%0 Journal Article %1 Chowa201127 %A Chowa, K. %A Wanga, X. %A Curtiss, R. %A Castillo-Chavez, C. %D 2011 %J Journal of Biological Dynamics %K (microorganisms) Adherence; Agents; Anti-Bacterial Bacteria Bacteria; Bacterial; Biological; Colony Computer Count, Drug Guideline Hospitals; Humans; Isolation; Microbial; Models, Multiple, Patient Physicians, Resistance, Simulation; agent, aging; and antiinfective article; bacterial bacterium; biological care; computer count; development drug effect; growth, guideline, hospital; human; model; multidrug patient physician; practice resistance; simulation; %N 1 %P 27-43 %R http://dx.doi.org/10.1080/17513758.2010.488300 %T Evaluating the efficacy of antimicrobial cycling programmes and patient isolation on dual resistance in hospitals %U http://dx.doi.org/10.1080/17513758.2010.488300 %V 5 %X Antibiotic-resistant bacteria cause a number of infections in hospitals and are considered a threat to public health. A strategy suggested to curb the development of resistant hospital-acquired infections is antimicrobial cycling, in which antibiotic classes are alternated over time. This can be compared with a mixing programme in which, when given two drugs, half of the physicians prescribe one drug over the other. A mathematical model of antimicrobial cycling in a hospital population setting is developed to evaluate the efficacy of a cycling programme with an emphasis on reducing the emergence and significance of dual resistance. The model also considers the effects of physician compliance and isolating patients harbouring dual-resistant bacteria. Simulation results show that the optimal antimicrobial drug usage programme in hospital populations depends upon the type of resistance being targeted for treatment; a cycling programme is more effective against dual resistance compared with mixing. Patient isolation and high compliance to a cycling programme is also shown to dramatically decrease dual resistance in hospitalized populations. Ultimately, the exclusive use of antimicrobials in fighting nosocomial infection does not solve the problem but just slows down what appears to be a losing battle against drug resistance.We hope that this paper serves to instigate discussion on the many dimensions of the complex problem of drug resistance in hospital settings. Â\copyright 2011 Taylor & Francis.

@article{Chowa201127, abstract = {Antibiotic-resistant bacteria cause a number of infections in hospitals and are considered a threat to public health. A strategy suggested to curb the development of resistant hospital-acquired infections is antimicrobial cycling, in which antibiotic classes are alternated over time. This can be compared with a mixing programme in which, when given two drugs, half of the physicians prescribe one drug over the other. A mathematical model of antimicrobial cycling in a hospital population setting is developed to evaluate the efficacy of a cycling programme with an emphasis on reducing the emergence and significance of dual resistance. The model also considers the effects of physician compliance and isolating patients harbouring dual-resistant bacteria. Simulation results show that the optimal antimicrobial drug usage programme in hospital populations depends upon the type of resistance being targeted for treatment; a cycling programme is more effective against dual resistance compared with mixing. Patient isolation and high compliance to a cycling programme is also shown to dramatically decrease dual resistance in hospitalized populations. Ultimately, the exclusive use of antimicrobials in fighting nosocomial infection does not solve the problem but just slows down what appears to be a losing battle against drug resistance.We hope that this paper serves to instigate discussion on the many dimensions of the complex problem of drug resistance in hospital settings. {\^A}{\copyright} 2011 Taylor & Francis.}, added-at = {2017-11-10T22:48:29.000+0100}, affiliation = {Mathematical, Computational Modeling Sciences Center, Arizona State University, PO Box 871904, Tempe, AZ 85287, United States; The Biodesign Institute, Arizona State University, Tempe, AZ 85287, United States; School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287, United States; School of Mathematics and Statistics, Arizona State University, Tempe, AZ 85287, United States; Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, United States}, author = {Chowa, K. and Wanga, X. and Curtiss, R. and Castillo-Chavez, C.}, author_keywords = {Antimicrobial; Cycling; Isolation; Model; Nosocomial; Resistance}, biburl = {https://www.bibsonomy.org/bibtex/2ec0fe83b2498efd0bf44ec7520be7324/ccchavez}, correspondence_address1 = {Chowa, K.; Mathematical, Computational Modeling Sciences Center, PO Box 871904, Arizona State University, Tempe, AZ 85287, United States; email: kchow@asu.edu}, date-added = {2017-11-10 21:45:26 +0000}, date-modified = {2017-11-10 21:45:26 +0000}, document_type = {Article}, doi = {http://dx.doi.org/10.1080/17513758.2010.488300}, interhash = {2cb2b3eacc763319fd27dc2bd6dffb78}, intrahash = {ec0fe83b2498efd0bf44ec7520be7324}, issn = {17513758}, journal = {Journal of Biological Dynamics}, keywords = {(microorganisms) Adherence; Agents; Anti-Bacterial Bacteria Bacteria; Bacterial; Biological; Colony Computer Count, Drug Guideline Hospitals; Humans; Isolation; Microbial; Models, Multiple, Patient Physicians, Resistance, Simulation; agent, aging; and antiinfective article; bacterial bacterium; biological care; computer count; development drug effect; growth, guideline, hospital; human; model; multidrug patient physician; practice resistance; simulation;}, language = {English}, number = 1, pages = {27-43}, pubmed_id = {22877228}, timestamp = {2017-11-10T22:48:29.000+0100}, title = {Evaluating the efficacy of antimicrobial cycling programmes and patient isolation on dual resistance in hospitals}, url = {http://dx.doi.org/10.1080/17513758.2010.488300}, volume = 5, year = 2011 }