Dengue Fever (DF) is the most important vector-borne disease in Taiwan. The geographic expansion of dengue fever has become a global public health issue since last decade. Climate change and climate variation in parallel with rapid urbanization are important drivers to trigger dengue epidemics worldwide. However, the impacts of global /local scale climate conditions and environmental changes on dengue transmission in Taiwan have not been analyzed systematically. Dengue fever demonstrated strong seasonal and inter-annual variability in Taiwan but it is noteworthy that both the spatial patterns and the severity of outbreaks have changed after 2006. The aim of this study is to investigate the environmental influences associated with spatial and temporal variations of dengue transmission in Taiwan. Two novel techniques, geographic information systems (GIS) and satellite remote sensing (RS), will be used to generate diverse environmental parameters and export risk maps. Spatial statistics will be integrated to develop dengue forecasting models. There are three goals in this study: (1) Investigate the land use changes and urban expansion in the past 17 years (1998-2014). Analyze the association between land use changes and diffusion pattern of dengue epidemics after 2006. (2) Develop a climatic prediction model which will integrate El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) effects and local climatic conditions derived from satellite remote sensing techniques. (3) Conduct a vector survey to provide empirical mosquito population data for mathematical model which was developed to capture transmission dynamics of dengue epidemics. The influences of multiple environmental parameters, including land use types, urbanization, climatic impacts and vector population dynamics, on dengue transmission will be discussed in depth. The climatic prediction model and the mathematical model will play different role on dengue forecasting. One will set up an early warning sign using climatic variables in early season, the other can provide real-time response and modification by monitoring vector population dynamics in the field. The ultimate goal of this study is to provide core models for establishing dengue early warning system in Taiwan.
|Effective start/end date||8/1/15 → 7/31/16|
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