6 results
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2. SIRS epidemic modeling using fractional-ordered differential equations: Role of fear effect.
- Author
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Mangal, Shiv, Misra, O. P., and Dhar, Joydip
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DIFFERENTIAL equations , *FRACTIONAL differential equations , *EPIDEMICS , *HOPF bifurcations , *COMMUNICABLE diseases , *BASIC reproduction number , *CLASSICAL swine fever - Abstract
In this paper, an SIRS epidemic model using Grunwald–Letnikov fractional-order derivative is formulated with the help of a nonlinear system of fractional differential equations to analyze the effects of fear in the population during the outbreak of deadly infectious diseases. The criteria for the spread or extinction of the disease are derived and discussed on the basis of the basic reproduction number. The condition for the existence of Hopf bifurcation is discussed considering fractional order as a bifurcation parameter. Additionally, using the Grunwald–Letnikov approximation, the simulation is carried out to confirm the validity of analytic results graphically. Using the real data of COVID-19 in India recorded during the second wave from 15 May 2021 to 15 December 2021, we estimate the model parameters and find that the fractional-order model gives the closer forecast of the disease than the classical one. Both the analytical results and numerical simulations presented in this study suggest different policies for controlling or eradicating many infectious diseases. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
3. A stochastic SIS epidemic infectious diseases model with double stochastic perturbations.
- Author
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Chen, Xingzhi, Tian, Baodan, Xu, Xin, Yang, Ruoxi, and Zhong, Shouming
- Subjects
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COMMUNICABLE diseases , *BASIC reproduction number , *STOCHASTIC models , *DISEASE outbreaks , *EPIDEMICS , *HOPFIELD networks , *ORNSTEIN-Uhlenbeck process - Abstract
In this paper, a stochastic SIS epidemic infectious diseases model with double stochastic perturbations is proposed. First, the existence and uniqueness of the positive global solution of the model are proved. Second, the controlling conditions for the extinction and persistence of the disease are obtained. Besides, the effects of the intensity of volatility ξ 1 and the speed of reversion 1 on the dynamical behaviors of the model are discussed. Finally, some numerical examples are given to support the theoretical results. The results show that if the basic reproduction number ℛ 0 s < 1 , the disease will be extinct, that is to say that we can control the threshold ℛ 0 s to suppress the disease outbreak. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
4. Bifurcation analysis of an SIS epidemic model with a generalized non-monotonic and saturated incidence rate.
- Author
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Huang, Chunxian, Jiang, Zhenkun, Huang, Xiaojun, and Zhou, Xiaoliang
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BASIC reproduction number , *BIFURCATION theory , *HOPF bifurcations , *EPIDEMICS , *INFECTIOUS disease transmission , *PSYCHOLOGICAL factors , *DYNAMIC models - Abstract
In this paper, a new generalized non-monotonic and saturated incidence rate was introduced into a susceptible-infected-susceptible (SIS) epidemic model to account for inhibitory effect and crowding effect. The dynamic properties of the model were studied by qualitative theory and bifurcation theory. It is shown that when the influence of psychological factors is large, the model has only disease-free equilibrium point, and this disease-free equilibrium point is globally asymptotically stable; when the influence of psychological factors is small, for some parameter conditions, the model has a unique endemic equilibrium point, which is a cusp point of co-dimension two, and for other parameter conditions the model has two endemic equilibrium points, one of which could be weak focus or center. In addition, the results of the model undergoing saddle-node bifurcation, Hopf bifurcation and Bogdanov–Takens bifurcation as the parameters vary were also proved. These results shed light on the impact of psychological behavior of susceptible people on the disease transmission. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
5. Pattern dynamics and bifurcation in delayed SIR network with diffusion network.
- Author
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Yang, Wenjie, Zheng, Qianqian, and Shen, Jianwei
- Subjects
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HOPF bifurcations , *COMMUNICABLE diseases , *INFECTIOUS disease transmission , *EPIDEMICS , *COMPUTER simulation - Abstract
The spread of infectious diseases often presents the emergent properties, which leads to more difficulties in prevention and treatment. In this paper, the SIR model with both delay and network is investigated to show the emergent properties of the infectious diseases' spread. The stability of the SIR model with a delay and two delay is analyzed to illustrate the effect of delay on the periodic outbreak of the epidemic. Then the stability conditions of Hopf bifurcation are derived by using central manifold to obtain the direction of bifurcation, which is vital for the generation of emergent behavior. Also, numerical simulation shows that the connection probability can affect the types of the spatio-temporal patterns, further induces the emergent properties. Finally, the emergent properties of COVID-19 are explained by the above results. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
6. The global stability and optimal control of the COVID-19 epidemic model.
- Author
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Chien, Fengsheng, Nik, Hassan Saberi, Shirazian, Mohammad, and Gómez-Aguilar, J. F.
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COVID-19 pandemic , *LYAPUNOV functions , *EPIDEMICS , *INFECTIOUS disease transmission , *DYNAMICAL systems , *PREVENTIVE medicine , *EQUILIBRIUM - Abstract
This paper considers stability analysis of a Susceptible-Exposed-Infected-Recovered-Virus (SEIRV) model with nonlinear incidence rates and indicates the severity and weakness of control factors for disease transmission. The Lyapunov function using Volterra–Lyapunov matrices makes it possible to study the global stability of the endemic equilibrium point. An optimal control strategy is proposed to prevent the spread of coronavirus, in addition to governmental intervention. The objective is to minimize together with the quantity of infected and exposed individuals while minimizing the total costs of treatment. A numerical study of the model is also carried out to investigate the analytical results. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
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