2014年高雄登革熱病例時空流行病學分析及探討氣爆之影響

Abstract

隨著現代交通的發達，傳染病在世界各地擴散的速度也與日俱增，登革熱的傳播亦然，加上近年全球氣候異常暖化，無疑地給予病媒蚊良好的繁殖空間。台灣地區的登革熱病例數於2014-2015年攀升不下，2014年高雄市病例數超過萬例，且同年發生一起嚴重的氣爆，因此本研究目的為：(ㄧ) 2014年高雄登革熱疫情的流行病學分析，(二) 探討氣爆對於登革熱疫情的影響，以及(三) 評估病媒蚊列管點( mosquito high-risk sites)的防治成效。 本研究以流行病學法分析2014年1月至12月底期間高雄44位境外移入與1,4999位本土確定登革熱病例（1,4867個登革熱與132個登革出血熱），尤其偏重流行「前期」不同週的境外移入與本土病例彼此間的流行病學相關性(epidemiological linkage)。在探討氣爆對於疫情的影響上，以氣爆發生(第31週)至疫情開始緩降(第45週)的時間點，將2014年高雄市本土登革熱確定病例疫情分為前、中、後三期，分別為第1至30週、第31至45週和第46至53週，並以2008年登革熱確定病例為對照組，以地理資訊系統QGIS探討2014年疫情，並且比較群聚現象與氣爆對於疫情之影響。再將2014劃分出氣爆區域與非氣爆區域之地理位置，利用線性迴歸(linear regression)觀察受氣爆影響的三行政區(前鎮、苓雅和鳳山區)在氣爆前、後的每週病例數與時間的登革熱確定病例斜率是否有差異，並以斯皮爾曼相關係數(Spearman’s Rank Correlation coefficients)觀察登革熱的發生率與人口密度的相關性，及其在氣爆與非氣爆區之前、中、後三期是否有顯著相關。另以高雄市衛生局提供之列管點資料，再使用QGIS探討氣爆區域與非氣爆區域於流行前、中、後三期的變化。 研究結果分三部分，目標(一)：疫情的開始是由前鎮區漁港的兩名工人於第20週發病而引發前鎮區的爆發，接著鄰近其他行政區與該二名工人同工作地的工人相繼發病，疫情於第24週始快速擴散，致在氣爆發生之前，氣爆鄰近區已有病例的群聚。目標(二)：比較2014與2008年高雄登革熱確定病例的流行病學分析和熱區圖(Heatmap)後，發現此兩年: (1)疫情走向相差不大，(2)病例有相似的人口組成，且又有群聚現象，(3)流行中期的病例數顯著地高 (2014前期2.4%、中期68.47%、後期29.13%；2008前期9.2%、中期68.4%、後期22.41%；p <0.0001)，及(4)病例在氣爆區域均呈顯著地高 (2014氣爆影響區 62.05%和其他區37.95%；2008氣爆影響區51.18%和其他區48.82%；p <0.0001)。另在時間分析上，發現受氣爆影響的前鎮、苓雅和鳳山三區的週病例數在「氣爆後」之線性迴歸斜率大於「氣爆前」(未受氣爆影響）之斜率(33.262 vs 12.071)，即氣爆發生後的病例數確實顯著上升，且該迴歸模型有高度的解釋力(R2=0.977, p < 0.01)。而在空間分析上，發現「非氣爆區域」在流行中期與後期的發生率與人口密度有顯著中度正相關(中期 r=0.647, p < 0.01; 後期 r=0.567, p < 0.01)，但「氣爆區域」卻僅在後期的發生率與人口密度卻有顯著中度負相關(後期 r = -0.486, p < 0.05)。目標(三)：在高市衛生局七大病媒蚊列管點中，大多數為積水地下室(n=156, 36.03%)與水溝(n=154, 35.57%)。在氣爆前，病媒蚊列管點仍持續新增，尤其以爆發疫情地最為明顯，但至流行中、後期，疫情大幅成長時，列管點數卻沒隨之增加。 研究結果發現，氣爆發生之前已有疫情持續擴散，然而氣爆可能造成孳生源增加與人口流動，進而擴增其後疫情。本研究提供科學實證以因應未來登革熱防疫的決策，包括：(1) 應加強環境壅擠、人口組成易感染或帶登革病毒的區域(例如漁港區、東南亞外勞較多區)之症狀監測與列管點監測，以避免境外移入病例造成本土病例疫情群聚與擴散；(2)應加強第一型登革病毒的高發地區(即本次受氣爆影響的前鎮、苓雅與鳳山三區居民)之衛生教育，提升民眾對登革熱症狀的自覺性以及清除孳生源的自主性，配合完善的症狀監測系統與臨床醫師通報，避免疫情在流行期間更為嚴重。未來研究重點為：(1) 分析其他影響登革熱傳播的風險因子，以加強登革熱的防治作為；(2)強化病媒監測，以比較歷年來列管點地區與列管項目歷年的變化，提升列管點的監測成效。

