應用季長期天氣預報推估高雄地區登革熱流行趨勢;Applying Seasonal Climate Outlooks for Estimating the Epidemic Trend of Dengue Fever in Kaohsiung Areas

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题名:	應用季長期天氣預報推估高雄地區登革熱流行趨勢;Applying Seasonal Climate Outlooks for Estimating the Epidemic Trend of Dengue Fever in Kaohsiung Areas
作者:	徐葦茵;Hsu,Wei-yin
贡献者:	水文與海洋科學研究所
关键词:	季長期預報;時間序列;登革熱;高雄地區;Dengue fever;Kaohsiung;Time series;Seasonal climate outlooks
日期:	2012-07-25
上传时间:	2012-09-11 18:26:07 (UTC+8)
出版者:	國立中央大學
摘要:	近年來登革熱一直為全球熱帶地區、亞熱帶地區相當嚴重的病媒蚊傳染性疾病，至1980年為止，全球亞熱帶地區，有活動性登革熱病毒傳播的國家多達61國，所涵蓋總人口數約有15億之多。台灣地處亞熱帶，高溫多雨，是病媒蚊傳染疾病的繁殖溫床，近年來由於氣候異常，若高溫多雨將促使登革熱病毒及病媒活化，進而導致登革熱疫情之擴大。台灣地區近十年來的登革熱病例流行，以2002年高雄地區為最主要的病例大爆發年，主因為2001年登革熱病例持續發生且跨年而導致該年的大流行，其中出血性登革熱病例高達240例，死亡率更高達8.75%。因此，預先研判登革熱在未來的可能發展趨勢為一重要的防疫課題。本研究利用中央氣象局發布之季長期預報資料結合週期性流行指數，利用ARIMA(Autoregressive Integrated Moving Average，自迴歸移動平均)時間序列模式預測登革熱病例在高雄地區的流行趨勢。結果顯示利用此模式所預測之登革熱病例數與歷史事件比較，所建立模式能掌握登革熱病例發展趨勢，因此可利用此模式結合未來之預報資料預測可能之病例發展趨勢。Dengue fever is the most serious infectious disease transmitted by mosquitoes in tropical and subtropical areas. Transmissions of dengue fever virus were observed in 61 countries accounting for more than 1.5 billion people in the risk of infection. Owing to humid climate and warm temperature, Taiwan is a great hotbed of mosquito activities promoting infectious diseases. Extreme climate in recent years further promotes the activation of dengue viruses and causes a significant trend of increasing dengue fever cases. The main outbreak of 2002 in Kaohsiung areas was the most extreme case of dengue fever epidemic in Taiwan over the past decade. It was recognized as a propagation of epidemics in 2001 and became a great outbreak. Among cases diagnosed in 2002, dengue hemorrhagic fever was up to 240 cases and the mortality rate was up to 8.75%. Therefore, projection of the epidemic trend of dengue fever is an important epidemic prevention topic in Taiwan. In this study, we applied seasonal climate outlooks issued by the Central Weather Bureau with the monthly population index averaged from historical dengue fever cases past events for the ARIMA modeling for estimating the epidemic trend of dengue fever in Kaohsiung areas. The result showed that the regression model proposed in this study has prediction skills and can be applied for projecting epidemic trend in Kaohsiung areas.
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