This page is focused on the developing of Markov Models.
Markov Models are models simulating the progress of diseases for economic calculations. These models are rather complex and complicated. For people without previous knowledge it is difficult to understand the process of creating such a model. The following tutorial deals with the creation process of an example model to simulate the course of a disease. This creating of a model is explained in a comprehensible way, the model being based on influenza. It is meant to act as an introduction into working with models, like those you can find on the open source project prosit.de.
The Cold River Team
To establish the basis of a good Model, you need significant data. The following three points will be helpful to find this data.
How to develop the Model's structure
After finding data, finding the models structure is the next point to do.
The model alludes to a very simplified course of the disease. Cases of death as a direct result of an infection and the disease's outbreak, are mostly the consequence of complications from especially sensitive patients. Not each single complication was listed in order to keep the model simple. That is the reason why the significance of the model is not very high. The economical aspect was left out as well, because the superficial assignment was to generate the Markov Model, so treatment expenses were not included in the modeling. To complete a model all incoming costs, e.g. treatment fees, drug costs that have to be researched, as well as labor costs. Of particular importance for this paper was it to clarify, how modeling happens in general and what one has to pay attention to during the individual operations.
This seminar paper can give only a small insight in creating Markov Models. It is not possible to pay attention to all aspects in such a short time, especially the demands of quality were neglected. We can recommend good surveys about this aspect, like MiltonC.Weinstein2003 and LouisP.Garrison2003. Also Elstein2001 and Sonnernberg1993 as well as Sculper1998 are good sources to find out more about Markov Models and help completing the descriptions in this paper.
Sources and auxiliaries