Modeling antibiotic resistance in hospitals: The impact of minimizing treatment duration

Erika M.C. D'Agata, Pierre Magal, Damien Olivier, Shigui Ruan, Glenn F. Webb

Research output: Contribution to journalArticlepeer-review

98 Scopus citations

Abstract

Infections caused by antibiotic-resistant pathogens are a global public health problem. Numerous individual- and population-level factors contribute to the emergence and spread of these pathogens. An individual-based model (IBM), formulated as a system of stochastically determined events, was developed to describe the complexities of the transmission dynamics of antibiotic-resistant bacteria. To simplify the interpretation and application of the model's conclusions, a corresponding deterministic model was created, which describes the average behavior of the IBM over a large number of simulations. The integration of these two model systems provides a quantitative analysis of the emergence and spread of antibiotic-resistant bacteria, and demonstrates that early initiation of treatment and minimization of its duration mitigates antibiotic resistance epidemics in hospitals.

Original languageEnglish (US)
Pages (from-to)487-499
Number of pages13
JournalJournal of theoretical biology
Volume249
Issue number3
DOIs
StatePublished - Dec 7 2007

Keywords

  • Antibiotic-resistant bacteria
  • Basic reproduction number
  • Differential equation model
  • Individual-based model

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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