Literature DB >> 15778333

Simple models of antibiotic cycling.

Timothy C Reluga1.   

Abstract

The use of environmental heterogeneity is an old but potentially powerful method for managing biological systems. Determining the optimal form of environmental heterogeneity is a difficult problem. One family of heterogeneous management strategies that has received attention in the medical community is the periodic cycling of antibiotic usage to control antibiotic resistance. This paper presents a theory for the optimization of antibiotic cycling based on a density-independent model of transmission and immigration of evolutionarily static strains. In the case of two pathogen strains, I show that the population's asymptotic growth rate is a monotonically increasing function of the oscillation period under certain common assumptions. Monte Carlo simulations show that this result fails in more general settings, but suggest that antibiotic cycling seldom provides a significant improvement over alternative mixing practices. The results support the findings of other researchers that antibiotic cycling does not offer significant advantages over idealized conventional practice. However, cycling strategies may be preferable in some special cases.

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Year:  2005        PMID: 15778333     DOI: 10.1093/imammb/dqi002

Source DB:  PubMed          Journal:  Math Med Biol        ISSN: 1477-8599            Impact factor:   1.854


  16 in total

Review 1.  The population genetics of antibiotic resistance: integrating molecular mechanisms and treatment contexts.

Authors:  R Craig MacLean; Alex R Hall; Gabriel G Perron; Angus Buckling
Journal:  Nat Rev Genet       Date:  2010-06       Impact factor: 53.242

Review 2.  The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study.

Authors:  L Temime; G Hejblum; M Setbon; A J Valleron
Journal:  Epidemiol Infect       Date:  2007-09-04       Impact factor: 2.451

3.  Qualitative analysis of models with different treatment protocols to prevent antibiotic resistance.

Authors:  Hong-Rui Sun; Xinxin Lu; Shigui Ruan
Journal:  Math Biosci       Date:  2010-06-25       Impact factor: 2.144

4.  Reduction in rates of methicillin-resistant Staphylococcus aureus infection after introduction of quarterly linezolid-vancomycin cycling in a surgical intensive care unit.

Authors:  Robert L Smith; Heather L Evans; Tae W Chong; Shannon T McElearney; Traci L Hedrick; Brian R Swenson; W Michael Scheld; Timothy L Pruett; Robert G Sawyer
Journal:  Surg Infect (Larchmt)       Date:  2008-08       Impact factor: 2.150

5.  Informed switching strongly decreases the prevalence of antibiotic resistance in hospital wards.

Authors:  Roger D Kouyos; Pia Abel Zur Wiesch; Sebastian Bonhoeffer
Journal:  PLoS Comput Biol       Date:  2011-03-03       Impact factor: 4.475

6.  Application of dynamic modelling techniques to the problem of antibacterial use and resistance: a scoping review.

Authors:  D E Ramsay; J Invik; S L Checkley; S P Gow; N D Osgood; C L Waldner
Journal:  Epidemiol Infect       Date:  2018-07-31       Impact factor: 4.434

7.  The effects of antibiotic cycling and mixing on acquisition of antibiotic resistant bacteria in the ICU: A post-hoc individual patient analysis of a prospective cluster-randomized crossover study.

Authors:  Pleun J van Duijn; Walter Verbrugghe; Philippe G Jorens; Fabian Spöhr; Dirk Schedler; Maria Deja; Andreas Rothbart; Djillali Annane; Christine Lawrence; Matjaz Jereb; Katja Seme; Franc Šifrer; Viktorija Tomič; Francisco Estevez; Jandira Carneiro; Stephan Harbarth; Marc J M Bonten
Journal:  PLoS One       Date:  2022-05-03       Impact factor: 3.752

Review 8.  What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature.

Authors:  Maria Arepeva; Alexey Kolbin; Alexey Kurylev; Julia Balykina; Sergey Sidorenko
Journal:  Front Microbiol       Date:  2015-04-29       Impact factor: 5.640

9.  The impact of different antibiotic regimens on the emergence of antimicrobial-resistant bacteria.

Authors:  Erika M C D'Agata; Myrielle Dupont-Rouzeyrol; Pierre Magal; Damien Olivier; Shigui Ruan
Journal:  PLoS One       Date:  2008-12-29       Impact factor: 3.240

Review 10.  A modeling framework for the evolution and spread of antibiotic resistance: literature review and model categorization.

Authors:  Ian H Spicknall; Betsy Foxman; Carl F Marrs; Joseph N S Eisenberg
Journal:  Am J Epidemiol       Date:  2013-05-09       Impact factor: 4.897

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