Reconstruction of dengue fever transmission network in Singapore
Dengue fever is a serious public health concern which is endemic in many parts of the world. The lack of a specific cure or treatment makes it more worrying because if not treated, dengue fever can potentially lead to death. To gain better understanding of the dengue transmission network in...
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sg-ntu-dr.10356-750242023-07-07T16:45:05Z Reconstruction of dengue fever transmission network in Singapore Tan, Wen Jian Xiao Gaoxi School of Electrical and Electronic Engineering A*STAR Institute of High Performance Computing DRNTU::Engineering Dengue fever is a serious public health concern which is endemic in many parts of the world. The lack of a specific cure or treatment makes it more worrying because if not treated, dengue fever can potentially lead to death. To gain better understanding of the dengue transmission network in Singapore, 2 correlation models were generated. The models aim to establish associations between population density, dengue incidence and occurrence of hotspots. Subsequently, detailed spatial and temporal analysis on specific parts of Singapore were carried out to check for spreading patterns that may model theoretical network models. Findings revealed that dengue clusters tend to appear more frequently in areas that has a higher population density. It was also observed that with more clusters appearing in the whole of Singapore, there was a greater number of incidence where dengue fever was diagnosed across the country. Through spatial and temporal analysis, it was observed that on an isolated scale, the dengue transmission network exhibited the characteristics of a scale-free network, although not mathematically justified. To better understand the spreading network of dengue, factors such as climate, human interactions and transportation must be considered. Bachelor of Engineering 2018-05-27T11:45:08Z 2018-05-27T11:45:08Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75024 en Nanyang Technological University 67 p. application/pdf |
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DRNTU::Engineering Tan, Wen Jian Reconstruction of dengue fever transmission network in Singapore |
description |
Dengue fever is a serious public health concern which is endemic in many parts of the world. The
lack of a specific cure or treatment makes it more worrying because if not treated, dengue fever
can potentially lead to death.
To gain better understanding of the dengue transmission network in Singapore, 2 correlation
models were generated. The models aim to establish associations between population density,
dengue incidence and occurrence of hotspots. Subsequently, detailed spatial and temporal
analysis on specific parts of Singapore were carried out to check for spreading patterns that may
model theoretical network models.
Findings revealed that dengue clusters tend to appear more frequently in areas that has a higher
population density. It was also observed that with more clusters appearing in the whole of
Singapore, there was a greater number of incidence where dengue fever was diagnosed across
the country. Through spatial and temporal analysis, it was observed that on an isolated scale, the
dengue transmission network exhibited the characteristics of a scale-free network, although not
mathematically justified.
To better understand the spreading network of dengue, factors such as climate, human
interactions and transportation must be considered. |
author2 |
Xiao Gaoxi |
author_facet |
Xiao Gaoxi Tan, Wen Jian |
format |
Final Year Project |
author |
Tan, Wen Jian |
author_sort |
Tan, Wen Jian |
title |
Reconstruction of dengue fever transmission network in Singapore |
title_short |
Reconstruction of dengue fever transmission network in Singapore |
title_full |
Reconstruction of dengue fever transmission network in Singapore |
title_fullStr |
Reconstruction of dengue fever transmission network in Singapore |
title_full_unstemmed |
Reconstruction of dengue fever transmission network in Singapore |
title_sort |
reconstruction of dengue fever transmission network in singapore |
publishDate |
2018 |
url |
http://hdl.handle.net/10356/75024 |
_version_ |
1772827045117558784 |