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The development of a combined simulation approach in a sexual health context: combining discrete event and system dynamics simulation to form a composite model

Viana, Joe (2011) The development of a combined simulation approach in a sexual health context: combining discrete event and system dynamics simulation to form a composite model University of Southampton, School of Management, Doctoral Thesis , 387pp.

Record type: Thesis (Doctoral)


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

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Published date: 31 March 2011
Organisations: University of Southampton


Local EPrints ID: 191859
PURE UUID: e31636d9-2b5a-4542-8f51-756fff20a72e

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Date deposited: 05 Jul 2011 14:46
Last modified: 18 Jul 2017 11:34

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Author: Joe Viana
Thesis advisor: Sally Brailsford

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