前言：許多研究皆預測未來全球的表面溫度將會增高，且異常天候事件如颱風、颶風、熱浪等之發生將會增加。氣候變遷會影響各類傳染性疾病流行規模與流行分佈，臺灣的氣候變化極大，又經常面對颱風的侵襲，尤其是夏季，且颱風帶來的暴雨亦可能由於洪水氾濫而攜帶污染之病原污染民生用水系統，進一步造成傳染性疾病之爆發。因此，在臺灣研究異常天候對於傳染性疾病所帶來的衝擊是重要的。
方法：分析1993年至2005年間來自疾病管制局之法定傳染病通報系統及中央氣象局之氣象資料庫，以事件前一星期之疾病個案數為分母、事件後一星期之疾病個案數為分子計算相對危險性來評估颱風與法定傳染疾病之關係。為了避免相互干擾，分別去除相隔小於4及8週之颱風；且分析時考慮各疾病之潛伏期、宿主生活史及延遲效應。
結果：阿米巴性痢疾(延遲時間40天；相對危險性1.83，95%信賴區間1.03-3.26)、猩紅熱(延遲時間17天；相對危險性=1.37，95%信賴區間=1.16-1.60) 、登革熱(延遲時間41天；相對危險性=1.36，95%信賴區間=1.26-1.47)、傷寒(延遲時間9天；相對危險性=1.91，95%信賴區間=1.14-3.20)及腸病毒感染併發重症(延遲時間7天；相對危險性=1.39，95%信賴區間=1.02-1.91)等法定傳染疾病在颱風過後其相對危險性是增加。
結論：本研究結果顯示颱風過後對於特定的法定傳染性疾病之發生風險是會有明顯的增加，如：猩紅熱、阿米巴性痢疾、登革熱、傷寒及腸病毒感染併發重症。此研究結果支持許多在不同地域的研究，證實傳染性疾病與颱風事件之關係。建立預防及控制感染性疾病之策略是相當重要的；未來的研究可進一步以空間時間序列統計方式更進一步探討颱風與疾病之相關。

Objective: Many studies predict that the surface temperature of the Earth will increase, and extreme weather events such as typhoon, hurricane, heat wave, etc. will occur more frequently. Climate changes may affect the scale and distribution of epidemics of infectious diseases. The weather in Taiwan changes a lot from time to time, and typhoons often attack Taiwan, especially in summer. Typhoons usually bring in heavy rainfalls that may cause floods, which may carry pathogens and pollutants into the drinking water system and thus cause outbreaks of infectious diseases. Therefore, it is important to evaluate effects of extreme weather events on infectious diseases in Taiwan.

Method: We analyzed the data from the National Notifiable Disease Surveillance System of the Center for Disease Control and meteorological database from the Central Weather Bureau and estimated the relative risk (RR) associate with typhoons from 1993 to 2005 to evaluate the relationships between the occurrence of infectious diseases and typhoons. We estimated the RR of a given diseases through dividing the numbers of cases observed in a one-week period after the typhoons by the numbers of cases observed one week before the typhoons. To avoid interference between typhoons, we excluded typhoons that were only 4-week and 8-week apart, respectively and took into account some factors including incubation period of every disease, lifecycle of host, and lag effect.

Results: We found significantly increased RRs for amoebic dysentery (lag time: 40 days; RR=1.83; 95% confidence interval [CI] =1.03-3.26), scarlet fever (lag time: 17; RR=1.37; 95%CI=1.16-1.60), dengue fever (lag time: 41; RR=1.36; 95%CI=1.26-1.47), typhoid fever (lag time: 9; RR=1.91; 95%CI=1.14-3.20) and complicated severe enteroviruses infection (lag time: 7; RR=1.39; 95%CI=1.02-1.91).

Conclusion: Our study found that the RRs of some diseases increased after typhoon attacks in Taiwan, such as amoebic dysentery, complicated severe enteroviruses infection, dengue fever, scarlet fever, and typhoid fever. The findings are consistent with those of studies in other countries. Developing the prediction and control strategies for infection disease is important in Taiwan. In the further studies, it should be taken into account different approaches such as time series and spatial analyses.

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