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

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.

Binary Logistic Regression Analysis, Accident Severity

1. Adavikottu, A., & Velaga, N. R. (2021). Analysis of factors influencing aggressive driver behaviour and crash involvement. Traffic Injury Prevention, 22(sup1), S21–S26. [Google Scholar] [Crossref]

2. Ahmed, S. K., Mohammed, M. G., Abdulqadir, S. O., El-Kader, R. G. A., El-Shall, N. A., Chandran, D., Rehman, M. E. U., & Dhama, K. (2023). Road traffic accidental injuries and deaths: A neglected global health issue. Health Science Reports, 6(5), e1240. [Google Scholar] [Crossref]

3. Al-Ghamdi, A. S. (2002). Using logistic regression to estimate the influence of accident factors on accident severity. Accident Analysis & Prevention, 34(6), 729–741. [Google Scholar] [Crossref]

4. Chen, S., Shao, H., & Ji, X. (2021). Insights into factors affecting traffic accident severity of novice and experienced drivers: A machine learning approach. International Journal of Environmental Research and Public Health, 18(23), 12725. [Google Scholar] [Crossref]

5. Chibaro, M., Munuhwa, S., Mupfiga, C., & Farai, F. C. (2024). Human factors and road traffic safety: An inquiry into the causes of upsurge in road traffic accidents in Harare Metropolitan Province, Zimbabwe. Asian Journal of Management, Entrepreneurship and Social Science, 4(03), 92–108. [Google Scholar] [Crossref]

6. Deepthi, A., Chaithrika, B., Teena, C., Manvitha, G., & Keerthana, G. S. (2023, December). Enhancing road safety: Predicting severity of accidents. In International Conference on Data Science, Machine Learning and Applications (pp. 775–783). Springer Nature Singapore. [Google Scholar] [Crossref]

7. Dominguez-Almendros, S., Benitez-Parejo, N., & Gonzalez-Ramirez, A. R. (2011). Logistic regression models. Allergologia et Immunopathologia, 39, 295–305. [Google Scholar] [Crossref]

8. Eboli, L., Forciniti, C., & Mazzulla, G. (2020). Factors influencing accident severity: An analysis by road accident type. Transportation Research Procedia, 47, 449–456. [Google Scholar] [Crossref]

9. Foya, D. (2019). Road traffic accidents, causes, trends and preventive measures: The case of City of Harare (2012–2018). International Journal of Research and Innovation in Social Science, 3(10), 776–792. [Google Scholar] [Crossref]

10. Goniewicz, K., Goniewicz, M., Pawłowski, W., & Fiedor, P. (2016). Road accident rates: Strategies and programmes for improving road traffic safety. European Journal of Trauma and Emergency Surgery, 42(4), 433–438. [Google Scholar] [Crossref]

11. Haerani, S., Parmitasari, R. D. A., Aponno, E. H., & Aunalal, Z. I. (2019). Moderating effects of age on personality, driving behavior, and driving outcomes. International Journal of Human Rights in Healthcare, 12(2), 91–104. [Google Scholar] [Crossref]

12. https://www.trafficsafety.co.zw. [Google Scholar] [Crossref]

13. McCarty, D., & Kim, H. W. (2024). Risky behaviors and road safety: An exploration of age and gender influences on road accident rates. PLoS ONE, 19(1), e0296663. [Google Scholar] [Crossref]

14. Michalaki, P., Quddus, M. A., Pitfield, D., & Huetson, A. (2015). Exploring the factors affecting motorway accident severity in England using the generalised ordered logistic regression model. Journal of Safety Research, 55, 89–97. [Google Scholar] [Crossref]

15. Munuhwa, S., Govere, E., Samuel, S., & Chiwira, O. (2020). Managing road traffic accidents using a systems approach: Case of Botswana—Empirical review. Journal of Economics and Sustainable Development, 10(11), 176–188. [Google Scholar] [Crossref]

16. Muvuringi, M. P. (2012). Road traffic accidents in Zimbabwe: Influencing factors, impact and strategies. Vrije University Amsterdam, KIT (Royal Tropical Institute). [Google Scholar] [Crossref]

• Tribal Child Nutrition and Health in District of Sundargarh: A Public Health Review of ICDS Intervention
• Knowledge, Attitudes and Practices Towards Prostate Cancer Screening Amongst Men Aged 40-60 Years in The Buea Health District: A Cross-Sectional Study
• Compliance with JCI Protocols: A Focus on Employee Safety
• Influence and Involvement of Teachers in Menstrual Hygiene Management of Female Secondary School Students in Kogi State, Nigeria
• A Critical Evaluation of Ayushman Bharat Pradhan Mantri Jan Arogya Yojana in Bihar