A Cellular Automaton Framework for Infectious Disease Spread Simulation
Bernhard Pfeifer*, 1, Karl Kugler2, Maria M Tejada1, Christian Baumgartner1, Michael Seger1, Melanie Osl1, Michael Netzer1, Michael Handler1, Andreas Dander1, Manfred Wurz3, Armin Graber2, Bernhard Tilg1
Identifiers and Pagination:Year: 2008
First Page: 70
Last Page: 81
Publisher Id: TOMINFOJ-2-70
Article History:Received Date: 18/1/2008
Revision Received Date: 27/3/2008
Acceptance Date: 9/4/2008
Electronic publication date: 24/4/2008
Collection year: 2008
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/license/by/2.5/), which permits unrestrictive use, distribution, and reproduction in any medium, provided the original work is properly cited.
In this paper, a cellular automaton framework for processing the spatiotemporal spread of infectious diseases is presented. The developed environment simulates and visualizes how infectious diseases might spread, and hence provides a powerful instrument for health care organizations to generate disease prevention and contingency plans. In this study, the outbreak of an avian flu like virus was modeled in the state of Tyrol, and various scenarios such as quarantine, effect of different medications on viral spread and changes of social behavior were simulated.
The proposed framework is implemented using the programming language Java. The set up of the simulation environment requires specification of the disease parameters and the geographical information using a population density colored map, enriched with demographic data.
The results of the numerical simulations and the analysis of the computed parameters will be used to get a deeper understanding of how the disease spreading mechanisms work, and how to protect the population from contracting the disease. Strategies for optimization of medical treatment and vaccination regimens will also be investigated using our cellular automaton framework.
In this study, six different scenarios were simulated. It showed that geographical barriers may help to slow down the spread of an infectious disease, however, when an aggressive and deadly communicable disease spreads, only quarantine and controlled medical treatment are able to stop the outbreak, if at all.