|Profession - modelbygger, 3. modul, 2006, id:345|
|Findes på RUb:||Ja|
Developing epidemiological models extend an important scientitic field of research within mathematical populations biology. Some of the most highly applied models are the classical SIR- and SEIR-models that descripe the dynamical pattern in a population exposed to a given disease. This paper contains an expansion of the SIR-model to a TSIR-model that incorporates timeseries, and the model is used on a set of data consisting of births and easles infected individuals in the years 1900-1967 in Copenhagen county. The group of susceptibles is reconstructed from the number of births by statistical regression modelling, and the amount of measles infected individuals is reproduced from the reconstructed susceptibles. Due to lack of stationarity in the susceptible group it turns out that the model is not adequate in its way of reproducing measles infected individuals in the original timeperiod. Meanwhile it is to som extend possible to gain a reproduction of the measles infected individuals when the model is applied to an appropriate time interval where the susceptibles exposes a relatively great stationarity. Thereby it is concluded that the useability of the model presumes that it is employed on a set of data that exposes a great deal of stationarity in the susceptible group in the entire modelled period.