Data Visualization and Analysis for the Epidemic Situation of Dengue Fever in Countries of the World

• Main Authors: Zhen-Sui Yan, 顏振修
• Other Authors: Jenn-Long Liu
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/n5j5av

碩士 === 義守大學 === 資訊管理學系 === 106 === The Tropic of Cancer lies across the middle of Taiwan, giving Taiwan a humid subtropical climate in the north, and a tropical monsoon climate in the south. Therefore, dengue fever is extremely common disease in Taiwan, especially in summer. In recent years, the epidemic is more serious than in the past. It is shocking that there were over 10,000 cases of dengue infection in Taiwan during 2015. Additionally, dengue fever is originally belonged to infectious diseases in tropical and subtropical regions. However, an outbreak of dengue fever occurred in Tokyo, Japan, which located in temperate regions, in 2014. These phenomena have demonstrated that dengue-endemic area on Earth and Infection season change gradually. Nowadays, big data is a hot topic has been discussed by people in various fields. In the era of big data, data visualization can enable people to absorb information quickly and effectively. There are two tools that extremely help people in big data analysis. One is Power BI, and the other is R Language. Power BI is a software application which can quickly make complex static data into dynamic charts and reports and assist people in analyzing data, while R Language is a programming language and free software environment for statistical computing and graphics. In the research, we applied the Power BI and the R Language on the data of cases of dengue infection of over 25 countries from Google Flu Trends and data set of dengue daily determined cases from each country government open data portal to conduct data visualization analysis of cases of dengue infection in each country in order to make it easier for people to understand the dengue infection trends in various countries. Moreover, we applied the a social listening platform, named OpView, to collect dengue-related articles online, then combined the data visualization for the volume of internet posts and data set of dengue daily determined cases from Taiwan government open data portal to analyze the relation between them.