A FRAMEWORK OF EPIDEMIC MODELING CONSIDERING PREVENTIVE BEHAVIORS: COMPARTMENTAL MODELING, TEXT ANALYTICS, AND MACHINE LEARNING

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dc.contributor.advisorShehab, Randa
dc.contributor.authorCho, Hyejin
dc.contributor.committeeMemberNicholson, Charles
dc.contributor.committeeMemberRaman, Shivakumar
dc.contributor.committeeMemberZhu, Rui
dc.contributor.committeeMemberHougen, Dean
dc.contributor.committeeMemberSong, Hairong
dc.date.accessioned2024-05-15T14:13:22Z
dc.date.available2024-05-15T14:13:22Z
dc.date.issued2024-04-25
dc.date.manuscript2024-04-25
dc.description.abstractThe goal of this research is to provide a novel framework for epidemic modeling incorporating metrics derived from social media to predict epidemic dynamics and to estimate the impact of preventive behaviors. This study employs empirical data collected from Centers for Diseases Control and Prevention, and Twitter (or X) to demonstrate the practical usability of the proposed framework. Specifically, this research utilizes optimization, simulation, and compartmental differential equations to predict the number of infected and deceased individuals. The research estimates the basic reproduction number (R0) for diseases dynamics. In addition, this study utilizes artificial intelligence and develops a self-training machine learning algorithm to predict the individual compliance level with prevention behaviors. In the analysis, the effect of preventive behaviors on mitigating transmission is evaluated quantitatively. The research contributes to enhance the accuracy of epidemic modeling and to improve decision-making within public healthcare systems, ultimately leading to a reduction in mortality rates and the saving of more lives.en_US
dc.identifier.urihttps://hdl.handle.net/11244/340348
dc.languageen_USen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectIndustrial Engineeringen_US
dc.subjectEpidemic Modelingen_US
dc.subjectHealthcare Policiesen_US
dc.subjectText Analytics and Machine Learningen_US
dc.thesis.degreePh.D.en_US
dc.titleA FRAMEWORK OF EPIDEMIC MODELING CONSIDERING PREVENTIVE BEHAVIORS: COMPARTMENTAL MODELING, TEXT ANALYTICS, AND MACHINE LEARNINGen_US
ou.groupGallogly College of Engineering::School of Industrial and Systems Engineeringen_US
shareok.nativefileaccessrestricteden_US
shareok.orcidhttps://orcid.org/0000-0001-5080-4734en_US

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