In this paper we present Gryphon, a hybrid agent-based stochastic modeling and simulation platform developed for characterizing the geographic spread of infectious diseases and the effects of interventions. We study both local and non-local transmission dynamics of stochastic simulations based on the published parameters and data for SARS. The results suggest that the expected numbers of infections and the timeline of control strategies predicted by our stochastic model are in reasonably good agreement with previous studies. These preliminary results indicate that Gryphon is able to characterize other future infectious diseases and identify endangered regions in advance. © Springer-Verlag Berlin Heidelberg 2010.
CITATION STYLE
Yu, B., Wang, J., Mcgowan, M., Vaidyanathan, G., & Younger, K. (2010). Gryphon: A hybrid agent-based modeling and simulation platform for infectious diseases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6007 LNCS, pp. 199–207). https://doi.org/10.1007/978-3-642-12079-4_26
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