The aim of this work is to examine, define and interpret dynamic effects on the spread of epidemics
through the use of different models. This approach is heavily based on the consequent application of
agent based models, which simulate the spread of a disease as a consequence of transmission from
person to person, and Markov models, which are based on stochastic processes. Thanks to its structure,
the former approach is able to create real effects, while the latter approach uses given transition
probabilities, and hence is not able to produce feedback effects.
Comparison of the modeling approaches allows analyzing the underlying dynamics and finding sufficiently
flexible definitions for correct interpretations and valid simulations of the consequences of
vaccination strategies against epidemics.
The aim of this work is to examine, define and interpret dynamic effects on the spread of epidemics
through the use of different models. This approach is heavily based on the consequent application of
agent based models, which simulate the spread of a disease as a consequence of transmission from
person to person, and Markov models, which are based on stochastic processes. Thanks to its structure,
the former approach is able to create real effects, while the latter approach uses given transition
probabilities, and hence is not able to produce feedback effects.
Comparison of the modeling approaches allows analyzing the underlying dynamics and finding sufficiently
flexible definitions for correct interpretations and valid simulations of the consequences of
vaccination strategies against epidemics.
Florian Miksch dwh Simulation Servicesr Neustaiftgasse 57-59, 1070, Vienna, Austria Email: florian.miksch@dwh.at Prof. Dr. D. Murray-Smith (EUROSIM / ASIM) Prof. Dr. F. Breitenecker (ARGESIM / ASIM) Prof. Dr.-Ing. Th. Pawletta (ASIM)