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目的分析上海市2013-2015年重特大交通事故及其伤亡信息的流行特征,为开展道路交通伤害预防提供依据。方法系统抽取上海市交警2013-2015年重特大道路交通事故信息,分析其主要事故原因、伤亡人员主要交通方式和临床特征。利用Arc Map 10.1软件分析交通事故面数据的全局和局部空间自相关,探索事故的空间聚集特征。结果上海市2013-2015年重特大交通事故抽样数据共224起,伤亡人员258人,直接财产损失共计196.14万元。人员伤亡以上午时段(6∶00~12∶00)为主,占43.41%;事故认定原因以机动车违法为主,占56.98%;受伤人群以电动自行车骑乘人员为主,占33.33%;人群伤亡临床特征以头部损伤为主,总计占65.89%。交通事故空间分析显示,事故高发区域和人群伤亡区域主要聚集于本市西部地区与外省市交汇处国道附近,在本市东部地区人口相对较少的区域也呈现事故聚集。结论道路交通事故的发生涉及到人、车、环境和道路;探测道路交通安全的重点区域和人群,开展有针对性的干预措施,有助于降低道路交通伤害的发生。
Objective To analyze the epidemiological characteristics of major traffic accidents and their casualty information in 2013-2015 in Shanghai and provide evidence for the prevention of road traffic injuries. Methods The traffic accident information of traffic police in Shanghai from 2013 to 2015 was extracted and analyzed for the main causes of accidents, the main traffic modes and clinical features of casualties. The Arc Map 10.1 software was used to analyze the global and local spatial autocorrelation of traffic accident surface data to explore the spatial agglomeration characteristics of accidents. Results A total of 224 samples of heavy traffic accidents in Shanghai during 2013-2015 were collected, including 258 casualties. The total direct asset losses totaled 1.61.414 million yuan. The casualties were mainly in the morning session (6:00 ~ 12:00), accounting for 43.41%. The main reasons for the accident were motor vehicle infringement, accounting for 56.98% of the total. The injured were mainly e-bike riders, accounting for 33.33% of the total. The clinical characteristics of the population casualties were mainly head injuries, accounting for a total of 65.89%. The spatial analysis of traffic accidents shows that the areas with high accident and casualties of people mainly gather near the national road where the western part of the city meets the other provinces and municipalities and the area with relatively small population in the eastern part of the city also presents an accident gathering. Conclusion The occurrence of road traffic accidents involves people, vehicles, environment and roads. The detection of road traffic safety in key areas and people and targeted interventions will help to reduce the occurrence of road traffic injuries.