IDEAS home Printed from https://ideas.repec.org/a/taf/mpopst/v12y2005i1p1-16.html
   My bibliography  Save this article

Deterministic and Stochastic Modeling of Pneumococcal Resistance to Penicillin

Author

Listed:
  • Laura Temime
  • Pierre-Yves Boëlle
  • Guy Thomas

Abstract

A stochastic compartmental model of the progression of pneumococcal resistance to penicillin G in a human community is built, through intra-individual selection and inter-individual transmission. It is structured by the resistance level of colonizing bacteria and driven by jump intensity functions. The Markov process associated with the model tends to the solution of a deterministic system when the size of the population tends to infinity. The behavior of the stochastic mean sample path is simulated for small population sizes and compared to the solution of the limit deterministic system. For populations over 5,000 individuals, the deterministic solution is a good approximation of the mean stochastic sample path. Both stochastic and deterministic predictions have proved useful to understand resistance selection mechanisms and to evaluate strategies for resistance prevention, such as a reduction in antibiotic consumption or vaccination.

Suggested Citation

  • Laura Temime & Pierre-Yves Boëlle & Guy Thomas, 2005. "Deterministic and Stochastic Modeling of Pneumococcal Resistance to Penicillin," Mathematical Population Studies, Taylor & Francis Journals, vol. 12(1), pages 1-16.
  • Handle: RePEc:taf:mpopst:v:12:y:2005:i:1:p:1-16
    DOI: 10.1080/08898480590902154
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/08898480590902154
    Download Restriction: Access to full text is restricted to subscribers.

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

    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:mpopst:v:12:y:2005:i:1:p:1-16. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/GMPS20 .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.