Literature DB >> 17767792

The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study.

L Temime1, G Hejblum, M Setbon, A J Valleron.   

Abstract

Mathematical modelling of infectious diseases has gradually become part of public health decision-making in recent years. However, the developing status of modelling in epidemiology and its relationship with other relevant scientific approaches have never been assessed quantitatively. Herein, using antibiotic resistance as a case study, 60 published models were analysed. Their interactions with other scientific fields are reported and their citation impact evaluated, as well as temporal trends. The yearly number of antibiotic resistance modelling publications increased significantly between 1990 and 2006. This rise cannot be explained by the surge of interest in resistance phenomena alone. Moreover, modelling articles are, on average, among the most frequently cited third of articles from the journal in which they were published. The results of this analysis, which might be applicable to other emerging public health problems, demonstrate the growing interest in mathematical modelling approaches to evaluate antibiotic resistance.

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Year:  2007        PMID: 17767792      PMCID: PMC2870826          DOI: 10.1017/S0950268807009442

Source DB:  PubMed          Journal:  Epidemiol Infect        ISSN: 0950-2688            Impact factor:   2.451


  66 in total

1.  Short- and long-term effects of pneumococcal conjugate vaccination of children on penicillin resistance.

Authors:  L Temime; D Guillemot; P Y Boëlle
Journal:  Antimicrob Agents Chemother       Date:  2004-06       Impact factor: 5.191

2.  Invasion of drug and pesticide resistance is determined by a trade-off between treatment efficacy and relative fitness.

Authors:  Richard J Hall; Simon Gubbins; Christopher A Gilligan
Journal:  Bull Math Biol       Date:  2004-07       Impact factor: 1.758

3.  Ecological theory suggests that antimicrobial cycling will not reduce antimicrobial resistance in hospitals.

Authors:  Carl T Bergstrom; Monique Lo; Marc Lipsitch
Journal:  Proc Natl Acad Sci U S A       Date:  2004-08-12       Impact factor: 11.205

4.  Modeling the emergence of the 'hot zones': tuberculosis and the amplification dynamics of drug resistance.

Authors:  Sally M Blower; Tom Chou
Journal:  Nat Med       Date:  2004-09-19       Impact factor: 53.440

5.  Projected benefits of active surveillance for vancomycin-resistant enterococci in intensive care units.

Authors:  Eli N Perencevich; David N Fisman; Marc Lipsitch; Anthony D Harris; J Glenn Morris; David L Smith
Journal:  Clin Infect Dis       Date:  2004-04-05       Impact factor: 9.079

Review 6.  Non-inherited antibiotic resistance.

Authors:  Bruce R Levin; Daniel E Rozen
Journal:  Nat Rev Microbiol       Date:  2006-07       Impact factor: 60.633

7.  Upgrading antibiotic use within a class: tradeoff between resistance and treatment success.

Authors:  Y Claire Wang; Marc Lipsitch
Journal:  Proc Natl Acad Sci U S A       Date:  2006-06-13       Impact factor: 11.205

8.  The analysis of hospital infection data using hidden Markov models.

Authors:  Ben Cooper; Marc Lipsitch
Journal:  Biostatistics       Date:  2004-04       Impact factor: 5.899

9.  Modeling epidemics of multidrug-resistant M. tuberculosis of heterogeneous fitness.

Authors:  Ted Cohen; Megan Murray
Journal:  Nat Med       Date:  2004-09-19       Impact factor: 53.440

10.  Methicillin-resistant Staphylococcus aureus in hospitals and the community: stealth dynamics and control catastrophes.

Authors:  B S Cooper; G F Medley; S P Stone; C C Kibbler; B D Cookson; J A Roberts; G Duckworth; R Lai; S Ebrahim
Journal:  Proc Natl Acad Sci U S A       Date:  2004-06-25       Impact factor: 11.205

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  14 in total

1.  Senescence and antibiotic resistance in an age-structured population model.

Authors:  Patrick De Leenheer; Jack Dockery; Tomás Gedeon; Sergei S Pilyugin
Journal:  J Math Biol       Date:  2009-11-12       Impact factor: 2.259

2.  Qualitative analysis of models with different treatment protocols to prevent antibiotic resistance.

Authors:  Hong-Rui Sun; Xinxin Lu; Shigui Ruan
Journal:  Math Biosci       Date:  2010-06-25       Impact factor: 2.144

3.  Mathematical modeling and the epidemiological research process.

Authors:  Mikayla C Chubb; Kathryn H Jacobsen
Journal:  Eur J Epidemiol       Date:  2009-10-27       Impact factor: 12.434

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

Authors:  D E Ramsay; J Invik; S L Checkley; S P Gow; N D Osgood; C L Waldner
Journal:  Epidemiol Infect       Date:  2018-07-31       Impact factor: 4.434

Review 5.  Modelling the transmission of healthcare associated infections: a systematic review.

Authors:  Esther van Kleef; Julie V Robotham; Mark Jit; Sarah R Deeny; William J Edmunds
Journal:  BMC Infect Dis       Date:  2013-06-28       Impact factor: 3.090

6.  Population Dynamics of Patients with Bacterial Resistance in Hospital Environment.

Authors:  Leilei Qu; Qiuhui Pan; Xubin Gao; Mingfeng He
Journal:  Comput Math Methods Med       Date:  2016-01-24       Impact factor: 2.238

Review 7.  Moving interdisciplinary science forward: integrating participatory modelling with mathematical modelling of zoonotic disease in Africa.

Authors:  Catherine Grant; Giovanni Lo Iacono; Vupenyu Dzingirai; Bernard Bett; Thomas R A Winnebah; Peter M Atkinson
Journal:  Infect Dis Poverty       Date:  2016-02-25       Impact factor: 4.520

8.  How to Use a Chemotherapeutic Agent When Resistance to It Threatens the Patient.

Authors:  Elsa Hansen; Robert J Woods; Andrew F Read
Journal:  PLoS Biol       Date:  2017-02-09       Impact factor: 8.029

9.  The impact of different antibiotic regimens on the emergence of antimicrobial-resistant bacteria.

Authors:  Erika M C D'Agata; Myrielle Dupont-Rouzeyrol; Pierre Magal; Damien Olivier; Shigui Ruan
Journal:  PLoS One       Date:  2008-12-29       Impact factor: 3.240

10.  How fitness reduced, antimicrobial resistant bacteria survive and spread: a multiple pig-multiple bacterial strain model.

Authors:  Kaare Græsbøll; Søren Saxmose Nielsen; Nils Toft; Lasse Engbo Christiansen
Journal:  PLoS One       Date:  2014-07-09       Impact factor: 3.240

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