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A Modeling Framework for the Evolution and Spread of Antibiotic Resistance: Literature Review and Model Categorization
Antibiotic-resistant infections complicate treatment and increase morbidity and mortality. Mathematical modeling has played an integral role in improving our understanding of antibiotic resistance. In these models, parameter sensitivity is often assessed, while model structure sensitivity is not. To...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3736756/ https://www.ncbi.nlm.nih.gov/pubmed/23660797 http://dx.doi.org/10.1093/aje/kwt017 |
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author | Spicknall, Ian H. Foxman, Betsy Marrs, Carl F. Eisenberg, Joseph N. S. |
author_facet | Spicknall, Ian H. Foxman, Betsy Marrs, Carl F. Eisenberg, Joseph N. S. |
author_sort | Spicknall, Ian H. |
collection | PubMed |
description | Antibiotic-resistant infections complicate treatment and increase morbidity and mortality. Mathematical modeling has played an integral role in improving our understanding of antibiotic resistance. In these models, parameter sensitivity is often assessed, while model structure sensitivity is not. To examine the implications of this, we first reviewed the literature on antibiotic-resistance modeling published between 1993 and 2011. We then classified each article's model structure into one or more of 6 categories based on the assumptions made in those articles regarding within-host and population-level competition between antibiotic-sensitive and antibiotic-resistant strains. Each model category has different dynamic implications with respect to how antibiotic use affects resistance prevalence, and therefore each may produce different conclusions about optimal treatment protocols that minimize resistance. Thus, even if all parameter values are correctly estimated, inferences may be incorrect because of the incorrect selection of model structure. Our framework provides insight into model selection. |
format | Online Article Text |
id | pubmed-3736756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-37367562013-08-08 A Modeling Framework for the Evolution and Spread of Antibiotic Resistance: Literature Review and Model Categorization Spicknall, Ian H. Foxman, Betsy Marrs, Carl F. Eisenberg, Joseph N. S. Am J Epidemiol Special Article Antibiotic-resistant infections complicate treatment and increase morbidity and mortality. Mathematical modeling has played an integral role in improving our understanding of antibiotic resistance. In these models, parameter sensitivity is often assessed, while model structure sensitivity is not. To examine the implications of this, we first reviewed the literature on antibiotic-resistance modeling published between 1993 and 2011. We then classified each article's model structure into one or more of 6 categories based on the assumptions made in those articles regarding within-host and population-level competition between antibiotic-sensitive and antibiotic-resistant strains. Each model category has different dynamic implications with respect to how antibiotic use affects resistance prevalence, and therefore each may produce different conclusions about optimal treatment protocols that minimize resistance. Thus, even if all parameter values are correctly estimated, inferences may be incorrect because of the incorrect selection of model structure. Our framework provides insight into model selection. Oxford University Press 2013-08-15 2013-05-09 /pmc/articles/PMC3736756/ /pubmed/23660797 http://dx.doi.org/10.1093/aje/kwt017 Text en © The Author 2013. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Special Article Spicknall, Ian H. Foxman, Betsy Marrs, Carl F. Eisenberg, Joseph N. S. A Modeling Framework for the Evolution and Spread of Antibiotic Resistance: Literature Review and Model Categorization |
title | A Modeling Framework for the Evolution and Spread of Antibiotic Resistance: Literature Review and Model Categorization |
title_full | A Modeling Framework for the Evolution and Spread of Antibiotic Resistance: Literature Review and Model Categorization |
title_fullStr | A Modeling Framework for the Evolution and Spread of Antibiotic Resistance: Literature Review and Model Categorization |
title_full_unstemmed | A Modeling Framework for the Evolution and Spread of Antibiotic Resistance: Literature Review and Model Categorization |
title_short | A Modeling Framework for the Evolution and Spread of Antibiotic Resistance: Literature Review and Model Categorization |
title_sort | modeling framework for the evolution and spread of antibiotic resistance: literature review and model categorization |
topic | Special Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3736756/ https://www.ncbi.nlm.nih.gov/pubmed/23660797 http://dx.doi.org/10.1093/aje/kwt017 |
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