Tubtimhin S, Laohasiriwong W, Pitaksanurat S, Sornlorm K, Luenam A
Faculty of Public Health, Khon Kaen University, Khon Kaen, Thailand.
Faculty of Public and Environmental Health, Huachiew Chalermprakiet University, Samut Prakan, Thailand.
Kathmandu Univ Med J (KUMJ). 2019;17(67):184-189.
Background Road traffic injury (RTI) is a major cause of fatalities around the world and Thailand is the second leading country. Objective To determine the spatial pattern of road traffic injury during the 7-day Songkran holiday in Thailand. Method This study utilized the data obtained from the Information Technology for Emergency Medical System (ITEMS) covering the nationwide road traffic injury during the Songkran festival, Thai New Year holiday (April 9-15, 2015). The Moran's I was used to identify global autocorrelation within the country whereas the Local Indicators of Spatial Association (LISA) analysis was administered for analyzing the spatial distribution of RTIs and determining the spatial autocorrelation and correlation of numbers motor vehicles and length of road networks and road traffic injury. Result During Songkran holiday 2015, the univariate Moran's I of RTIs distribution among provinces in Thailand showed a slightly positive spatial autocorrelation, as the Moran's I was 0.1701, with statistical significance at 0.05. Local indicators of spatial association indicated seven hotspots and five cold spots. In addition, the number of motor vehicles, and length of trunk road (super highway), tertiary roads, secondary roads, and primary roads had positive spatial autocorrelation with road traffic injury, with Moran's I values of 0.173, 0.117, 0.219, 0.162, and 0.279, respectively. Conclusion This study demonstrates that local indicators of spatial association could detect the spatial pattern of road traffic injury. The number of motor vehicles, length of all roads served as new parameters for determining road traffic injury hotspots.
道路交通伤害（RTI）是全球主要的死亡原因之一，泰国是道路交通伤害致死率第二高的国家。目的：确定泰国宋干节7天假期期间道路交通伤害的空间模式。方法：本研究利用了从紧急医疗系统信息技术（ITEMS）获得的数据，该数据涵盖了泰国新年假期宋干节期间（2015年4月9日至15日）全国范围内的道路交通伤害情况。使用莫兰指数（Moran's I）来识别该国范围内的全局自相关性，而局部空间自相关指标（LISA）分析则用于分析道路交通伤害的空间分布，并确定机动车数量、道路网络长度与道路交通伤害之间的空间自相关性和相关性。结果：在2015年宋干节假期期间，泰国各省道路交通伤害分布的单变量莫兰指数（Moran's I）显示出轻微的正空间自相关性，莫兰指数为0.1701，在0.05水平上具有统计学意义。局部空间自相关指标显示有7个热点和5个冷点。此外，机动车数量以及主干道（高速公路）、三级公路、二级公路和一级公路的长度与道路交通伤害存在正空间自相关性，莫兰指数分别为0.173、0.117、0.219、0.162和0.279。结论：本研究表明，局部空间自相关指标可以检测道路交通伤害的空间模式。机动车数量和所有道路的长度可作为确定道路交通伤害热点的新参数。
