Global Analysis of a Novel Nonlinear Stochastic SIVS Epidemic System with Vaccination Control
Joint Authors
Leng, Xiaona
Feng, Tao
Meng, Xinzhu
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-28
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
This paper proposes a stochastic SIVS epidemic system with nonlinear saturated infection rate under vaccination and investigates the dynamics predicted by the model.
By using Itô’s formula and Lyapunov methods, we first study the existence and uniqueness of global positive solution.
Then we investigate the stochastic dynamics of the system and obtain the thresholds which govern the extinction and the spread of the epidemic disease.
Results show that large stochastic noises can lead to the extinction of epidemic diseases; that is, stochastic disturbances can suppress the outbreak of epidemic diseases.
Finally, we carry out a series of numerical simulations to demonstrate the performance of our theoretical findings.
American Psychological Association (APA)
Leng, Xiaona& Feng, Tao& Meng, Xinzhu. 2017. Global Analysis of a Novel Nonlinear Stochastic SIVS Epidemic System with Vaccination Control. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1192178
Modern Language Association (MLA)
Leng, Xiaona…[et al.]. Global Analysis of a Novel Nonlinear Stochastic SIVS Epidemic System with Vaccination Control. Mathematical Problems in Engineering No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1192178
American Medical Association (AMA)
Leng, Xiaona& Feng, Tao& Meng, Xinzhu. Global Analysis of a Novel Nonlinear Stochastic SIVS Epidemic System with Vaccination Control. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1192178
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1192178