ORIGINAL RESEARCH article
Front. Public Health
Sec. Injury Prevention and Control
Spatio-temporal Distribution and Aggregation Analysis of Road Traffic Fatalities in Shandong Province, China, 2012–2022
Provisionally accepted
- 1People’s Hospital of Deyang City, Deyang, China
- 2Shandong University, Jinan, China
- 3Shandong Center for Disease Control and Prevention, Jinan, China
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This study aimed to analyze the temporal and spatial distribution, as well as 5 spatio-temporal aggregation, of road traffic fatalities in Shandong Province, China, 6 from 2012 to 2022, with the aim of establishing scientific foundation for crafting 7 customized intervention strategies and preventive actions to mitigate road traffic 8 fatalities. Data were obtained from the Chinese Center for Disease Control and 9 Prevention Population Death Information Registration Management System. Statistical 10 analyses, including composition ratios, chi-square tests, spatial autocorrelation analyses, 11 and spatio-temporal aggregation, were conducted. Software tools, such as Excel, Geoda, 12 and SaTScan v10.1.2, were utilized for data analysis. Results showed pedestrians were 13 the most affected group (55.18%), followed by motorized drivers, non-motorized 14 drivers, and passengers. The temporal distribution showed cyclical trends, with the 15 largest number of deaths in autumn. Passengers had a higher number of deaths during 16 leave in lieu (χ2=12.247, P=0.007) and vacation (χ2=17.599, P=0.001) than other 17 subgroups. The spatial distribution identified varying hotspots and cold spots across 18 different cities in Shandong Province. The spatial autocorrelation analysis indicated 19 unique patterns for different groups of road traffic fatalities. Spatio-temporal cluster 20 analysis indicated that a notable and novel finding was the emergence of non-motorized 21 drivers as the newest spatio-temporal agglomeration in southwestern Shandong, while 22 that of motorized drivers was distinctly located in the Jiaodong Peninsula. In conclusion, 23 targeted measures in high-risk areas and peak periods have reduced road traffic fatalities. 24 Legislative efforts and educational campaigns have improved road safety; however, 25 challenges with e-bikes require focused interventions.
Keywords: road traffic fatalities, Shandong province, temporal distribution, spatial autocorrelation, Spatio-temporal aggregation
Received: 24 Sep 2025; Accepted: 25 Nov 2025.
Copyright: © 2025 Wang, Lu, Chu, Li, Yao, Guo and Jia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiao-Lei Guo
Cunxian Jia
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