

Qureshi

et al. 2024

Nonlinear Dyn

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Modeling and sensitivity analysis of HBV epidemic model with convex incidence rate

Cited by 28 publications

References 23 publications

Stationary distribution of a reaction-diffusion hepatitis B virus infection model driven by Ornstein-Uhlenbeck process

Stationary distribution of a reaction-diffusion hepatitis B virus infection model driven by Ornstein-Uhlenbeck process

Stochastic COVID-19 SEIQ epidemic model with time-delay

Modeling and analysis of the fractional-order epidemic model to investigate mutual influence in HIV/HCV co-infection

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