The transmission of dengue has increased while modern transportation becomes more convenient. Moreover, mosquitoes have better chances to enlarge their population as global warming occurs. In 2014-2015, dengue cases in Taiwan had strikingly climbed up, particularly Kaohsiung had suffered from occurring more than 10,00 cases after the serious gas explosion. Therefore, the specific aims of this study were: (1) to describe epidemiology of dengue in Kaohsiung, 2014, (2) to assess the impact of gas explosion on dengue cases during this epidemic, and (3) to evaluate the effectiveness of public health efforts in monitoring mosquito high-risk sites. For Aim #1, total laboratory-confirmed dengue cases from Jan. 1 to Dec. 31, 2014, including 44 imported and 1,4999 indigenous dengue cases (1,4867 DF and 132 DHF cases) in Kaohsiung City were analyzed, especially the epidemiological linkage between the imported and indigenous dengue cases at the early stage of the epidemic. For Aim #2, discussing the impact of gas explosion on the epidemic, we divided the 2014 lab -confirmed indigenous dengue cases in Kaohsiung into three stages: (1) the early stage before the gas explosion event [the 31st week (wk)], (2) middle stage (31st – 45th wk), and (3) the late stage when the epidemic begun decreasing (46-53 wk). Using QGIS software to find out the phenomenon of clustering and the impact of gas explosion on the 2014 epidemic, this process was compared with the 2008 epidemic of dengue in the same city (as a control group). Using linear regression analyses for cases, the slopes of weekly case number before and after the gas explosion were compared. In addition, the Spearman's rank correlation coefficients between the incidence of dengue and population density in the gas-explosion areas [the Li (subdistricts) in Qianzhen, Lingya and Fengshan Districts)] versus those in the non-gas-explosion areas in these three districts at the early, middle and late stages of the epidemic were investigated. For Aim #3, data of mosquito-monitoring high-risk sites provided by Kaohsiung Dept of Health were plotted by QGIS in gas-explosion vs non-gas explosion areas at the early, middle and late stages of the 2014 epidemic. The results involved three parts. For Aim #1, the 2014 outbreak started from the two workers in the fish harbor of Qianzhen District and then their colleagues got dengue in other districts. The epidemic spread at the 24th week (wk), with dengue clusters even before the gas explosion at the 31st wk. For Aim #2. the epidemiological characteristics and heatmap results of the dengue cases in 2008 and 2014 were similar in four aspects: (1) trends in epidemic pattern, (2) the demographic composition and dengue clusters, (3) significantly high at the middle epidemic stage (2014: Early 2.4%, Middle 68.47%, Late 29.13%; 2008: Early 9.2%, Middle 68.4%, Late 22.41%; p <0.0001), and (4) significantly greater in gas explosion affected areas (2014: Affected area 62.05%, Others 37.95%; 2008: Affected area 51.18%, Others 48.82%; p <0.0001). In temporal analysis, the slope coefficient at post-gas explosion period in the three districts was higher than pre-gas explosion time (33.262 vs 12.071). The number of dengue cases increased significantly with better interpretation in the model (R2=0.977, p < 0.01). In spatial analysis, the incidence rates of dengue at “the non-gas explosion area” had a significantly moderate positive correlation with the population density in the middle (r=0.647, p < 0.01) and late stages (r=0.567, p < 0.01). On contrast, such incidence rates at the gas explosion area had a moderate negative correlation with population density but a positive correlation only occurred at the last stage (r=-0.486, p < 0.05). For Aim #3, the majority of the seven mosquito-monitoring high-risk sites in Kaohsiung in 2014 were basement accumulated with water (n=156, 36.03%) and mosquito positive ditch (n=154, 35.57%). These mosquito-breeding sites had increased, particularly in the gas-explosion areas even before gas explosion whereas such sites that are necessarily to be managed had not been elevated at the middle and late stages of the epidemic. In conclusion, dengue cases were present and spread even before the occurrence of gas explosion. However, this unexpected event might increase mosquito breeding sites and the population movement, so that the prevention and control measures could not be implemented effectively and thus affecting the 2014 dengue epidemic. This study provided scientific evidences to recommend public health policies of dengue in the future, including: (1) enhancing clinical surveillance and mosquito monitoring in high-risk areas (e.g. fishing port, high foreign labors from SE Asia) to avoid indigenous case clusters initiated by imported cases; (2) strengthening health education on symptoms of dengue in the high-incidence areas as the gas explosion affected areas (i.e. Qianzhen, Lingya and Fengshan Districts) in this epidemic through better clinical surveillance and clinician’s reporting and thus minimizing epidemic severity. The future research directions are: (1) analyzing other risk factors affecting dengue transmission to increase efficiency of prevention and control, and (2) improving mosquito surveillance and comparing the differences in the effectiveness of various types of mosquito high-risk sites.