The University of Liverpool
Department of Mathematical Sciences
Division of Statistics and Probability
SEMINAR
Modelling Healthcare Associated Infections: A Bayesian Approach
Dr Theodore Kypraios,
Wednesday, 7th November, 2pm
The Whittaker Room (211)
Abstract:
There are large knowledge gaps in both the epidemiology and population biology of major nosocomial pathogens such as methicillin-resistant Staphylococcus aureus (MRSA) and glycopeptide-resistant enterococci (GRE). We are interested in answering questions such as: what enables some strains to spread more rapidly than others? how do different antibiotics select for different can control measures be quantitatively assessed?
A biologically meaningful stochastic epidemic model is proposed in order to address such questions and explain in more detail the dynamics of the spread of these major nosocomial pathogens. Having obtained very detailed data sets, we show how Markov Chain Monte Carlo (MCMC) methods, enable us to draw efficient inference for the key parameters governing transmission. Furthermore, a Reversible-Jump Markov Chain Monte Carlo
(RJMCMC) algorithm is applied to compare different models. Finally, the
methodology is illustrated by analysing real data which were obtained from a hospital in Boston. This is joint work with Phil O'Neill and Ben Cooper.
Following the talk, tea and biscuits will be available in Room 304
ALL WELCOME
*************************************************
Ingrid Harper
Division of Statistics and Probability
Department of Mathematical Sciences
University of Liverpool
Mathematical Sciences Building
Peach Street
Liverpool L69 7ZL
Tel: 0151 794 4751
Fax: 0151 794 4754
*************************************************
|