Wongkoon S, Jaroensutasinee M, Jaroensutasinee K
Centre of Excellence for Ecoinformatics, School of Science, Walailak University, 222 Thaiburi, Thasala, Nakhon Si Thammarat 80161, Thailand.
Trop Biomed. 2013 Dec;30(4):631-41.
This study explored the impact of weather variability on the transmission of dengue fever in Nakhon Si Thammarat, Thailand. Data on monthly-notified cases of dengue fever, over the period of January 1981 - June 2012 were collected from the Bureau of Epidemiology, Department of Disease Control, Ministry of Public Health. Weather data over the same period were obtained from the Thai Meteorological Department. Spearman correlation analysis and time-series adjusted Poisson regression analysis were performed to quantify the relationship between weather and the number of dengue cases. The results showed that maximum and minimum temperatures at a lag of zero months, the amount of rainfall, and relative humidity at a lag of two months were significant predictors of dengue incidence in Nakhon Si Thammarat. The time series Poisson regression model demonstrated goodness-of-fit with a correlation between observed and predicted number of dengue incidence rate of 91.82%. This model could be used to optimise dengue prevention by predicting trends in dengue incidence. Accurate predictions, for even a few months, provide an invaluable opportunity to mount a vector control intervention or to prepare for hospital demand in the community.
本研究探讨了天气变化对泰国那空是贪玛叻府登革热传播的影响。1981年1月至2012年6月期间每月通报的登革热病例数据，是从公共卫生部疾病控制司流行病学局收集的。同期的天气数据来自泰国气象部门。进行了Spearman相关性分析和时间序列调整泊松回归分析，以量化天气与登革热病例数之间的关系。结果表明，滞后零个月的最高和最低温度、降雨量以及滞后两个月的相对湿度，是那空是贪玛叻府登革热发病率的显著预测因素。时间序列泊松回归模型显示拟合良好，观察到的和预测的登革热发病率之间的相关性为91.82%。该模型可用于通过预测登革热发病率趋势来优化登革热预防。即使提前几个月进行准确预测，也能提供一个实施病媒控制干预或为社区医院需求做准备的宝贵机会。
