Logistic Regression Modelling of Road Traffic Accident Severity: A Study on Driver Characteristics in Zimbabwe

Abstract

Road traffic accidents (RTAs) remain a major public health concern in Zimbabwe, yet little empirical work has examined the combined influence of driver behavior, demographic characteristics and environmental factors on accident severity. This study applied binary logistic regression analysis to a dataset of 500 accident-involved drivers to identify the key predictors of severe accidents. Frequency distributions summarised the characteristics of drivers, environmental conditions and vehicle status, while logistic regression quantified their influence on accident severity. The results showed that six key predictors significantly increased the likelihood of severe accidents: low driving experience, alcohol use, fatigue, mobile phone use, over speeding and wet road conditions. Over speeding emerged as the strongest predictor, with drivers who overspeed being four times more likely to be involved in a severe accident. Although age, gender, time of accident and vehicle condition were not statistically significant, they exhibited expected directional effects. The full model (M1) significantly improved prediction compared to the null model (M0) with Δχ² = 77.3 demonstrating that the included predictors collectively enhance the model’s explanatory power with respect to predicting accident severity. It demonstrated an acceptable predictive accuracy with an AUC = 0.720, indicating its effectiveness in distinguishing between severe and non-severe accidents. The findings emphasize that human behavior remains the most critical determinant of accident severity in Zimbabwe, with implications for targeted interventions. The study findings highlight the need for evidence-based interventions focused on speed control, anti-drunk driving enforcement, fatigue management, mobile phone usage laws, targeted road safety campaigns and improved road infrastructure especially during wet conditions. Training and awareness programs targeting inexperienced drivers could reduce severity outcomes. The study contributes valuable insights toward improving road safety strategies in Zimbabwe and similar contexts.