本研究旨在探討淹水事件對於高雄、台南地區登革熱疫情的影響。蒐集台南市、高雄市、花蓮縣、台東縣2015年至2019年間，逐月的行政區劃資料為樣本。迴歸估計式中使用到的變量有月均溫、布氏級數、遲滯兩期之降雨量、各區域人口密度及本土登革熱病例數。同時找出高雄市與台南市各年度淹水事件發生時間點及該淹水地點之行政區劃，將其作為實驗組並指定花蓮縣、台東縣為控制組。迴歸樣本期間則篩選當次淹水事件發生的前後六個月，共計一年。依次操作差異中之差異法（Difference in difference, DID），來看當次淹水事件對於該實驗組地區的登革熱病例數如何影響及其影響程度大小。而後依據實驗組與對照組與否做邏輯斯迴歸，將得到的邏輯斯機率值用於傾向分數配對法(Propensity Score Matching, PSM)，讓實驗組與對照組的解釋變量分布狀況接近，再操作差異中之差異法估算淹水對於登革熱病例數的影響。
估算結果顯示2015年8月蘇迪勒颱風台南、高雄部分地區淹水，會導致登革熱病例數顯著增加。遲滯兩期之降雨量、氣溫和人口密度愈高對於病例數有顯著正影響，降雨使地區戶外積水容器變多，成為病媒蚊幼蟲的溫床，將提高該地區感染登革熱的病例數。氣溫愈高將使病媒蚊的孳生與傳染速度變快，且人口密度愈高也會提升登革熱的傳染速度，因居民得到登革熱後將成為病毒帶原者，一般家蚊也會經由吸取病毒帶原者血液後成為病媒蚊，故人口密集地區將更易使登革熱疫情傳播；而經過PSM配對後2015年8月的淹水事件DID結果也呈現顯著。2016年高雄三民區本安滯洪池落成，經過DID估計對於該地區的登革熱病例為顯著負相關。即滯洪池調節地區洪水功能有效降低病媒蚊孳生與疾病傳播的途徑。

The purpose of this study was to investigate the impact of flooding on the prevalence of indigenous dengue fever in Taiwan. Our monthly administrative division data is from 2015 to 2019, including Tainan, Kaohsiung, Hualien, and Taitung. The independent variables include average temperature, Breteau Index, average precipitation, and population density.
The treatment group comprised the recorded dates and districts of every flood in Tainan and Kaohsiung, and the control group comprised all the districts in Hualien and Taitung. The sample period covered a total of one year, which was six-month before and six-month after each flood event.
An investigation was conducted to determine how flooding impacts the cases of indigenous dengue fever using a difference-in-difference method. Next, a logistic regression was performed to compare the treatment group and the control group. Then, the propensity score obtained from the logistic regression was used for propensity score matching. Afterwards, the distribution of the independent variables between the treatment group and control group were close, so a difference-in-difference method was used to estimate the impact of flooding again.
The empirical analysis found the following: (1) Temperature, population density and precipitation with two months lag were the factors affecting indigenous dengue fever cases in Tainan and Kaohsiung after Typhoon Soudelor in August 2015. High temperatures lead to the breeding of mosquito vectors and faster spread of the disease. Population density in these cities also contributed to the spread of the virus. (2) The Benan Retarding Basin likely eliminated mosquito vector-breeding ground and reduced the spread of dengue fever. To summarize, extreme rainfall caused by Typhoons have significant impacts on the number of dengue fever cases in Taiwan.

中文文獻
Petcharat, R. （2014）。 氣候變遷對傳染病的潛在影響: 登革熱在泰國為例。中興大學應用經濟學系所學位論文，頁 1-45。
王鴻龍、楊孟麗、陳俊如、林定香 （2012）。 缺失資料在因素分析上的處理方法之研究。教育科學研究期刊。
亞拉妮（2013）。降雨對於登革熱發病率的潛在衝擊: 印尼與台灣的案例研究。

