全球氣候變異可能導致極端降雨發生的機率增加，其可能間接造成腹瀉相關疾病風險隨之提高，甚而造成其流行區域分布的改變。因此本研究希望可以針對臺灣地區降雨情形對於腹瀉相關疾病之影響的相關研究，在不同人口特性以不同病原體上等面向以進行詳盡的探討及研究。
研究之氣象資料選取自中央氣象局 33 個固定氣象測站的監測資料，與全台約 372 個雨量自動測站資料；病例資料則採用可取得之行政區 (鄉鎮區)建立每日通報案例數與症狀通報統計資料。而研究方法的部份則依照疾病資料本身特性採用病例交叉研究設計進行與降雨變化的相關資料分析。在研究模型上則應用Cox proportional hazard model進行條件式羅吉斯回歸分析。
研究結果顯示以四類腹瀉相關疾病而言，腸病毒併發重症其病例發生主要集中於五歲以下之幼童族群，桿菌性痢疾則無特定分布之情形。此外，諾羅病毒以及輪狀病毒則主要分布於六歲以上之族群。而就影響程度而言，可以發現在腸病毒併發重症的部份在全人口以及五歲以下之族群呈現一正相關之結果，其影響程度為2%至2.5%；而桿菌性痢疾則均呈現出一致之正相關趨勢，其影響程度為0.1%至4%，然而在諾羅病毒以及輪狀病毒上，則是出現了負相關，其影響程度分別為1% - 12%以及4% - 31%。而本研究同時以降雨雨量百分比以探討對於四類疾病之衝擊，由分析結果可知，在腸病毒併發重症的部份可發現在Lag7至Lag9時當降雨雨量相較於未降雨時，若降雨雨量達到95th至99th（31.658 – 93.032 mm）時有最大之爆發風險之衝擊；在桿菌性痢疾的部份則可發現在Lag5至Lag6時當降雨雨量相較於未降雨，若其降雨雨量大於95th（31.658 mm）時有最大爆發風險之衝擊；而在諾羅病毒以及輪狀病毒的部份則發現分別在Lag3至Lag4以及Lag3至Lag5時當降雨雨量相較於未降雨，若降雨雨量達到25th至75th (0.044 相較於未降雨，)以及25th至50th (0.044 相較於未降雨，)時有最大爆發風險之衝擊。
本研究在病例對照研究設計下之分析結果顯示，降雨雨量影響四類腹瀉相關疾病主要集中於潛伏期後兩天，且同時腸病毒併發重症以及桿菌性痢疾會受到較大之降雨雨量之影響而增加其爆發之風險。而諾羅病毒以及輪狀病毒則會受到較小之降雨雨量而有所衝擊其爆發風險，顯示未來應針對不同降雨狀況下對於不同腹瀉疾病進行相關防治工作。

Global climate change increases the variation of extreme precipitation which has presented indirect damage as the consequences of changing risk area and diarrhea distribution pattern. This study is aimed for investigating the relationship between extreme precipitation and diarrhea-related diseases in Taiwan from 1998 to 2008.
Meteorological data was acquired from the 33 meteorological stations of Central Weather Bureau and 372 automatic precipitation observation stations of Central Weather Bureau. The recorded registries of the diseases occurrence and outbreak were acquired from Taiwan Centers for Disease Control, Symptom Surveillance Report Data and Mandatory Communicable Disease report database. In addition, case-crossover study design and Conditional logistic regression were utilized to assess the associations of extreme precipitation and diarrhea-related diseases.
The results demonstrated the enterovirus in either all population or the group under 5 years old displayed the positive relationship, and the levels of impact is 2% to 2.5%; the shigellosis displayed similar positive relationship in total population, the levels ranged from 0.1% to 4%; the norovirus and rotavirus both showed the negative relationship, the level of impact were 1% to 12% and 4% to 31%, respectively. Furthermore, we used the percentile of precipitation to probe into the impacts of four diarrhea-related diseases. The enterovirus had the highest outbreak risk when the precipitation achieved 95th to 99th (31.658 – 93.032 mm) in 7 to 9 days prior using “no precipitation” as the reference group. As the precipitation went beyond 95th (31.658 mm) in 5 to 6 days prior, the shigellosis had the largest impact of outbreak risk; when the precipitation achieved 25th to 75th (0.044 – 4.805 mm) in 3 to 4 days prior and 25th to 50th (0.044 – 0.763 mm) in 3 to 5 days prior separately, the norovirus and rotavirus will have the largest outbreak impacts individually.
The analyses showed the lag time of precipitation on diarrhea-related diseases mainly concentrated in two days after incubation. Outbreak risks of enterovirus and shigellosis will be increased by stronger precipitation whereas the associations for norovirus and rotavirus will be attenuated with the increase of precipitation. It suggested that different disease prevention works should be implemented given the type of diarrhea-related diseases that public health sectors tackle.

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