Remote Sensing and GIS Field of Study, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand.
Int J Environ Res Public Health. 2012 Oct 24;9(11):3824-42. doi: 10.3390/ijerph9113824.
Influenza is one of the most important leading causes of respiratory illness in the countries located in the tropical areas of South East Asia and Thailand. In this study the climate factors associated with influenza incidence in Chiang Mai Province, Northern Thailand, were investigated. Identification of factors responsible for influenza outbreaks and the mapping of potential risk areas in Chiang Mai are long overdue. This work examines the association between yearly climate patterns between 2001 and 2008 and influenza outbreaks in the Chiang Mai Province. The climatic factors included the amount of rainfall, percent of rainy days, relative humidity, maximum, minimum temperatures and temperature difference. The study develops a statistical analysis to quantitatively assess the relationship between climate and influenza outbreaks and then evaluate its suitability for predicting influenza outbreaks. A multiple linear regression technique was used to fit the statistical model. The Inverse Distance Weighted (IDW) interpolation and Geographic Information System (GIS) techniques were used in mapping the spatial diffusion of influenza risk zones. The results show that there is a significance correlation between influenza outbreaks and climate factors for the majority of the studied area. A statistical analysis was conducted to assess the validity of the model comparing model outputs and actual outbreaks.
流感是东南亚热带国家和泰国导致呼吸道疾病的最重要的主要原因之一。本研究调查了与泰国北部清迈省流感发病率相关的气候因素。确定导致流感爆发的因素并绘制清迈潜在风险区域的地图早已迫在眉睫。这项工作检查了 2001 年至 2008 年之间的年度气候模式与清迈省流感爆发之间的关联。气候因素包括降雨量,降雨天数百分比,相对湿度,最高温度,最低温度和温差。该研究开发了一种统计分析方法,定量评估气候与流感爆发之间的关系,然后评估其用于预测流感爆发的适用性。使用多元线性回归技术拟合统计模型。使用反距离加权(IDW)插值和地理信息系统(GIS)技术绘制流感风险区域的空间扩散图。结果表明,对于大部分研究区域,流感爆发与气候因素之间存在显著相关性。进行了统计分析以评估模型的有效性,比较了模型输出和实际爆发。