Literature DB >> 21077707

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

Avner Friedman1, Najat Ziyadi, Khalid Boushaba.   

Abstract

Antibiotic resistant organisms (ARO) pose an increasing serious threat in hospitals. One of the most life threatening ARO is methicillin-resistant staphylococcus aureus (MRSA). In this paper, we introduced a new mathematical model which focuses on the evolution of two bacterial strains, drug-resistant and non-drug resistant, residing within the population of patients and health care workers in a hospital. The model predicts that as soon as drug is administered, the average load of the non-resistant bacteria will decrease and eventually (after 6 weeks of the model's simulation) reach a very low level. However, the average load of drug-resistant bacteria will initially decrease, after treatment, but will later bounce back and remain at a high level. This level can be made lower if larger amount of drug is given or if the contact between health care workers and patients is reduced.

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Year:  2010        PMID: 21077707     DOI: 10.3934/mbe.2010.7.779

Source DB:  PubMed          Journal:  Math Biosci Eng        ISSN: 1547-1063            Impact factor:   2.080


  5 in total

1.  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 2.  What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature.

Authors:  Maria Arepeva; Alexey Kolbin; Alexey Kurylev; Julia Balykina; Sergey Sidorenko
Journal:  Front Microbiol       Date:  2015-04-29       Impact factor: 5.640

Review 3.  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

4.  Population-level mathematical modeling of antimicrobial resistance: a systematic review.

Authors:  Anna Maria Niewiadomska; Bamini Jayabalasingham; Jessica C Seidman; Lander Willem; Bryan Grenfell; David Spiro; Cecile Viboud
Journal:  BMC Med       Date:  2019-04-24       Impact factor: 8.775

5.  Send more data: a systematic review of mathematical models of antimicrobial resistance.

Authors:  Anna Camilla Birkegård; Tariq Halasa; Nils Toft; Anders Folkesson; Kaare Græsbøll
Journal:  Antimicrob Resist Infect Control       Date:  2018-09-29       Impact factor: 4.887

  5 in total

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