Bekoe Collins, Pansombut Tatdow, Riyapan Pakwan, Kakchapati Sampurna, Phon-On Aniruth
Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani campus, Pattani, Thailand.
J Res Health Sci. 2017 May 4;17(2):e00378.
Dengue fever is one of the infectious diseases that is still a public health problem in Thailand. This study considers in detail, the geographic consequence, seasonal and pattern of dengue fever transmission among the 76 provinces of Thailand from 2003 to 2015.
A cross-sectional study.
The data for the study was from the Department of Disease Control under the Bureau of Epidemiology, Thailand. The quarterly effects and location on the transmission of dengue was modeled using an alternative additive log-linear model.
The model fitted well as illustrated by the residual plots and the Again, the model showed that dengue fever is high in the second quarter of every year from May to August. There was an evidence of an increase in the trend of dengue annually from 2003 to 2015.
There was a difference in the distribution of dengue fever within and between provinces. The areas of high risks were the central and southern regions of Thailand. The log-linear model provided a simple medium of modeling dengue fever transmission. The results are very important in the geographic distribution of dengue fever patterns.
登革热是泰国仍然存在的公共卫生问题之一的传染病。本研究详细考察了2003年至2015年泰国76个省份登革热传播的地理影响、季节性和模式。
横断面研究。
研究数据来自泰国流行病学局疾病控制司。使用替代加法对数线性模型对登革热传播的季度效应和地点进行建模。
如残差图所示，模型拟合良好。此外，模型显示每年5月至8月的第二季度登革热发病率较高。有证据表明2003年至2015年登革热发病率呈逐年上升趋势。
登革热在各省份内部和之间的分布存在差异。高风险地区是泰国的中部和南部地区。对数线性模型为登革热传播建模提供了一种简单的方法。这些结果对登革热模式的地理分布非常重要。
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