英文文獻
Abadie, A., & Gardeazabal, J. (2003). The economic costs of conflict: A case study of the Basque Country. American economic review, 93(1), 113-132.
Aström, C., Rocklöv, J., Hales, S., Béguin, A., Louis, V., & Sauerborn, R. (2012). Potential distribution of dengue fever under scenarios of climate change and economic development. Ecohealth, 9(4), 448-454. doi:10.1007/s10393-012-0808-0
Brady, O. J., Smith, D. L., Scott, T. W., & Hay, S. I. (2015). Dengue disease outbreak definitions are implicitly variable. Epidemics, 11, 92-102.
Breen, P., Mag, V., & Seymour, B. (1994). The combination of a flood-retarding basin and a wetland to manage the impact of urban runoff. Water Science and Technology, 29(4), 103-109.
Chen, M.-J., Lin, C.-Y., Wu, Y.-T., Wu, P.-C., Lung, S.-C., & Su, H.-J. (2012). Effects of extreme precipitation to the distribution of infectious diseases in Taiwan, 1994–2008. PloS one, 7(6), e34651.
Cheong, Y. L., Burkart, K., Leitão, P. J., & Lakes, T. (2013). Assessing weather effects on dengue disease in Malaysia. International journal of environmental research and public health, 10(12), 6319-6334.
Chien, L.-C., & Yu, H.-L. (2014). Impact of meteorological factors on the spatiotemporal patterns of dengue fever incidence. Environment international, 73, 46-56.
Gubler, D. J. (1998). Dengue and dengue hemorrhagic fever. Clinical microbiology reviews, 11(3), 480-496.
Guha-Sapir, D., & Schimmer, B. (2005). Dengue fever: new paradigms for a changing epidemiology. Emerging themes in epidemiology, 2(1), 1-10.
Hashizume, M., Dewan, A. M., Sunahara, T., Rahman, M. Z., & Yamamoto, T. (2012). Hydroclimatological variability and dengue transmission in Dhaka, Bangladesh: a time-series study. BMC infectious diseases, 12(1), 1-9.
Hii, Y. L., Zhu, H., Ng, N., Ng, L. C., & Rocklöv, J. (2012). Forecast of dengue incidence using temperature and rainfall. PLoS Negl Trop Dis, 6(11), e1908.
Hsu, J. C., Hsieh, C.-L., & Lu, C. Y. (2017). Trend and geographic analysis of the prevalence of dengue in Taiwan, 2010–2015. International Journal of Infectious Diseases, 54, 43-49.
Ivers, L. C., & Ryan, E. T. (2006). Infectious diseases of severe weather-related and flood-related natural disasters. Current opinion in infectious diseases, 19(5), 408-414.
Karim, M. N., Munshi, S. U., Anwar, N., & Alam, M. S. (2012). Climatic factors influencing dengue cases in Dhaka city: a model for dengue prediction. The Indian journal of medical research, 136(1), 32.
Kyle, J. L., & Harris, E. (2008). Global spread and persistence of dengue. Annu. Rev. Microbiol., 62, 71-92.
Lin, C.-H., Schiøler, K. L., Jepsen, M. R., Ho, C.-K., Li, S.-H., & Konradsen, F. (2012). Dengue outbreaks in high-income area, Kaohsiung City, Taiwan, 2003–2009. Emerging infectious diseases, 18(10), 1603.
Moore, R., & Jones, D. (1998). Linking hydrological and hydrodynamic forecast models and their data. Paper presented at the Proceedings of the first RIBAMOD workshop:“River Basin Modeling, management and flood mitigation.
Plate, E. J. (2002). Flood risk and flood management. Journal of Hydrology, 267(1-2), 2-11.
Reiter, P. (2001). Climate change and mosquito-borne disease. Environmental health perspectives, 109(suppl 1), 141-161.
Reiter, P., Lathrop, S., Bunning, M., Biggerstaff, B., Singer, D., Tiwari, T., . . . Hayes, J. (2003). Texas lifestyle limits transmission of dengue virus. Emerging infectious diseases, 9(1), 86.
Sanna, M., & Hsieh, Y.-H. (2017). Temporal patterns of dengue epidemics: The case of recent outbreaks in Kaohsiung. Asian Pacific journal of tropical medicine, 10(3), 292-298.
Tseng, W.-C., Chen, C.-C., Chang, C.-C., & Chu, Y.-H. (2009). Estimating the economic impacts of climate change on infectious diseases: a case study on dengue fever in Taiwan. Climatic Change, 92(1), 123-140.
Wang, S.-F., Chang, K., Lu, R.-W., Wang, W.-H., Chen, Y.-H., Chen, M., . . . Chen, Y.-M. A. (2015). Large Dengue virus type 1 outbreak in Taiwan. Emerging microbes & infections, 4(1), 1-3.
Wang, S.-F., Wang, W.-H., Chang, K., Chen, Y.-H., Tseng, S.-P., Yen, C.-H., . . . Chen, Y.-M. A. (2016). Severe dengue fever outbreak in Taiwan. The American journal of tropical medicine and hygiene, 94(1), 193-197.
Wang, T.-L., & Chang, H. (2002). Do the Floods Have the Impacts on Vector-Born Diseases in Taiwan? Ann. Disaster Med Vol, 1(1).
Wang, Z.-Y., & Plate, E. (2002). Recent flood disasters in China. Paper presented at the Proceedings of the Institution of Civil Engineers-Water and Maritime Engineering.
Waterman, S. H., & Gubler, D. J. (1989). Dengue fever. Clinics in dermatology, 7(1), 117-122.
Watts, D. M., Burke, D. S., Harrison, B. A., Whitmire, R. E., & Nisalak, A. (1987). Effect of temperature on the vector efficiency of Aedes aegypti for dengue 2 virus. The American journal of tropical medicine and hygiene, 36(1), 143-152.
Whitcomb, J. C., & Morris, H. M. (1961). The genesis flood. SPONS AGENCY PUB DATE, 60, 60.