A system dynamics model for the diabetes prevalence in Austria / Peter Kristöfel
VerfasserKristöfel, Peter
Begutachter / BegutachterinBreitenecker, Felix
UmfangVII, 74 S. : graph. Darst.
HochschulschriftWien, Techn. Univ., Dipl.-Arb., 2007
Zsfassung in dt. Sprache
Bibl. ReferenzOeBB
Schlagwörter (DE)Systemdynamik / Modellbildung / Simulation / nichtlineare, algebraische Integro-Differentialgleichungssysteme / Sozio-Ökonomie / Typ-2 Diabetes Mellitus / Gesundheitswesen
Schlagwörter (EN)System Dynamics / modelling / simulation / nonlinear, algebraic intergo-differentialequation systems / socio-economics / type-2 diabetes mellitus / health care system /
URNurn:nbn:at:at-ubtuw:1-16051 Persistent Identifier (URN)
 Das Werk ist frei verfügbar
A system dynamics model for the diabetes prevalence in Austria [3.23 mb]
Zusammenfassung (Deutsch)

Type-2 diabetes mellitus is on the advance in aging affluent society. As a chronic disease with severe consequences it poses a major health care challenge. The question is how to best manage this serious threat to public health. In this thesis we develop a system dynamics model for the type-2 diabetes prevalence in Austria. There are many different input variables and they change discontinuously with time. The statistical surveys to obtain these data were performed selectively, just for some characteristics at different times, and not all parameters are available. On the one hand this makes a model relying only on statistics impossible, on the other hand these restrictions influence the structure of the dynamic model. So the modelling of the course of the disease in the population leads to a system of coupled, nonlinear, algebraic integro-differential equations with discrete changes in state with time.

Therefore System Dynamics is the method of choice. Modern System Dynamics programs allow the calculation of the time development of such a system. A model developed by J.Homer et al. for the USA is adopted to the health care system in Austria and the available data. It is enhanced further, especially a distinction by sex is introduced, since there is a gender-specific risk to develop type-2 diabetes. The available input data is implemented in the model to reproduce the correct historic prevalence of diabetes in Austria. The stability of the system is examined with statistical and Monte-Carlo methods. Then some experiments with the model, analogous to ongoing studies but with a larger population, are made. Parameters with which the success of different measures can be evaluated are identified.

Future work may include the extension of the model to people from a different social background or the connection with a model for the adipositas prevalence, since there is a strong correlation.