Main purpose of project Burden of Disease was the analysis of health-care needs of Austria’s population. Hereby project was subdivided into two consecutive sub-projects: GEPOC (Generic Population Concept) dealt with the question, how Austria’s population is currently structured and how it might possibly be structured in several years. Results were necessary pre-work of the second sub-project TOMAP (Tools for Morbidity Analysis & Prognosis). Hereby, based on GEPOC, the further impact of diseases was investigated in order to generate prognoses for current and future morbidity levels in Austria. Furthermore Project 5 (Intervention and Planning) is directly based on the results of this project.
The goals of this project can be summarised as follows:
Development of a dynamic computer simulation model able to validly simulate Austria’s population for up to 50 years.
As the resulting model not only poses the basis for all other subprojects of Burden of Disease, but also for most research in Project 5, it was not possible to decide which modelling technique will be the most suitable one right from the start. Hence not only one, but a series of different population models were developed, tested, compared and finally summarised in a handbook – the “Generic Population Concept” (GEPOC).
Development of a prognostic simulation model for the level of morbidity in Austria.
Hereby we developed tools to make prognoses for the distribution of Austrian people suffering from chronic or infectious diseases (TOMAP). Especially the occurrence of simultaneously occurring diseases (comorbidity) posed a huge challenge here.
Tests of the tools on certain (multiple) diseases.
In order to validate the tools (i.e. make sure, that the model accurately describes the real system) it was crucial that we thoroughly tested them on real applications. Hereby questions arised which were and are tackled in other applied projects.
In general methods developed in Project 6 ‘Dynamics Analysis’ were applied to develop simulation models for GEPOC and TOMAP. Different modelling methods like agent-based modelling, discrete-event simulation and system dynamics were used to develop different population model concepts. Two different approaches were implemented as proof-of-concept. Further conceptual developments lead to morbidity modelling which focuses on two areas: Representing the current situation and predicting future trends. Again, two approaches have been implemented which ensured overall quality of the models and provided insights on the impact of the methodological differences on results. The first was based on so called panel analysis by tracing statistically generated fictional individuals over a certain time-span, the second on dynamic modelling.
The findings of the project help to better analyse and predict the burden of disease in order to inform decision makers about the state of the health care system. Based on this information, they now can make decisions about planning aspects of care and interventions much more accurately.