Stochastic modelling and Bayesian inference for the effect of antimicrobial treatments on transmission and carriage of nosocomial pathogens
Verykouki, Eleni (2013) Stochastic modelling and Bayesian inference for the effect of antimicrobial treatments on transmission and carriage of nosocomial pathogens. PhD thesis, University of Nottingham.
Nosocomial pathogens are usually organisms such as fungi and bacteria that are associated with infections caused in a hospital environment. Examples include Clostridium difficile, Pseudomonas aeruginosa, Vancomycin-resistant enterococcus and Methicillin-resistant Staphylococcus aureus (MRSA). MRSA, like most of the nosocomial pathogens, is resistant to antibiotics and is one of the most serious causes of infections. In this thesis we assess the effects of antibiotics and antiseptics on carriage and transmission of MRSA. We use highly detailed patient level data taken from two Intensive Care Unit (ICU) wards in St. Guys and Thomas’s hospital in London, where patients were receiving daily antimicrobial treatment and a decolonisation protocol was used. We work in discrete time and employ three different patient-level stochastic models in a Bayesian framework to explore the effectiveness of antimicrobial treatment on MRSA in discrete time. We also develop suitable methods of model assessment.
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