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Gryphon: A Hybrid Agent-Based Modeling and Simulation Platform for Infectious Diseases

  • Bin Yu
  • Jijun Wang
  • Michael McGowan
  • Ganesh Vaidyanathan
  • Kristofer Younger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6007)

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.

Keywords

Group Agent Stochastic Simulation Severe Acute Respiratory Syndrome Simulation Platform Secondary Group 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Bin Yu
    • 1
  • Jijun Wang
    • 1
  • Michael McGowan
    • 1
  • Ganesh Vaidyanathan
    • 1
  • Kristofer Younger
    • 1
  1. 1.Quantum Leap InnovationsNewarkUSA

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