VacSeen : semantically enriched automatic identification and data capture for improved vaccine logistics
Name
974652556-MIT.pdf
Description
Full printable version
Size
10.43 MB
Format
Adobe PDF
Checksum (MD5)
294e2588b80790e31615590073016b52
Author(s)
Bhattacharjee, Partha Sarathi, S.M. Massachusetts Institute of Technology
Advisor(s)
Sanjay Sarma.
Alternative Title
Vac Seen : semantically enriched automatic identification and data capture for improved vaccine logistics
Semantically enriched automatic identification and data capture for improved vaccine logistics
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
Vaccines 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.
Description
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2016.
Thesis: 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.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 79-82).
Subjects
Institute for Data, Systems, and Society.
System Design and Management Program.
Engineering Systems Division.
Technology and Policy Program.
MIT Department
System Design and Management Program.
Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Technology and Policy Program
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