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

ABSTRACT: 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.

SUBMITTER: Spicknall IH

PROVIDER: S-EPMC3736756 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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

Spicknall Ian H IH Foxman Betsy B Marrs Carl F CF Eisenberg Joseph N S JN

American journal of epidemiology 20130509 4

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 mor ...[more]

PMID: 23660797

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Project description:BackgroundAntibiotic resistance is an increasing challenge for health care services worldwide. While up to 90% of antibiotics are being prescribed in the outpatient sector recommendations for the treatment of community-acquired infections are usually based on resistance findings from hospitalized patients. In context of the EU-project called "APRES - the appropriateness of prescribing antibiotic in primary health care in Europe with respect to antibiotic resistance" it was our aim to gain detailed information about the resistance data from Austria in both the scientific and the grey literature.MethodsA systematic review was performed including scientific and grey literature published between 2000 and 2010. Inclusion and exclusion criteria were defined and the review process followed published recommendations.ResultsSeventeen scientific articles and 23 grey literature documents could be found. In contrast to the grey literature, the scientific publications describe only a small part of the resistance situation in the primary health care sector in Austria. Merely half of these publications contain data from the ambulatory sector exclusively but these data are older than ten years, are very heterogeneous concerning the observed time period, the number and origin of the isolates and the kind of bacteria analysed. The grey literature yields more comprehensive and up-to-date information of the content of interest. These sources are available in German only and are not easily accessible. The resistance situation described in the grey literature can be summarized as rather stable over the last two years. For Escherichia coli e.g. the highest antibiotic resistance rates can be seen with fluorochiniolones (19%) and trimethoprim/sulfamethoxazole (27%).ConclusionComprehensive and up-to-date antibiotic resistance data of different pathogens isolated from the community level in Austria are presented. They could be found mainly in the grey literature, only few are published in peer-reviewed journals. The grey literature, therefore, is a very valuable source of relevant information. It could be speculated that the situation of published literature is similar in other countries as well.

Dataset Information

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

Publications

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

Similar Datasets

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