This thesis presents research on the epidemiology and transmission dynamics of healthcare-associated infections (HCAI) and focuses on the antibiotic resistant hospital pathogen methicillin-resistant Staphylococcits aureus (MRSA). First, a stochastic mathematical model of MRSA transmission dynamics is developed in which patient movement within and between both hospital and community populations is considered. The effects on transmission of both surveillance and control within this setting are explored. Significant interplay is found to exist between surveillance and control; surveillance is shown to be essential to control success and in addition allows quantification of the level of control achieved. Furthermore, patient movement between hospital and community populations is shown to have a considerable impact on transmission dynamics and on the success of infection control strategies. Analyses of the demographics of a hospital population using a real hospital dataset are presented and the heterogeneous nature of the patient population described. Differences in admission patterns and length of hospital stay between age groups, gender and speciality are explored. Combining these analyses highlights the patient groups constituting the majority of patient days. Further to this, the heterogeneous nature of patient readmissions is described and the existence of a 'core group' of most frequently readmitted patients is illustrated. Overall, readmissions are found to be far more likely than previously thought, with the majority of patient admissions to hospital being readmissions. Given this finding of increased readmission, the hospital admission data is used to inform the development of a model in which real patient movements between the hospital and community are simulated and transmission within this setting explored. Endemic behaviour results and the change in movement patterns is found to influence control strategy success. Further to this, the model is extended to simulate transmission within a multi-centre setting where patient movements within a three-hospital and community network are simulated. This increase in heterogeneity within the patient population appears to allow endemic behaviour throughout all hospitals 11 within the network.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:487985 |
| Date | January 2007 |
| Creators | Robotham, Julie |
| Publisher | University of Warwick |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://wrap.warwick.ac.uk/4105/ |
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