Gryphon: A Hybrid Agent-Based Modeling and Simulation Platform for Infectious Diseases
Identifieur interne : 000273 ( Istex/Curation ); précédent : 000272; suivant : 000274Gryphon: A Hybrid Agent-Based Modeling and Simulation Platform for Infectious Diseases
Auteurs : Bin Yu [États-Unis] ; Jijun Wang [États-Unis] ; Michael Mcgowan [États-Unis] ; Ganesh Vaidyanathan [États-Unis] ; Kristofer Younger [États-Unis]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
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.
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DOI: 10.1007/978-3-642-12079-4_26
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wicri:rule="url">États-Unis</country></affiliation></author></analytic><monogr></monogr><series><title level="s" type="main" xml:lang="en">Lecture Notes in Computer Science</title><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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