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  Modeling antimicrobial cycling and mixing: Differences arising from an individual-based versus a population-based perspective

Uecker, H., & Bonhoeffer, S. (2017). Modeling antimicrobial cycling and mixing: Differences arising from an individual-based versus a population-based perspective. Mathematical Biosciences, 294, 85-91. doi:10.1016/j.mbs.2017.09.002.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-39B5-4 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-42AB-1
Genre: Journal Article

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 Creators:
Uecker, Hildegard1, Author              
Bonhoeffer, Sebastian, Author
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1External Organizations, ou_persistent22              

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Free keywords: Antibiotic resistance; Hospital-acquired infections; Antimicrobial stewardship; Epidemic model
 Abstract: In order to manage bacterial infections in hospitals in the face of antibiotic resistance, the two treatment protocols “mixing” and “cycling” have received considerable attention both from modelers and clinicians. However, the terms are not used in exactly the same way by both groups. This comes because the standard modeling approach disregards the perspective of individual patients. In this article, we investigate a model that comes closer to clinical practice and compare the predictions to the standard model. We set up two deterministic models, implemented as a set of differential equations, for the spread of bacterial infections in a hospital. Following the traditional approach, the first model takes a population-based perspective. The second model, in contrast, takes the drug use of individual patients into account. The alternative model can indeed lead to different predictions than the standard model. We provide examples for which in the new model, the opposite strategy maximizes the number of uninfected patients or minimizes the rate of spread of double resistance. While the traditional models provide valuable insight, care is hence needed in the interpretation of results.

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Language(s): eng - English
 Dates: 2017-06-302016-11-142017-09-112017-09-282017
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
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Title: Mathematical Biosciences
Source Genre: Journal
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Publ. Info: New York : Elsevier
Pages: - Volume / Issue: 294 Sequence Number: - Start / End Page: 85 - 91 Identifier: ISSN: 0025-5564
CoNE: /journals/resource/991042744490246