Improving disease outbreak forecasting models for efficient targeting of public health resources

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dc.contributor.authorFernando, Lasantha
dc.contributor.authorPerera, Amal
dc.contributor.authorLokanathan, Sriganesh
dc.date.accessioned2018-04-09T17:18:41Z
dc.date.available2018-04-09T17:18:41Z
dc.date.issued2018-03
dc.description.abstractThe forecasting models developed in this work can be utilized to effect better resource mobilisation for combatting dengue. For understanding human mobility in disease propagation, Mobile Network Big Data (MNBD) is a low cost data exhaust that provides rich insight into human mobility patterns, including better spatial and temporal granularity. Research focuses on the development of a human mobility model, using MNBD that can accurately depict aggregate human population movements in Sri Lanka, and from this determine which machine learning technique provides the best disease forecasting model.en
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10625/56923
dc.language.isoen
dc.subjectDENGUEen
dc.subjectNEGLECTED TROPICAL DISEASESen
dc.subjectDISEASE OUTBREAK FORECASTINGen
dc.subjectDISEASE SURVEILLANCEen
dc.subjectRESOURCE ALLOCATIONen
dc.subjectMOBILE PHONE NETWORKSen
dc.subjectBIG DATAen
dc.subjectSRI LANKAen
dc.subjectDISEASE VECTORSen
dc.subjectTROPICAL DISEASESen
dc.subjectMOBILE NETWORKSen
dc.subjectMACHINE LEARNINGen
dc.subjectDATA COLLECTION METHODOLOGYen
dc.subjectSOUTH ASIAen
dc.titleImproving disease outbreak forecasting models for efficient targeting of public health resourcesen
dc.typeJournal Article (peer-reviewed)en
idrc.dspace.accessOpen Accessen
idrc.project.componentnumber108008001
idrc.project.number108008
idrc.project.titleLeveraging Mobile Network Big Data for Developmental Policyen
idrc.rims.adhocgroupIDRC SUPPORTEDen

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Improving Disease Outbreak Forecasting Models for Efficient Targeting of Public Health Resources
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