Literature DB >> 30062979

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

D E Ramsay1, J Invik2, S L Checkley2, S P Gow3, N D Osgood4, C L Waldner5.   

Abstract

Selective pressure exerted by the widespread use of antibacterial drugs is accelerating the development of resistant bacterial populations. The purpose of this scoping review was to summarise the range of studies that use dynamic models to analyse the problem of bacterial resistance in relation to antibacterial use in human and animal populations. A comprehensive search of the peer-reviewed literature was performed and non-duplicate articles (n = 1486) were screened in several stages. Charting questions were used to extract information from the articles included in the final subset (n = 81). Most studies (86%) represent the system of interest with an aggregate model; individual-based models are constructed in only seven articles. There are few examples of inter-host models outside of human healthcare (41%) and community settings (38%). Resistance is modelled for a non-specific bacterial organism and/or antibiotic in 40% and 74% of the included articles, respectively. Interventions with implications for antibacterial use were investigated in 67 articles and included changes to total antibiotic consumption, strategies for drug management and shifts in category/class use. The quality of documentation related to model assumptions and uncertainty varies considerably across this subset of articles. There is substantial room to improve the transparency of reporting in the antibacterial resistance modelling literature as is recommended by best practice guidelines.

Entities:  

Keywords:  Antibiotic resistance; modelling; transmission

Mesh:

Substances:

Year:  2018        PMID: 30062979      PMCID: PMC6453001          DOI: 10.1017/S0950268818002091

Source DB:  PubMed          Journal:  Epidemiol Infect        ISSN: 0950-2688            Impact factor:   4.434


  109 in total

1.  A model of drug resistance with infection by health care workers.

Authors:  Avner Friedman; Najat Ziyadi; Khalid Boushaba
Journal:  Math Biosci Eng       Date:  2010-10       Impact factor: 2.080

2.  Model parameter estimation and uncertainty: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--6.

Authors:  Andrew H Briggs; Milton C Weinstein; Elisabeth A L Fenwick; Jonathan Karnon; Mark J Sculpher; A David Paltiel
Journal:  Value Health       Date:  2012 Sep-Oct       Impact factor: 5.725

3.  Preventing the transmission of multidrug-resistant organisms: modeling the relative importance of hand hygiene and environmental cleaning interventions.

Authors:  Sean L Barnes; Daniel J Morgan; Anthony D Harris; Phillip C Carling; Kerri A Thom
Journal:  Infect Control Hosp Epidemiol       Date:  2014-07-25       Impact factor: 3.254

4.  Studies of antibiotic resistance within the patient, hospitals and the community using simple mathematical models.

Authors:  D J Austin; R M Anderson
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  1999-04-29       Impact factor: 6.237

5.  The relationship between antimicrobial resistance and patient outcomes: mortality, length of hospital stay, and health care costs.

Authors:  Sara E Cosgrove
Journal:  Clin Infect Dis       Date:  2006-01-15       Impact factor: 9.079

6.  Cost-effectiveness evaluation of ertapenem versus piperacillin/tazobactam in the treatment of complicated intraabdominal infections accounting for antibiotic resistance.

Authors:  Jeroen P Jansen; Ritesh Kumar; Yehuda Carmeli
Journal:  Value Health       Date:  2009 Mar-Apr       Impact factor: 5.725

7.  Accounting for the development of antibacterial resistance in the cost effectiveness of ertapenem versus piperacillin/tazobactam in the treatment of diabetic foot infections in the UK.

Authors:  Jeroen P Jansen; Ritesh Kumar; Yehuda Carmeli
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

8.  Antibiotic control of antibiotic resistance in hospitals: a simulation study.

Authors:  Michael Haber; Bruce R Levin; Piotr Kramarz
Journal:  BMC Infect Dis       Date:  2010-08-25       Impact factor: 3.090

9.  Bacterial resistance to penicillin G by decreased affinity of penicillin-binding proteins: a mathematical model.

Authors:  L Temime; P Y Boëlle; P Courvalin; D Guillemot
Journal:  Emerg Infect Dis       Date:  2003-04       Impact factor: 6.883

10.  When does overuse of antibiotics become a tragedy of the commons?

Authors:  Travis C Porco; Daozhou Gao; James C Scott; Eunha Shim; Wayne T Enanoria; Alison P Galvani; Thomas M Lietman
Journal:  PLoS One       Date:  2012-12-07       Impact factor: 3.240

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  2 in total

1.  Microbiome-pathogen interactions drive epidemiological dynamics of antibiotic resistance: A modeling study applied to nosocomial pathogen control.

Authors:  Laura Temime; Lulla Opatowski; David Rm Smith
Journal:  Elife       Date:  2021-09-14       Impact factor: 8.140

Review 2.  Feedlot Cattle Antimicrobial Use Surveillance Network: A Canadian Journey.

Authors:  Sherry J Hannon; Stephanie A Brault; Simon J G Otto; Paul S Morley; Tim A McAllister; Calvin W Booker; Sheryl P Gow
Journal:  Front Vet Sci       Date:  2020-11-20
  2 in total

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