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dc.contributor.advisorRichard Larson.en_US
dc.contributor.authorZhang, Hui, S.M. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Computation for Design and Optimization Program.en_US
dc.date.accessioned2010-05-25T20:40:25Z
dc.date.available2010-05-25T20:40:25Z
dc.date.copyright2009en_US
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/55088
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2009.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 69-70).en_US
dc.description.abstractThe purpose of this project is to incorporate a Poisson disease model into the Spatiotemporal Epidemiological Modeler (STEM) and visualize the disease spread on Google Earth. It is done through developing a Poisson disease model plug-in using the Eclipse Modeling Framework (EMF), a modeling framework and code generation facility for building tools and other applications based on a structured data model. The project consists of two stages. First, it develops a disease model plug-in of a Poisson disease model of a homogenous population, which is built as an extension of the implemented SI disease model in the STEM. Next, it proposes an algorithm to port a Poisson disease model of a heterogeneous population into the STEM. The development of the two new diseases plugins explores the maximum compatibility of the STEM and sets model for potential users to flexibly construct their own disease model for simulation.en_US
dc.description.statementofresponsibilityby Hui Zhang.en_US
dc.format.extent75 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectComputation for Design and Optimization Program.en_US
dc.titleModelling pandemic influenza progression using Spatiotemporal Epidemiological Modeller (STEM)en_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computation for Design and Optimization Program
dc.identifier.oclc587614987en_US


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