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Environmental Science & Technology 2018 Journal of Environmental Research
Page 21
March 29-31, 2018
Vienna, Austria
4th Edition of International Conference on
Environmental Science
& Technology 2018
T he number of dengue fever patients has increased in Taiwan
in recent years, and measures are urgently needed to prevent
dengue fever outbreaks.Themechanismsunderlying theoutbreaks
must be clarified in order to develop a predictive model and take
appropriate precautions. Unfortunately, these mechanisms are
complex, and the factors involved in the generation, propagation,
and spread of dengue fever have yet to be fully elucidated.
However, the outbreaks are known to be influenced by the interplay
of factors that include rising temperatures, including rising sea
surface temperatures (SSTs); increasing rainfall due to global
warming; and rapid urbanization. These factors contribute to
inadequate water and sewage treatment systems. Subsequently,
water storage containers, as well as discarded automobile tires
and other containers that fill with rainfall, allow mosquito breeding
and vector dispersion. In addition, rising temperatures, rapid
urbanization lead to human displacement and travel, contribute to
the spread of dengue virus-infected mosquitoes. Here I present
a conceptual framework that helps clarify how these factors
contribute to dengue fever outbreaks in Taiwan. This framework
uses satellite remote sensing data and deep learning, which is
a machine learning technique, as well as our current, ongoing
research findings.
Recent Publications
1. Sumiko Anno (2016) Gene–environment interaction
analysis: methods in bioinformatics and computational
biology, Pan Stanford Publishing Pte. Ltd., ISBN
9789814669634.
2. Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu
Igarashi,SubramaniamSivaganesh,SelvamKannathasan,
Vaithehi Kumaran, Sinnathamby Noble Surendran (2015)
Space–time clustering characteristics of dengue based
on ecological, socio-economic, and demographic factors
in northern Sri Lanka, Geospatial Health, 10(376):215-
222,.
3. Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu
Igarashi, Subramaniam Sivaganesh, Selvam
Kannathasan, Vaithehi Kumaran, Sinnathamby Noble
Surendran (2014) Assessing the temporal and spatial
dynamics of the dengue epidemic in Northern Sri Lanka
using remote sensing data, GIS and statistical analysis.
Journal of Geophysics & Remote Sensing 3(4):1-5.
4. Sumiko Anno, Kazuhiko Ohshima, Takashi Abe, Takeo
Tadono, Aya Yamamoto, Tamotsu Igarashi (2013)
Approaches to Detecting Gene-Environment Interactions
in Human Variation Using Genetic Engineering,
Remote Sensing and GIS. Journal of Earth Science and
Engineering 3(6):371-378.
5. Sumiko Anno, Kazuhiko Ohshima, andTakashi Abe (2010)
Approaches to understanding adaptations of skin color
variation by detecting gene-environment interactions.
Expert Review of Molecular Diagnostics 10(8):987-991.
Biography
Sumiko Anno is an Associate Professor of Shibaura Institute of Technology. Her
research is interdisciplinary, ranging fromMolecular Biology to the Earth Scienc-
es, and uses Genetic Engineering, Remote Sensing, and Geographic Information
System Technologies. She has received three research achievement awards in
Japan and in other countries, including an award for the work that was pub-
lished in 2016 as “Gene-Environment Interaction Analysis: Methods in Bioinfor-
matics and Computational Biology” She is currently interested in exploring the
application of artificial intelligence to public health issues.
Deep learning applications for predicting dengue fever
outbreak
Sumiko Anno1, Takeshi Hara2, Hiroki Kai3, Yi Chang 4, Ming-An Lee5, Kei Oyoshi6,
Yosei Mizukami6 and Takeo Tadono6
1Shibaura Institute of Technology, Japan
2Gifu University, Japan
3Remote Sensing Technology Center of Japan, Japan
4National Cheng Kung University, Taiwan
5National Taiwan Ocean University, Taiwan
6Japan Aerospace Exploration Agency, Japan
Sumiko Anno et al., J Environ Res, Volume 2