Stability analysis of SEIQR model in computer networks

Ge, Shao-Ting; Tang, Gong‐You; Yang, Xue; Xu, Qi; Yu, Haitao

doi:10.1109/ccdc.2013.6561309

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…If we neglect the lag and latency, we cannot control the transmission risk of EVD efficiently. 7 In order to solve this problem, we built a SEIQR model to study the optimal control method for the transmission risk of Ebola, and analyzed the stability of the free-Ebola-virus-disease equilibrium and Ebola-virus-disease equilibrium.…”

Section: Introductionmentioning

confidence: 99%

Study on modeling simulation and optimal control method for the transmission risk of the Ebola virus

Liu

2018

SIMULATION

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In order to prevent and control the transmission risk of the Ebola virus, an Ebola virus disease SEIQR model was built. The free-Ebola-virus-disease equilibrium state and the Ebola-virus-disease equilibrium state of the SEIQR model are asymptotically stable. On the basis of the SEIQR model, the numerical simulation was formulated. From the simulation curves, it is found that if the production speed of the medicine cannot keep pace with demand, the transmission risk of Ebola will become out of control. Assuming that the medicine demand point and the medicine supply point constitute a logistics system in a certain planar range, the center-of-gravity method was used to obtain the optimal location for medicine delivery. By using this discrete-time virus model's optimal control rate to control the serious transmission risk of Ebola virus in the crowd, the effective strategy for transmission was added to the model, and then the control sheet was obtained. From the simulation results on the basis of the SEIQR model, it is concluded that the theory of the optimal control rate has a negative effect on the transmission risk of Ebola.

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Section: Introductionmentioning

confidence: 99%

Study on modeling simulation and optimal control method for the transmission risk of the Ebola virus

Liu

2018

SIMULATION

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“…S. T. Ge et al presented the SEIQR epidemic model with the discrete time in computer networks. The stability of the proposed model was shown by Lyapunove method in [9]. M. Kummar and A. Kumar analyzes the SI j RS E-Epidemic model for various groups of infection in computer networking [10].…”

Section: Introductionmentioning

confidence: 99%

Global Stability of SEIQRS Computer Virus Propagation Model with Non-Linear Incidence Function

Badshah¹

2015

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In this paper, we present an SEIQRS epidemic model with non-linear incidence function. The proposed model exhibits two equilibrium points, the virus free equilibrium and viral equilibrium. The model stability is connected with the basic reproduction number R0. If R0 < 1 then the virus free equilibrium point is stable locally and globally. In the opposite case R0 > 1, then the model is locally and globally stable at viral equilibrium point. Numerical methods are used for supporting the analytical work.

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Stability analysis of SEIQR model in computer networks

Cited by 2 publications

References 14 publications

Study on modeling simulation and optimal control method for the transmission risk of the Ebola virus

Study on modeling simulation and optimal control method for the transmission risk of the Ebola virus

Global Stability of SEIQRS Computer Virus Propagation Model with Non-Linear Incidence Function

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