Annex 19 : predictive model for the dengue incidences in Sri Lanka using mobile network big data

Show simple item record Dharmawardana, K.G.S. Lokuge, K. S. Dassanayake, P. S. B. Sirisena, M. L. Fernando, Lasantha Perera, Amal Shehan Lokanathan, Sriganesh 2019-09-23T08:28:47Z 2019-09-23T08:28:47Z 2018
dc.description.abstract The study constructs a usable predictive model for any given Medical Officer of Health (MOH) division, which is the smallest medical administrative district in Sri Lanka, by taking human mobility into account. It includes the importation of dengue into immunologically ’naive’ regions. Derived mobility values for each region of the country are weighted using reported past dengue cases. The study introduces a generalizable methodology to fuse big data sources with traditional data sources, using machine learning techniques. Mobile Network Big Data (MNBD) consists of data categories such as Call Detail Records (CDR), Internet access usage records, and airtime recharge records. en
dc.format.mimetype application/pdf
dc.language.iso en
dc.subject DENGUE en
dc.subject AEDES AEGYPTI en
dc.subject MOBILE PHONES en
dc.subject MACHINE LEARNING en
dc.subject MOBILE DATA en
dc.subject BIG DATA en
dc.subject EPIDEMIOLOGY en
dc.subject SIMULATION en
dc.subject MODELLING en
dc.subject SRI LANKA en
dc.subject SOUTH ASIA en
dc.title Annex 19 : predictive model for the dengue incidences in Sri Lanka using mobile network big data en
dc.type Working Paper en
idrc.project.number 108008
idrc.project.componentnumber 108008001
idrc.project.title Leveraging Mobile Network Big Data for Developmental Policy en
idrc.copyright.holder © 2018, LIRNEASIA
idrc.copyright.oapermissionsource CC BY 4.0 en
idrc.dspace.access Open Access en
idrc.rims.adhocgroup IDRC SUPPORTED en

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