Mathematical Modeling and Computational Issues of Dengue Epidemic
碩士 === 國立成功大學 === 數學系應用數學碩博士班 === 106 === Tainan experienced severe dengue epidemics in 2015. According to the open data, some interesting issues are found. We use Susceptible - Exposed - Infected - Recovered (SEIR) model and adjust the parameters in the effective contact rate to fit historical data...
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ndltd-TW-106NCKU55070062019-05-16T01:07:58Z http://ndltd.ncl.edu.tw/handle/k6ayjz Mathematical Modeling and Computational Issues of Dengue Epidemic 登革熱疫情的數學建模及計算 Yu-HsunLee 李昱勳 碩士 國立成功大學 數學系應用數學碩博士班 106 Tainan experienced severe dengue epidemics in 2015. According to the open data, some interesting issues are found. We use Susceptible - Exposed - Infected - Recovered (SEIR) model and adjust the parameters in the effective contact rate to fit historical data. By comparing the trend of the optimized effective contact rate and the dates of the epidemic prevention works by the government, the decay after prevention works gives a positive evidence for those works of government. We also compare the severity of each districts, and the relationship between the trend of epidemics and the chemical prevention is found. In the future, we will integrate the multi-scale method with different information, such as geographic map, social information, and climate to establish a multi-scale heterogeneous epidemic model and discuss its computational efficiency and related error analysis. Yu-Chen Shu 舒宇宸 2018 學位論文 ; thesis 20 en_US |
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碩士 === 國立成功大學 === 數學系應用數學碩博士班 === 106 === Tainan experienced severe dengue epidemics in 2015. According to the open data, some interesting issues are found. We use Susceptible - Exposed - Infected - Recovered (SEIR) model and adjust the parameters in the effective contact rate to fit historical data. By comparing the trend of the optimized effective contact rate and the dates of the epidemic prevention works by the government, the decay after prevention works gives a positive evidence for those works of government. We also compare the severity of each districts, and the relationship between the trend of epidemics and the chemical prevention is found.
In the future, we will integrate the multi-scale method with different information, such as geographic map, social information, and climate to establish a multi-scale heterogeneous epidemic model and discuss its computational efficiency and related error analysis.
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Yu-Chen Shu |
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Yu-Chen Shu Yu-HsunLee 李昱勳 |
author |
Yu-HsunLee 李昱勳 |
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Yu-HsunLee 李昱勳 Mathematical Modeling and Computational Issues of Dengue Epidemic |
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Yu-HsunLee |
title |
Mathematical Modeling and Computational Issues of Dengue Epidemic |
title_short |
Mathematical Modeling and Computational Issues of Dengue Epidemic |
title_full |
Mathematical Modeling and Computational Issues of Dengue Epidemic |
title_fullStr |
Mathematical Modeling and Computational Issues of Dengue Epidemic |
title_full_unstemmed |
Mathematical Modeling and Computational Issues of Dengue Epidemic |
title_sort |
mathematical modeling and computational issues of dengue epidemic |
publishDate |
2018 |
url |
http://ndltd.ncl.edu.tw/handle/k6ayjz |
work_keys_str_mv |
AT yuhsunlee mathematicalmodelingandcomputationalissuesofdengueepidemic AT lǐyùxūn mathematicalmodelingandcomputationalissuesofdengueepidemic AT yuhsunlee dēnggérèyìqíngdeshùxuéjiànmójíjìsuàn AT lǐyùxūn dēnggérèyìqíngdeshùxuéjiànmójíjìsuàn |
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