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Modeling reduction of pandemic influenza using pharmaceutical and non pharmaceutical interventions in a heterogeneous population

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dc.contributor.advisor Richard C. Larson. en_US
dc.contributor.author Teytelman, Anna en_US
dc.contributor.other Massachusetts Institute of Technology. Operations Research Center. en_US
dc.date.accessioned 2012-09-13T18:56:06Z
dc.date.available 2012-09-13T18:56:06Z
dc.date.copyright 2012 en_US
dc.date.issued 2012 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/72847
dc.description Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012. en_US
dc.description Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references. en_US
dc.description.abstract In an event of a pandemic influenza outbreak such as the great "Spanish Flu" of 1918 and the more recent 2009-2010 H1N1 "Swine Flu" scare, pharmaceutical as well as non-pharmaceutical resources are limited in availability and effectiveness. In this thesis we apply OR methods to evaluate the effectiveness of such resources and the strategies for reducing the number of infections resulting from an outbreak. In the first half of this work, we focus on epidemiological analysis of influenza modeling in a heterogeneous population. The majority of existing epidemiological literature models influenza spread in a statistically homogeneous population, but the model-based inclusion of heterogeneity by contact rate, susceptibility, and infectivity introduces significant effects on disease progression. We introduce a new discrete-time influenza outbreak model for a heterogeneous population and use it to describe the changes in a population's flu-related characteristics over time. This information allows us to evaluate the effectiveness of different vaccine targeting techniques in achieving herd immunity, that is, the point at which there is no further growth in new infections. In the second half of this work we switch to a practical application of OR methods in a pandemic situation. We evaluate the effectiveness of vaccines administered to US states during the 2009-2010 H1N1 pandemic. Since the US is geographically diverse and large, the outbreak progressed at different rates and started at different times in each individual state. We discuss dynamic, multi-regional, vaccine allocation schemes for large geographical entities that take into account the different conditions of the epidemic in each region and maximize the total effect of available vaccines. In addition, we discuss effective strategies for combining vaccines with non-pharmaceutical interventions such as hand-washing and public awareness campaigns to decrease the strain of an outbreak on the population. en_US
dc.description.statementofresponsibility by Anna Teytelman. en_US
dc.format.extent 159 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.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.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Operations Research Center. en_US
dc.title Modeling reduction of pandemic influenza using pharmaceutical and non pharmaceutical interventions in a heterogeneous population en_US
dc.type Thesis en_US
dc.description.degree Ph.D. en_US
dc.contributor.department Massachusetts Institute of Technology. Operations Research Center. en_US
dc.identifier.oclc 807200779 en_US


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