Dharmawardana, K.G.S.Lokuge, K. S.Dassanayake, P. S. B.Sirisena, M. L.Fernando, LasanthaPerera, Amal ShehanLokanathan, Sriganesh2019-09-232019-09-232018http://hdl.handle.net/10625/58136The 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.application/pdfenDENGUEAEDES AEGYPTIMOBILE PHONESMACHINE LEARNINGMOBILE DATABIG DATAEPIDEMIOLOGYSIMULATIONMODELLINGSRI LANKASOUTH ASIAWorking Paper