IDEAS home Printed from https://ideas.repec.org/a/taf/nmcmxx/v29y2023i1p236-264.html
   My bibliography  Save this article

A stochastic model of antibiotic misuse, economy, and drug resistance: relating mutant extinction probability to socioeconomic and epidemiological factors

Author

Listed:
  • Bhawna Malik
  • Samit Bhattacharyya

Abstract

Controlling antibiotic drug resistance requires understanding extinction and emergence mechanisms of emerging bacteria. Selective pressure from prolonged antibiotic misuse may cause high-level antimicrobial resistance. Self-medication and other socioeconomic factors reduce antibiotic use, accelerating the emergence and extinction of resistant pathogens through stochastic fluctuation. This continuous antibiotic self-medication exposes individuals and communities to antibiotic resistance, especially in low- and lower-middle-income countries, according to current literature. We developed a stochastic drug-resistance model that integrates socio-economic growth and antibiotic use to study extinction and strain establishment in this paper. We analytically derived the extinction threshold using the multi-type branching process and obtained pathogen extinction conditions that match numerical experiments. The model's sensitivity analysis identifies extinction dynamics' key parameters. Our results show that higher income, awareness, and lower antibiotic use may increase the chance of extinction by reducing antibiotic misuse, along with strain transmission potential. These analyses may help public health policymakers combat drug resistance.

Suggested Citation

  • Bhawna Malik & Samit Bhattacharyya, 2023. "A stochastic model of antibiotic misuse, economy, and drug resistance: relating mutant extinction probability to socioeconomic and epidemiological factors," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 29(1), pages 236-264, December.
  • Handle: RePEc:taf:nmcmxx:v:29:y:2023:i:1:p:236-264
    DOI: 10.1080/13873954.2023.2244175
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13873954.2023.2244175
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/13873954.2023.2244175?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:nmcmxx:v:29:y:2023:i:1:p:236-264. 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/NMCM20 .

    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.