Trend Analysis of Road Traffic Accident Injuries and Fatalities Using Nonparametric Statistical Methods: A Temporal and Seasonal Assessment

Abstract

Road traffic accidents remain a major public health concern, requiring systematic analyses of temporal trends to support evidence-based road safety planning. This retrospective longitudinal study analyzes traffic accident-related injuries and fatalities in Diyarbakir Province, Türkiye, based on official records from 2014 to 2023. The study evaluates temporal trends in accident severity and their associations with selected accident-related variables across monthly, seasonal, and annual scales. Four complementary non-parametric trend analysis methods, including Innovative Trend Analysis (ITA), Innovative Polygon Trend Analysis (IPTA), the Sen Slope Test Method (SSTM), and the Mann-Kendall (MK) trend test, were applied to injury and fatality data. Correlation analysis was also performed to examine the associations between 26 accident-related parameters and injury and fatality counts. The results revealed a statistically significant decreasing trend in injury counts, whereas fatalities showed increasing tendencies during specific periods, indicating that reductions in accident frequency were not accompanied by proportional decreases in accident severity. Seasonal analysis showed that injuries occurred more frequently in summer, while fatalities were relatively higher in winter and spring. Correlation analysis identified significant associations between accident outcomes and several traffic-related variables, highlighting the complex temporal characteristics of road traffic accidents. Overall, the findings demonstrate the importance of integrating complementary non-parametric trend analysis methods for evaluating accident severity patterns and supporting regional road safety assessment.