Thesis Topic Details

Topic ID:
918
Title:
Bacterial evolution: modelling the dynamics of antibiotic resistance
Supervisor:
Mark Tanaka
Research Area:
Modelling
Associated Staff
Assessor:
Bruno Gaeta
Topic Details
Status:
Active
Type:
Research
Programs:
BINF
Group Suitable:
No
Industrial:
No
Pre-requisites:
--
Description:
Bacteria are known to evolve resistance to antibiotics within years of the introduction of any drug. The rising frequency of antibiotic resistance raises public health concerns about the future treatability of bacterial infections. Drug resistance genes are known to induce a reproductive fitness cost to bacteria in the absence of drugs. One possible public health strategy is therefore to use drugs prudently and sparingly with the hope that there will be a reversion to sensitivity in the bacterial population. A hindrance to this approach, however, is that resistant bacteria evolve further to reduce the cost of resistance in the absence of drugs, thereby reducing the competitive advantage of sensitive strains. The aim of this project is to understand these complex dynamics through mathematical and computational models. Through these models the effectiveness of the prudent-use approach can be evaluated.
Comments:
Past Student Reports
  Alexander WONG in s1, 2011
Bacterial evolution: modelling the dynamics of antibiotic resistance
  Natalia VAUDAGNOTTO in s2, 2013
Bacterial evolution: modelling the dynamics of antibiotic resistance
 

Download report from the CSE Thesis Report Library

NOTE: only current CSE students can login to view and select reports to download.