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The defense date of the thesis is 2018-08-28
The current date is 2019-04-24
This thesis will be accessible at 2019-08-28
URN etd-0827118-151023 Statistics This thesis had been viewed 98 times. Download 0 times. Author Yu-Chung Chang Author's Email Address No Public. Department Information Management Year 2017 Semester 2 Degree Master Type of Document Master's Thesis Language zh-TW.Big5 Chinese Page Count 38 Title Implementation of an Information System for Epidemic Alert ─ By Example of Monitoring Dengue Vector Development Keyword dengue open data predictive system geographic information system (GIS) environmental factor environmental factor geographic information system (GIS) predictive system open data dengue Abstract The purpose of this study is to develop an information system to predict spatial/temporal mosquito reproduction and disease outbreaks. Dengue fever has been studied since 200 years ago. There is no effective remedy or vaccine to control it. As a result, it can only be tackled by isolation, control, wiping out and other administrative methods. In order to monitor a region where there is a possibility of recurrence of dengue fever, the construction of a predictive information system would help the authority control disease outbreaks.
The data used in this research are mainly dengue vector density indexes and daily meteorological information between 2010 and 2015 acquired from Taiwan Government Open Data Platform. The spatial/temporal relationships between larval density and dengue outbreaks were analyzed based on these historic data. The results were displayed on geographic information systems to facilitate convenient visualization. Finally, the information was presented on frontend page to support the authority for disease control and decision-making.
This study makes use of climate and geographic information as the basis for the analytic model to forecast possible epidemic outbreaks in the next several days. This approach can be applied to other application areas such as influenza alerts. It could improve the effectiveness of disease prevention and reduce pandemic risk.
Advisor Committee Patrick S. Chen - advisor
Ching-Tsan Tsai - co-chair
Yucheng Kao - co-chair
Files Date of Defense 2018-06-12 Date of Submission 2018-08-28