本文應用c管制圖及地理資訊系統觀察歷年腸病毒併發重症之疫情趨勢。本文利用歷年中腸病毒重症疫情較穩定之年份，來尋找合適的c管制圖中央線及控制上下線，並運用控制上限來瞭解疫情不穩定的年份，以利觀察疫情是否處於控制狀態內或控制狀態外。最後，本文運用2008年資料做為疫情監控之驗証，若疫情超出控制上限時，則進一步透過地理資訊系統的繪圖功能輔助，可立即觀察出疫情於不同地區上之感染。本文之研究結果顯示，在歷年不穩定年份下之監控結果，可發現有兩波腸病毒流行期，第一波約在4月初至8月底；第二波約在9月初至11月底。在2008年的監測結果下，雖疫情於8月份有下降遞減的趨勢，但因9月初可能會有另一波的流行發生，故仍需持續監控中。而在各縣市疫情感染的情況下，不論在觀察第16週或第0週至第16週之地區疫情分布累積密度來看，亦可發現2008年第一波流行期間，疫情大多集中於中南部地區。因此，本文之研究結果可提供衛生主管機關擬定疫情監控政策之參考，且能有效幫助預測及監控疫情發展之趨勢。

This study examined epidemic episodes based on data acquired from severe complicated enterovirus cases over several years by adopting the use of the c control chart and geographic information system. Data from episodes involving severe complicated enteroviruses over several years was adopted to identify the proper central line and control limit of a c control chart. The upper control limit was then utilized to understand unstable epidemic episodes over the years in order to determine whether the epidemic episode was stable or not in terms of adequate control. Next, data from 2008 on epidemic episodes was analyzed when the epidemic episode exceeded the upper control limit, as achieved through the drawing function of a geographical information system. Doing so allowed us to determine immediately the infection level of an epidemic episode in various regions. Monitoring results from data based on unstable years indicate the prevalence of two waves of severe complicated enterovirus episodes, with the first wave lasting from the start of April to the end of August and the second wave lasting from the start of September to the end of November. According to monitoring results of 2008, although decreasing in August, epidemic episodes may undergo another wave in September, necessitating continuous monitoring of the situation. As for infection levels of epidemic episodes in cities, regardless of whether during the 16th week or 0 week to 16th week, in terms of density distribution, the first term was found to be prevalent in 2008. During this period, epidemic episodes concentrate mainly in the central and southern parts of Taiwan. In addition to providing governmental officials with a valuable reference for monitoring epidemic episodes, this study contributes to efforts to accurately predict and monitor epidemic episodes in the future.