Abstract: Objective To identify the epidemic characteristics of serious road traffic accidents and road traffic injuries in Shanghai from 2013 to 2015 and provide the evidence for road traffic injury intervention. Methods A representative sample of serious road traffic accidents was randomly obtained through a systematic sampling of data from the Shanghai municipal traffic police department to analyze the main cause of serious road traffic injury and clinic feature of injuries. ArcMap 10.1 was used to describe the global spatial autocorrelation and local spatial autocorrelation and spatial clustering in a community scale. Results According to data road traffic in Shanghai from 2013 to 2015, there were a total 224 accidents, 258 casualties (injury and death), and 1.96 million dollars in direct property loss. Most injuries (43.41%) occurred between 6:00 to 12:00. The leading reason was motor vehicle illegal behavior, which accounted for 56.98% of all accidents. In addition, the largest group of victims(33.33%) were E-bike riders and passengers, with the most prevalent clinical characteristic in each age group being brain trauma, accounting for 65.89%. The Getis-OrdGi index of local spatial autocorrelation indicated that the clusters of serious accidents and casualties were detected in the relatively small populated districtsin the east along with the western districts of Shanghai where roads are overlapped with the main channels that connect other cities to Shanghai. Conclusions The influences of road traffic injury include people, vehicle, environment and road. To explorer hotspot, high risk population and develop appropriate intervention program would promote to decrease the serious traffic accidents and casualties.