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

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56970.pdf (1.28 MB)

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2018-03

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Abstract

The 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.

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DENGUE, NEGLECTED TROPICAL DISEASES, DISEASE OUTBREAK FORECASTING, DISEASE SURVEILLANCE, RESOURCE ALLOCATION, MOBILE PHONE NETWORKS, BIG DATA, SRI LANKA, DISEASE VECTORS, TROPICAL DISEASES, MOBILE NETWORKS, MACHINE LEARNING, DATA COLLECTION METHODOLOGY, SOUTH ASIA

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http://hdl.handle.net/10625/56923

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2010-2019 / Années 2010-2019
Data / Données
IDRC Research Results / Résultats de recherches du CRDI
Research Results (INASSA) / Résultats de recherche (IRAAS)
Research Results (Networked Economies) / Résultats de recherche (Économies en réseaux)