運用分裂可行解演算方法分析登革熱傳染之熱點-以台南地區為例

Analysis on Dengue Fever Infection Hotspot Using the Split Feasibility Common Fixed Point Algorithm - Tainan Cases as Example

張家銘(Jia-Ming Jhang)

指導教授 ： 洪宗乾

國立屏東科技大學/管理學院/工業管理系所/碩士(2016年)

摘要

近年來病媒蚊相關之傳染病迅速蔓延，使得病媒蚊相關研究逐漸受到重視。每年夏秋兩季台灣登革熱疫情層出不窮，由於登革熱的病毒是經由埃及斑蚊與白線斑蚊進行傳播，鑒於相關登革熱研究是以環境、行為、病媒蚊、噴藥進行探討。本研究將從確診病例資料去探討登革熱的傳染性並建立傳染熱點；文中將以圖像重建的方式，建立台南市中各點登革熱的傳染能力預測模型，並且藉由分群、繪圖等方式探討傳染能力較強的環境狀況。經由數據驗證，本研究所建立的模型能有效鎖定傳染能力較強的區域，經由地圖繪製探討這些區域發現，傳染能力較強的區域主要環境是集中在餐飲商家、菜市場和老舊社區。最後，並且針對這些高傳染能力的地區其噴藥後改善情形進行探討，研究結果顯示目前噴藥對於防疫效果不一定有效，建議防疫單位應該是要研究如何改善這些傳染能力較強的區域環境來抑制登革熱傳染。

關鍵字

分裂可行解演算法 ； 登革熱 ； 登革熱網絡 ； 防疫噴藥

並列摘要

In recent years, related diseases of the vector mosquito, such as dengue fever, have been rapid spread. In Taiwan, dengue fever always breaks out during summers and falls. The number of dengue fever cases in Tainan city is more than 20,000, a historical high, at 2015. Dengue virus is spread by two kinds of mosquitos, Aedes aegypti and Aedes albopictus. Most of the past literatures of dengue fever focus on discussing about environment, behavior and insecticides. This study focuses on identifying the high infecting hotspots. First, we use image reconstruction to calculate the infecting rate for each infected spot in Taiwan for each time periods (ten days as a period from 8/1~12/31, 2015). Then, we show that we can use the high-infecting-rate spot at 8/1~9/10 (period 1) to predict the high-infecting-rate ones at 9/11~12/31 (period 2) with around 70% accuracy. Meanwhile, we also use the change of calculated infecting abilities of each infected spots in those two periods to study the factors that cause the breakout of dengue fever at 2015 in Tainan city. Finally, we study the change of the infecting rate of these insecticide-applied spots. The result shows that insecticide always cannot reduce the infecting ability of hotspots.

並列關鍵字

Split Feasibility Common Fixed Point Algorithm ； Dengue ； Dengue Network ； Prevention spraying

參考文獻

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