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Stochastic permanence of an SIQS epidemic model with saturated incidence and independent random perturbations

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  • Wei, Fengying
  • Chen, Fangxiang

Abstract

This article discusses a stochastic SIQS epidemic model with saturated incidence. We assume that random perturbations always fluctuate at the endemic equilibrium. The existence of a global positive solution is obtained by constructing a suitable Lyapunov function. Under some suitable conditions, we derive the stochastic boundedness and stochastic permanence of the solutions of a stochastic SIQS model. Some numerical simulations are carried out to check our results.

Suggested Citation

  • Wei, Fengying & Chen, Fangxiang, 2016. "Stochastic permanence of an SIQS epidemic model with saturated incidence and independent random perturbations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 99-107.
    • Handle: RePEc:eee:phsmap:v:453:y:2016:i:c:p:99-107
    DOI: 10.1016/j.physa.2016.01.059
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    References listed on IDEAS

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    1. Witbooi, Peter J., 2013. "Stability of an SEIR epidemic model with independent stochastic perturbations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 4928-4936.
    2. Lahrouz, Aadil & Omari, Lahcen, 2013. "Extinction and stationary distribution of a stochastic SIRS epidemic model with non-linear incidence," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 960-968.
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    Cited by:

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    2. Zhang, Yue & Li, Yang & Zhang, Qingling & Li, Aihua, 2018. "Behavior of a stochastic SIR epidemic model with saturated incidence and vaccination rules," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 178-187.
    3. Hussain, Ghulam & Khan, Amir & Zahri, Mostafa & Zaman, Gul, 2022. "Ergodic stationary distribution of stochastic epidemic model for HBV with double saturated incidence rates and vaccination," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    4. Raul Nistal & Manuel De la Sen & Santiago Alonso-Quesada & Asier Ibeas, 2018. "On a New Discrete SEIADR Model with Mixed Controls: Study of Its Properties," Mathematics, MDPI, vol. 7(1), pages 1-19, December.
    5. Li, Yan & Zhang, Qimin, 2020. "The balanced implicit method of preserving positivity for the stochastic SIQS epidemic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    6. Wei, Fengying & Liu, Jiamin, 2017. "Long-time behavior of a stochastic epidemic model with varying population size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 146-153.
    7. Zhang, Xiao-Bing & Huo, Hai-Feng & Xiang, Hong & Shi, Qihong & Li, Dungang, 2017. "The threshold of a stochastic SIQS epidemic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 362-374.
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    9. Caraballo, T. & Settati, A. & Lahrouz, A. & Boutouil, S. & Harchaoui, B., 2024. "On the stochastic threshold of the COVID-19 epidemic model incorporating jump perturbations," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    10. Liu, Jiamin & Wei, Fengying, 2016. "Dynamics of stochastic SEIS epidemic model with varying population size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 241-250.
    11. Qi, Haokun & Zhang, Shengqiang & Meng, Xinzhu & Dong, Huanhe, 2018. "Periodic solution and ergodic stationary distribution of two stochastic SIQS epidemic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 223-241.
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    14. Zhiming Li & Zhidong Teng, 2019. "Analysis of uncertain SIS epidemic model with nonlinear incidence and demography," Fuzzy Optimization and Decision Making, Springer, vol. 18(4), pages 475-491, December.

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