Title :
Modeling the spread of antibiotic resistance
Author :
Hallinan, J.S. ; Wiles, J.
Author_Institution :
Dept. of Comput. Sci. & Electr. Eng., Queensland Univ., Brisbane, Qld., Australia
Abstract :
This paper describes a stochastic implementation of Austin et al.´s (1999) model of the spread of antibiotic resistance in a population of fixed size under varying conditions of antibiotic use. The population is divided into sub-groups: individuals colonized by commensal bacteria and an uncolonized group. The colonized group is further divided according to whether the commensal bacteria are sensitive or resistant to antibiotics. This study uses Monte Carlo techniques to model the dynamics of the evolution of the antibiotic resistant population, a study that cannot be done in the original model. The Monte Carlo approach allows the investigation of the transient dynamics of the spread of resistance, the effects of finite (especially small) populations and the interaction of model parameters
Keywords :
Monte Carlo methods; evolutionary computation; medical computing; patient treatment; Monte Carlo techniques; antibiotic resistance spread modeling; antibiotic resistant population evolution; commensal bacteria; stochastic implementation; transient dynamics; Antibiotics; Computer science; Electric resistance; Immune system; Medical treatment; Microorganisms; Monte Carlo methods; Psychology; Public healthcare; Stochastic processes;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870778