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dc.contributor.advisorSanjay Sarma.en_US
dc.contributor.authorBhattacharjee, Partha Sarathi, S.M. Massachusetts Institute of Technologyen_US
dc.contributor.otherTechnology and Policy Program.en_US
dc.date.accessioned2017-03-20T19:41:07Z
dc.date.available2017-03-20T19:41:07Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/107582
dc.descriptionThesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2016.en_US
dc.descriptionThesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, System Design and Management Program, 2016.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 79-82).en_US
dc.description.abstractVaccines are globally recognized as a critical public health intervention. Routine immunization coverage in large parts of the developing world is around 80%. Technology and policy initiatives are presently underway to improve vaccine access in such countries. Efforts to deploy AIDC technologies, such as barcodes, on vaccine packaging in developing countries are currently ongoing under the aegis of the 'Decade of Vaccines' initiative by key stakeholders. Such a scenario presents an opportunity to evaluate novel approaches for enhancing vaccine access. In this thesis I report the development of VacSeen, a Semantic Web technology-enabled platform for improving vaccine access in developing countries. Furthermore, I report results of evaluation of a suite of constituent software and hardware tools pertaining to facilitating equitable vaccine access in resource-constrained settings through data linkage and temperature sensing. I subsequently discuss the value of such linkage and approaches to implementation using concepts from technology, policy, and systems analysis.en_US
dc.description.statementofresponsibilityby Partha Sarathi Bhattacharjee.en_US
dc.format.extent82 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectInstitute for Data, Systems, and Society.en_US
dc.subjectSystem Design and Management Program.en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectTechnology and Policy Program.en_US
dc.titleVacSeen : semantically enriched automatic identification and data capture for improved vaccine logisticsen_US
dc.title.alternativeVac Seen : semantically enriched automatic identification and data capture for improved vaccine logisticsen_US
dc.title.alternativeSemantically enriched automatic identification and data capture for improved vaccine logisticsen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Technology and Policyen_US
dc.description.degreeS.M. in Engineering and Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society.en_US
dc.contributor.departmentSystem Design and Management Program.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.contributor.departmentTechnology and Policy Program.en_US
dc.identifier.oclc974652556en_US


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