No description available.

No description available.

No description available.

This thesis aims to explore the measurement of and the correlation between risky sexual behaviour and chlamydia and gonorrhoea infection in the UK in three chapters. The first of these explores methods of calculating rates of Chlamydia and gonorrhoea infection at UK genitourinary medicine (GUM) clinics. Data from KC60 returns from clinics in the Northwest, Southwest and East Midlands of England are used to provide a numerator for the rates and three methods are tested to derive the denominator: Thiessen polygons, 15 mile boundaries, and 30 minute drive times. The study finds that the rates calculated are relatively insensitive to the method chosen and thus the simplest approach, the Thiessen polygons, is recommended. The analysis also highlights substantial regional differences in GUM service accessibility. The second chapter uses latent class analysis to derive a measure of risky sexual behaviour with respect to chlamydia and gonorrhoea infection. Data from the National Survey of Sexual Attitudes and Lifestyles II, a nationally representative survey of sexual behaviour in Britain, has been analysed in order to identify patterns of behaviours associated with increased disease risk A 3-class solution is obtained, with individuals classified on the basis of the number of partners they have had in the last 12 months. iii The third chapter examines the relationship between the rates of chlamydia and gonorrhoea infection and the measure of risky sexual behaviour. Small area estimates of risky behaviour are obtained for all wards in England using synthetic regression methods. These are then aggregated in line with the Thiessen polygons in order to explore the correlation with the rates of chlamydia and gonorrhoea infection. There is a positive correlation for both infections, but far stronger for gonorrhoea than chlamydia (r=0.70 and r=0.41 respectively), suggesting that although risky behaviour may explain some of the observed variation, further research is need to explore other possible explanations.

Sexually Transmitted Infections (STIs) are a priority of many health services. Chlamydia Trachomatis (Chlamydia) is one of the most common STIs in the world. Chlamydia can have serious consequences for men and women in the form of infertility and particularly in women has been associated with Pelvic Inflammatory Disease (PID). A System Dynamics (SD) model of Chlamydia prevalence has been constructed to evaluate different screening strategies. The SD model incorporates risk groups, ageing, gender, heterosexual and homosexual relationships and migration in and out of the area of interest. A Discrete Event Simulation (DES) model has been constructed of the Genito-urinary Medicine (GUM) department at St Mary’s Hospital, Portsmouth, the department that treats patients presenting with STIs to enable healthcare professionals evaluate different GUM configurations. A composite model has been developed in which the SD model provides the demand (number of patients) to be treated in the GUM DES model each month. The DES model transforms the demand generated by the SD model into patient arrival patterns based on historically recorded data. The DES model processes the demand based on its current configuration and provides the number of treated patients back to the SD model. The DES model and the SD model can be run independently as stand-alone models or in the composite state through a simple Excel user interface. Results from each model are presented and model development discussed. The simulation models were developed in close collaboration with healthcare professionals. The models were informed by other methodologies including: regression analysis of socioeconomic data, geographical referencing of infection data and a behavioural survey to identify behaviours associated with STI infection