A nonlinear time-series analysis approach to identify thresholds in associations between population antibiotic use and rates of resistance. View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04-08

AUTHORS

José-María López-Lozano, Timothy Lawes, César Nebot, Arielle Beyaert, Xavier Bertrand, Didier Hocquet, Mamoon Aldeyab, Michael Scott, Geraldine Conlon-Bingham, David Farren, Gábor Kardos, Adina Fésűs, Jesús Rodríguez-Baño, Pilar Retamar, Nieves Gonzalo-Jiménez, Ian M Gould

ABSTRACT

Balancing access to antibiotics with the control of antibiotic resistance is a global public health priority. At present, antibiotic stewardship is informed by a 'use it and lose it' principle, in which antibiotic use by the population is linearly related to resistance rates. However, theoretical and mathematical models suggest that use-resistance relationships are nonlinear. One explanation for this is that resistance genes are commonly associated with 'fitness costs' that impair the replication or transmissibility of the pathogen. Therefore, resistant genes and pathogens may only gain a survival advantage where antibiotic selection pressures exceed critical thresholds. These thresholds may provide quantitative targets for stewardship-optimizing the control of resistance while avoiding over-restriction of antibiotics. Here, we evaluated the generalizability of a nonlinear time-series analysis approach for identifying thresholds using historical prescribing and microbiological data from five populations in Europe. We identified minimum thresholds in temporal relationships between the use of selected antibiotics and incidence rates of carbapenem-resistant Acinetobacter baumannii (Hungary), extended-spectrum β-lactamase-producing Escherichia coli (Spain), cefepime-resistant E. coli (Spain), gentamicin-resistant Pseudomonas aeruginosa (France) and methicillin-resistant Staphylococcus aureus (Northern Ireland) in different epidemiological phases. Using routinely generated data, our approach can identify context-specific quantitative targets for rationalizing population antibiotic use and controlling resistance. Prospective intervention studies that restrict antibiotic consumption are needed to validate these thresholds. More... »

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41564-019-0410-0

DOI

http://dx.doi.org/10.1038/s41564-019-0410-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113300789

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30962570


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41564-019-0410-0'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41564-019-0410-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41564-019-0410-0'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41564-019-0410-0'


 

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