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Cited by 167

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

A model of antibiotic-resistant bacterial epidemics in hospitals

Open access
Webb, Glenn F., D'Agata, Erika M. C., Magal, Pierre, Ruan, Shigui·2005·Proceedings of the National Academy of Sciences

Abstract

The emergence of drug-resistant strains of bacteria is an increasing threat to society, especially in hospital settings. Many antibiotics that were formerly effective in combating bacterial infections in hospital patients are no longer effective because of the evolution of resistant strains, which compromises medical care worldwide. In this article, we formulate a two-level population model to quantify key elements in nosocomial (hospital-acquired) infections. At the bacteria level, patients infected with these strains generate both nonresistant and resistant bacteria. At the patient level, susceptible patients are infected by infected patients at rates proportional to the total bacteria load of each strain present in the hospital. The objectives of this paper are to analyze the dynamic elements of nonresistant and resistant bacteria strains in epidemic populations in hospital environments and to provide understanding of measures to avoid the endemicity of resistant antibiotic strains.

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Metadata

Authors
Webb, G. F., D'Agata, E. M. C., Magal, P., & Ruan, S.
Venue
Proceedings of the National Academy of Sciences
Published
2005-09-02
Volume
102
Issue
37
Pages
13343-13348
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2097764864
Cited by
167
References
2
FWCI
2.26
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: A model of antibiotic-resistant bacterial epidemics in hospitals. https://app.cochat.ai/papers/10.1073/pnas.0504053102
The paper
Webb, G. F., D'Agata, E. M. C., Magal, P., & Ruan, S. (2005). A model of antibiotic-resistant bacterial epidemics in hospitals. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0504053102

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.