Modeling and dynamic analysis of a stochastic mutualism model with distributed delays

Stochastic mutualism model with Lévy jumps

In this paper, we consider a stochastic food chain chemostat model with variable yields. First, we prove the stochastic model has a unique global positive solution. Second, by employing suitable Lyapunov functions, Itô[Formula: see text] formula and some other important inequalities, the existence of a unique ergodic stationary distribution of a stochastic food chain chemostat model is researched, which can help us better understand the statistical characteristics of stochastic food chain chemostat models. Second, we investigate the extinction of the microorganism and the bacteria. Moreover, the case of extinction for bacteria but persistence for microbial species is considered. Finally, some numerical simulations are carried out to illustrate our theoretical results and the influence of the variable yields on the microorganism and the bacteria.

A stochastic SIRS epidemic model with nonlinear incidence rate

A remark on stationary distribution of a stochastic SIR epidemic model with double saturated rates

A stochastic mutualism model is proposed and investigated in this paper. We show that there is a unique solution to the model for any positive initial value. Moreover, we show that the solution is stochastically bounded, uniformly continuous and globally attractive. Under some conditions, we conclude that the stochastic model is stochastically permanent and persistent in mean. Finally, we introduce some figures to illustrate our main results.

Bifurcation dynamics in a stochastic population model with Beverton–Holt growth

A stochastic SICA model for HIV/AIDS transmission

<abstract><p>The spread of infectious diseases are inevitably affected by natural and social factors, and their evolution presents oscillations and other uncertainties. Therefore, it is of practical significance to consider stochastic noise interference in the studies of infectious disease models. In this paper, a stochastic SIR model with nonlinear incidence and recovery rate is studied. First, a unique global positive solution for any initial value of the system is proved. Second, we provide the sufficient conditions for disease extinction or persistence, and the influence of threshold $ \tilde{R_{0}} $ of the stochastic SIR model on disease state transition is analyzed. Additionally, we prove that the system has a stationary distribution under some given parameter conditions by building an appropriate stochastic Lyapunov function as well as using the equivalent condition of the Hasminskii theorem. Finally, the correctness of these theoretical results are validated by numerical simulations.</p></abstract>

Rumor propagation in the new media era poses a huge threat to maintaining the normal order of social life. In this context, we put forth a nonlinear dynamics-based stochastic SICR rumor model that integrates media coverage with science education. First, the existence of a unique global positive solution is obtained. Second, sufficient conditions for extinction are constructed on the spread of rumors based on the Lyapunov function methods and Khasminskii’s theory. Finally, the theoretical analysis is verified through numerical simulations. Additionally, it demonstrates how rumor spreading can be hampered by media coverage.

Cholera is a life-threatening form of diarrhoea resulting from a bacterial infection of the gastrointestinal system caused by Vibrio cholerae. The aim of this article is to explore the dynamic characteristics of cholera disease transmission and the equilibrium level of recovery in a stochastic cholera framework by adopting piecewise fractional differential operator approaches. Firstly, we provide a detailed fractional-order form of the cholera model, showing the system’s positivity and boundedness. Meanwhile, equilibrium analysis is performed to comprehend the model’s behaviour and stability for disease-free as well as endemic-free equilibrium. Bacterial development rates have been reported to correlate with the Allee phenomenon. The resulting system exhibits multi-stability for forward and saddle-node bifurcations based on various settings. Global sensitivity is calculated employing the partial rank correlation coefficient approach. Furthermore, the model analyzes a stochastic fractional cholera system. Through a rigorous analysis, we demonstrate that the stochastic model offers a unique global positive solution. Lyapunov function theory is used to create criteria that ensure the model’s unique erogodic stationary distribution at 1$$\\end{document}]]>. Afterwards, the phenomenon that excessive noises can result in the elimination of cholera is discovered. Moreover, this model enables us to study a range of behaviors, from bridging to unpredictability, helping us to understand and predict the process from the beginning to the end of the virus. Moreover, the piecewise differential operators have chosen to extend novel pathways for researchers across several fields, enabling them to convey unique features in various time periods. These operators can be gathered with classical, Caputo, Atangana-Baleanu-Caputo fractional derivative, and random perturbation. As a result, the analytical insights are validated using computational modeling, providing a novel viewpoint on spreading diseases in a societal environment.

Stochastic characteristics of a chemostat model with variable yield

Ergodic stationary distribution and extinction of a hybrid stochastic SEQIHR epidemic model with media coverage, quarantine strategies and pre-existing immunity under discrete Markov switching

A stochastic SIS-type epidemic model with general nonlinear incidence and disease-induced mortality is investigated. It is proved that the dynamical behaviors of the model are determined by a certain threshold value . That is, when and together with an additional condition, the disease is extinct with probability one, and when , the disease is permanent in the mean in probability, and when there is not disease-related death, the disease oscillates stochastically about a positive number. Furthermore, when , the model admits positive recurrence and a unique stationary distribution. Particularly, the effects of the intensities of stochastic perturbation for the dynamical behaviors of the model are discussed in detail, and the dynamical behaviors for the stochastic SIS epidemic model with standard incidence are established. Finally, the numerical simulations are presented to illustrate the proposed open problems.

This paper formulates an infected predator-prey model with Beddington-DeAngelis functional response from a classical deterministic framework to a stochastic differential equation (SDE). First, we provide a global analysis including the global positive solution, stochastically ultimate boundedness, the persistence in mean, and extinction of the SDE system by using the technique of a series of inequalities. Second, by using Ito’s formula and Lyapunov methods, we investigate the asymptotic behaviors around the equilibrium points of its deterministic system. The solution of the stochastic model has a unique stationary distribution, it also has the characteristics of ergodicity. Finally, we present a series of numerical simulations of these cases with respect to different noise disturbance coefficients to illustrate the performance of the theoretical results. The results show that if the intensity of the disturbance is sufficiently large, the persistence of the SDE model can be destroyed.

Smoking has gradually become a very common behavior, and the related situation in different groups also presents different forms. Due to the differences of individual smoking cessation time and the interference of environmental factors in the spread of smoking behavior, we establish a stochastic giving up smoking model with quit-smoking duration. We also consider the saturated incidence rate. The total population is composed of potential smokers, smokers, quitters and removed. By using Itô's formula and constructing appropriate Lyapunov functions, we first ensure the existence of a unique global positive solution of the stochastic model. In addition, a threshold condition for extinction and permanence of smoking behavior is deduced. If the intensity of white noise is small, and $ \widetilde{\mathcal{R}}_0 < 1 $, smokers will eventually become extinct. If $ \widetilde{\mathcal{R}}_0 > 1 $, smoking will last. Then, the sufficient condition for the existence of a unique stationary distribution of the smoking phenomenon is studied as $ R_0^s > 1 $. Finally, conclusions are explained by numerical simulations.