Prediction of dengue incidence using auto-regression models: case study of Ping-Tung County
碩士 === 崑山科技大學 === 環境工程研究所 === 105 === Monthly time series data of dengue infection cases was collected from 1998 to 2015 in Ping-Tung County. Regression technique applied to predict dengue incidence rate by using weather, social-economic and climate change parameters. Auto-regression (AR) was then...
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| Format: | Others |
| Language: | zh-TW |
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2018
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| Online Access: | http://ndltd.ncl.edu.tw/handle/sp24sc |
| Summary: | 碩士 === 崑山科技大學 === 環境工程研究所 === 105 === Monthly time series data of dengue infection cases was collected from 1998 to 2015 in Ping-Tung County. Regression technique applied to predict dengue incidence rate by using weather, social-economic and climate change parameters. Auto-regression (AR) was then embedded into IR models, and to significantly improve the predictability of dengue for Ping-Tung County. The integration models of AR would be used to assist an efficient dengue control. The predictive power and robustness of predictive models would be improved with additional data over longer time periods. Capturing all aspects of the disease is a daunting task, but newer techniques may help overcome the difficulties. In particular, this study discussed several significant outbreaks in Ping-Tung County with better performance.
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