IDEAS home Printed from https://ideas.repec.org/a/taf/gcmbxx/v26y2023i9p1086-1099.html
   My bibliography  Save this article

Impact of Levy noise on a stochastic Norovirus epidemic model with information intervention

Author

Listed:
  • Ting Cui
  • Anwarud Din
  • Peijiang Liu
  • Amir Khan

Abstract

In this article, we study the dynamics of Norovirus infection by developing a stochastic epidemic model having Levy noise. The study shows that Levy noise and informative interventions have more influence on the said dynamics. Firstly, we show that the model has a unique global positive solution. After this, we formulated a stochastic threshold value as a necessary condition for the extinction and persistence in the mean of the proposed epidemic model. Finally, numerical simulation are drawn to verify our obtained results of the dynamics. The perturbed stochastic approach may affect the dynamical properties of the model and large noises will be greatly significant to minimize its transmission.

Suggested Citation

  • Ting Cui & Anwarud Din & Peijiang Liu & Amir Khan, 2023. "Impact of Levy noise on a stochastic Norovirus epidemic model with information intervention," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 26(9), pages 1086-1099, July.
    • Handle: RePEc:taf:gcmbxx:v:26:y:2023:i:9:p:1086-1099
    DOI: 10.1080/10255842.2022.2106784
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10255842.2022.2106784
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/10255842.2022.2106784?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:gcmbxx:v:26:y:2023:i:9:p:1086-1099. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/gcmb .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.