Development of a multi-Sexually transmitted infections decision modelling tool for use by health care professionals, policy makers and analysts.

Conference:

SAPC ASM 2017 - Warwick

Talk Code:

EP2D.04

Presenter:

Fabian Sailer

Co-authors:

John Saunders, Greta Rait, Rachael Hunter

Author institutions:

University College London, Department of Primary Care and Population Health; University College London, Centre for Sexual Health and HIV Research, Research Department of Infection and Population Health

Problem

Sexually transmitted infections (STI) affect the sexual health and general wellbeing of patients. STIs do not operate in isolation and patients with one STI are likely to have a secondary simultaneous infection. The main reason for this is risky sexual behaviour, like frequent partner changes and concurrent sexual partnerships. Furthermore, but to a smaller extent, the immune system is weakened by the presence of a STI, which increases the possibility of getting another STI. It might help to understand the sexual health of a cohort by examining multiple STIs at once.The early detection of STIs and interventions tailored to high risks groups can decrease the disease burden and health care expenses. Disease modelling helps to evaluate these interventions. By conducting a literature review we found that the majority of STI models only covers single STIs or no more than two STIs, opposing the before mentioned need to examine multiple STIs and their interactions simultaneously.

Approach

To overcome this problem we set up a multi-STI model which includes the most important STIs in the UK. We will embed this model in a user friendly computer program. Therefore, everyone interested in understanding the landscape of STIs in a certain cohort can easily conduct analyses. This cohort might be the population of a borough, the patients of a GUM clinic or all of England.Our model uses a discrete event simulation approach to model different STIs and connected sequelae at the same time. This enables the user to evaluate the total arising costs and outcomes for all modelled STIs. These outputs can help to compare different interventions.

Findings

So far, we have set up a prototype which simulates Chlamydia and Genital Herpes. Pelvic Inflammatory Disease, Tubal Infertility, Ectopic Pregnancy, Chronic Pelvic Pain, Cervicitis, Urethritis, Epididymitis, and Male Infertility as well as Neonatal Pneumonia, and Neonatal Conjunctivitis are included into the model as possible sequelae. The model is designed in a flexible way so that it can easily be adapted as changes in medical knowledge emerge.We currently develop user interfaces in cooperation with end-users. This inclusive development process guarantees to customize the computer program to the needs of potential users.

Consequences

The final easy-to-use tool will support decision makers in venereal disease medicine to find interventions tailored to the specific needs of certain cohorts. This will help to decrease the overall STI incidence so that limited health care resources are no longer occupied by preventable cases of STI.

Submitted by:

Fabian Sailer

Funding acknowledgement:

This research is funded by the National Institute for Health Research School for Primary Care Research (NIHR SPCR). The views are those of the author(s) and not necessarily those of the NIHR, the NHS or the Department of Health.