Figure 1 - uploaded by Fabian Sailer
Content may be subject to copyright.
The female main chlamydia model Green states are infectious states, persons in red states know about their infection, orange states signalise, that screened persons will receive positive test results.
Source publication
Introduction: Chlamydia is a very common bacterial sexual transmitted
infection (STI) among young adults. High numbers of asymptomatic
cases hamper a timely treatment start, whereas the treatment itself is
efficient and cheap. Proactive screening can decrease this mismatch.
There are many models which are able to evaluate and simulate different
scr...
Context in source publication
Similar publications
Abstract Background Chlamydia infections are common in both men and women, are often asymptomatic and can cause serious complications. Repeat testing in high-risk groups is therefore indicated. In the Netherlands, guidelines on repeat chlamydia testing differ between testing facilities, and knowledge on repeat testing behaviour is limited. Here, we...
Citations
Background Human Immunodeficiency Virus (HIV) and other sexually transmitted infections (STIs) do not operate in isolation; people with risk-taking sexual behaviour in particular are more likely to be co-infected. In this complex landscape policy makers are limited by monetary constraints and still need to find optimal coverage solutions. Disease modelling could help in this context but modelling software accessible to decision makers examining various STIs and HIV is rare. Methods I developed an STI modelling software, using the programming language Java, consisting of a model for each STI and a graphical user interface. The models were drafted based on literature reviews and subsequently refined by experts, e.g. STI clinicians and policy makers. Afterwards, all models were internally and externally validated. The user interface was developed with user interface development experts and policy makers. The resulting software was validated using the MenSS trial. Results The software consists of different models, which serve individual purposes. All models are interacting, individual-based discrete event simulations. Separate disease models, which describe the progression of chlamydia, gonorrhoea, HIV, and syphilis, and their corresponding sequelae describe the progression of the respective infections. Sexual network models are used to describe the formation and dissolution of partnerships and thereby the occurrence of sexual contacts. A user can choose from four different network models which are included in the software. Clinical pathway models, which describe interventions, like screening or treatment for all included STIs, reflect the current English setting. All models have been validated using sensitivity analyses and publicly available data sources. The user interface has been validated by policy makers. Conclusion With this modelling software policy makers can compare intervention options, existing and hypothetical, to each other. All parameters, formulas, model structures, and clinical pathways are editable and well documented. The software is not bound to a specific research question but can be fitted for different scenarios to be reused and updated if needed, e.g. if medicinal knowledge changes. For example, by adapting parameters which describe treatment pathways the software can be used in non-English scenarios.
