JpGU-AGU Joint Meeting 2017

Presentation information

[EJ] Oral

U (Union) » Union

[U-05] [EJ] Innovative research at the intersection of geoscience and health science

Sun. May 21, 2017 10:45 AM - 12:15 PM 101 (International Conference Hall 1F)

convener:Geoffrey S Plumlee(U.S. Geological Survey), Christine McEntee(American Geophysical Union), Fumiko KASUGA(National Institute for Environmental Studies), Chairperson:Christine McEntee(American Geophysical Union), Chairperson:Fumiko Kasuga(National Institute for Environmental Studies)

11:15 AM - 11:30 AM

[U05-02] The Correlation of Urban Climate and Dengue: Metro Manila and Bandung Cases

*Kozo Watanabe1, Thaddeus M. Carvajal1,2, Lia Faridah1,3, Dwi Agustian3, Nurrachman Hidayath3, Fedri Rinawan3, Howell T. Ho2, Divina Amalin2, Chiho Watanabe4 (1.Ehime University, Japan, 2.De La Salle University, Philippines, 3.Padjadjaran University, Indonesia, 4.The University of Tokyo, Japan)

Keywords:Dengue, climate change, epidemiology

Dengue fever is a rapidly emerging mosquito-borne viral disease in tropical and subtropical urban cities. A growing evidence base demonstrates the causal link between climate-driven factors and dengue edpiemiology. A general hypothesis tested by environmental epidemiologists is that urban climate such as temperature and precipitation affect the mosquito vector’s biology and ecology therefore, increasing the risk of dengue transmission. The main objective of this study was to associate the spatial and temporal variations among three eco-edpiemiological elements; namely, local dengue incidence, mosquito abundance, and climate factors using observation data in Metro Manila, Philippines and Bandung, Indonesia. Results of the spatial analysis showed high predictive power of local flood and land use parameters in modeling the spatial variation of dengue incidence. Temporal correlation analysis using time series data demonstrated the lag effects of climate parameters and El Niño-Southern Oscillation index on the increase of dengue cases. The findings can be applied to predict future dengue risk under global climate change, and thus to implement proper adaptation for dengue control.