Gryphon: a hybrid agent-based modeling and simulation platform for infectious diseases

Authors:
Bin Yu;Jijun Wang;Michael McGowan;Ganesh Vaidyanathan;Kristofer Younger
Affiliations:
Quantum Leap Innovations, Newark, DE;Quantum Leap Innovations, Newark, DE;Quantum Leap Innovations, Newark, DE;Quantum Leap Innovations, Newark, DE;Quantum Leap Innovations, Newark, DE
Venue:
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
Year:
2010

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Abstract

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.