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dc.contributor.authorPeña-Miller, R
dc.contributor.authorBeardmore, Robert
dc.date.accessioned2013-04-30T13:33:15Z
dc.date.issued2010-07
dc.description.abstractThe purpose of this paper is to use mathematical models to investigate the claim made in the medical literature over a decade ago that the routine rotation of antibiotics in an intensive care unit (ICU) will select against the evolution and spread of antibiotic-resistant pathogens. In contrast, previous theoretical studies addressing this question have demonstrated that routinely changing the drug of choice for a given pathogenic infection may in fact lead to a greater incidence of drug resistance in comparison to the random deployment of different drugs. Using mathematical models that do not explicitly incorporate the spatial dynamics of pathogen transmission within the ICU or hospital and assuming the antibiotics are from distinct functional groups, we use a control theoretic-approach to prove that one can relax the medical notion of what constitutes an antibiotic rotation and so obtain protocols that are arbitrarily close to the optimum. Finally, we show that theoretical feedback control measures that rotate between different antibiotics motivated directly by the outcome of clinical studies can be deployed to good effect to reduce the prevalence of antibiotic resistance below what can be achieved with random antibiotic use.en_GB
dc.identifier.citationVol. 7, Issue 3, pp. 527 - 552en_GB
dc.identifier.doi10.3934/mbe.2010.7.527
dc.identifier.urihttp://hdl.handle.net/10871/8701
dc.publisherAmerican Institute of Mathematical Sciencesen_GB
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pubmed/20578784en_GB
dc.subjectAnimalsen_GB
dc.subjectAnti-Bacterial Agentsen_GB
dc.subjectBacteriaen_GB
dc.subjectBacterial Infectionsen_GB
dc.subjectDrug Administration Scheduleen_GB
dc.subjectDrug Resistance, Bacterialen_GB
dc.subjectIntensive Care Unitsen_GB
dc.subjectModels, Biologicalen_GB
dc.titleRotating antibiotics selects optimally against antibiotic resistance, in theory.en_GB
dc.typeArticleen_GB
dc.date.available2013-04-30T13:33:15Z
dc.identifier.issn1547-1063
exeter.place-of-publicationUnited States
dc.descriptionFinal published version deposited in accordance with SHERPA RoMEO guidelines.en_GB
dc.identifier.journalMathematical Biosciences & Engineeringen_GB


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