Wu Pei-Chih, Guo How-Ran, Lung Shih-Chun, Lin Chuan-Yao, Su Huey-Jen
Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, 138 Sheng-Li Road, Tainan 70428, Taiwan, ROC.
Acta Trop. 2007 Jul;103(1):50-7. doi: 10.1016/j.actatropica.2007.05.014. Epub 2007 May 26.
We evaluated the impacts of weather variability on the occurrence of dengue fever in a major metropolitan city, Kaohsiung, in southern Taiwan using time-series analysis. Autoregressive integrated moving average (ARIMA) models showed that the incidence of dengue fever was negatively associated with monthly temperature deviation (beta=-0.126, p=0.044), and a reverse association was also found with relative humidity (beta=-0.025, p=0.048). Both factors were observed to present their most prominent effects at a time lag of 2 months. Meanwhile, vector density record, a conventional approach often applied as a predictor for outbreak, did not appear to be a good one for diseases occurrence. Weather variability was identified as a meaningful and significant indicator for the increasing occurrence of dengue fever in this study, and it might be feasible to be adopted for predicting the influences of rising average temperature on the occurrence of infectious diseases of such kind at a city level. Further studies should take into account variations of socio-ecological changes and disease transmission patterns to better propose the increasing risk for infectious disease outbreak by applying the conveniently accumulated information of weather variability.
我们采用时间序列分析方法，评估了天气变化对台湾南部主要大都市高雄市登革热发病情况的影响。自回归积分滑动平均（ARIMA）模型显示，登革热发病率与月温度偏差呈负相关（β=-0.126，p=0.044），与相对湿度也呈反向关联（β=-0.025，p=0.048）。观察发现，这两个因素在滞后2个月时呈现出最显著的影响。同时，病媒密度记录这一常用于预测疫情爆发的传统方法，对于疾病发生情况而言似乎并非一个良好的指标。在本研究中，天气变化被确定为登革热发病增加的一个有意义且显著的指标，在城市层面，采用它来预测平均气温上升对这类传染病发生的影响可能是可行的。进一步的研究应考虑社会生态变化和疾病传播模式的变化，以便通过应用方便积累的天气变化信息，更好地提出传染病爆发风险增加的情况。
