Long-Term Trends in Road Traffic Accidents and Mortality in Tunisia: Persistent Territorial Disparities (2002–2025)
DOI:
https://doi.org/10.63002/assm.405.1846Keywords:
Road accidents, Road mortality, Territorial disparities, Spatiotemporal analysis, TunisiaAbstract
This study analyzes the temporal and spatial evolution of road accidents and road deaths in Tunisia between 2002 and 2025. It examines the differences between the 24 governorates and compares trends in accidents and deaths. The analysis is based on data from the National Road Safety Observatory (ONSR) and the National Institute of Statistics (INS). It covers 576 observations over 24 years. The Mann–Kendall test and Sen’s slope are used to measure trends. The coefficient of variation is used to study annual fluctuations in mortality. The frequency of exceedances of the national rate is used to assess the persistence of territorial disparities.
Between 2002 and 2025, the number of accidents fell from 12,127 to 5,424, a decrease of 55.3%. The number of fatalities decreased from 1,585 to 1,253 (−20.9%). By contrast, the number of fatalities per 100 recorded accidents rose from 13.07 to 23.10. There is a downward trend in the accident rates in all 24 governorates. This decrease is statistically significant in 19 governorates, compared to 16 for mortality rates, at the 5% threshold in the individual Mann–Kendall tests. Territorial disparities remain marked. In Gabès, the mortality rate exceeded the national rate for 23 of the 24 years studied, compared to 21 years in Kairouan, Zaghouan and Médenine. These results show that the decline in accidents is not accompanied by a comparable reduction in fatalities. They also highlight the value of considering several indicators to better assess road risk and guide prevention measures.
References
Alhaek, F., Li, T., Rajeh, T. M., Javed, M. H., & Liang, W. (2025). Encoding global semantic and localized geographic spatial-temporal relations for traffic accident risk prediction. Information Sciences, 697, 121767. https://doi.org/10.1016/j.ins.2024.121767
Alharbi, R.J. (2025). National trends in road traffic injuries and fatalities in Saudi Arabia from 2000 to 2023. Scientific Reports, 15, 42838. https://doi.org/10.1038/s41598-025-15217-z
Alhusain, F., Alghafees, M., Rezk, A., Alwatban, S., Almoaiqel, F., & Alsalamah, M. (2023). Exploring the spatio-temporal patterns of road traffic accidents in Saudi Arabia. Saudi Journal of Emergency Medicine, 4(1), 12–30. https://doi.org/10.24911/SJEMed/72-1669286526
Alsahfi, T. (2024). Spatial and temporal analysis of road traffic accidents in major Californian cities using a geographic information system. ISPRS International Journal of Geo-Information, 13(5), 157. https://doi.org/10.3390/ijgi13050157
Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
Asadi, M., Ulak, M. B., Geurs, K. T., & Weijermars, W. (2024). A methodological framework to conduct joint zone-based analysis of traffic safety and accessibility. Journal of Transport Geography, 118, 103949. https://doi.org/10.1016/j.jtrangeo.2024.103949
Atalay, Y. A., Alemie, B. W., Gelaw, B., & Gelaw, K. A. (2025). Epidemiology of road traffic accidents and its associated factors among public transportation in Africa: Systematic review and meta-analysis. Frontiers in Public Health, 13, 1511715. https://doi.org/10.3389/fpubh.2025.1511715
Belarem, M. (2022a). Mapping road traffic crashes in Sfax Governorate (Tunisia). Open Journal of Applied Sciences, 12(1), 19–41. https://doi.org/10.4236/ojapps.2022.121003
Belarem, M. (2022b). The practice of “two-wheelers” in Sfax City (Tunisia). Open Access Library Journal, 9(3), 1–21. https://doi.org/10.4236/oalib.1108398
Belarem, M. (2026). Territorial profiles of road risk in Tunisia: Structure and severity of road traffic accidents. Applied Sciences Research Periodicals, 4(5). https://doi.org/10.63002/asrp.405.1780
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
GBD 2021 Causes of Death Collaborators. (2024). Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: A systematic analysis for the Global Burden of Disease Study 2021. The Lancet, 403(10440), 2100–2132. https://doi.org/10.1016/S0140-6736(24)00367-2
GBD 2021 Diseases and Injuries Collaborators. (2024). Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: A systematic analysis for the Global Burden of Disease Study 2021. The Lancet, 403(10440), 2133–2161. https://doi.org/10.1016/S0140-6736(24)00757-8
Gedamu, W. T., Plank-Wiedenbeck, U., & Wodajo, B. T. (2025). Spatio-temporal analysis of road traffic crashes by severity. Transportation Engineering, 20, 100327. https://doi.org/10.1016/j.treng.2025.100327
Hamed, K. H., & Rao, A. R. (1998). A modified Mann–Kendall trend test for autocorrelated data. Journal of Hydrology, 204(1–4), 182–196. https://doi.org/10.1016/S0022-1694(97)00125-X
International Transport Forum (ITF). (2024). Road safety annual report 2024. OECD Publishing. https://www.itf-oecd.org/road-safety-annual-report-2024
Le, K. G., Liu, P., & Lin, L.-T. (2022). Traffic accident hotspot identification by integrating kernel density estimation and spatial autocorrelation analysis: A case study. International Journal of Crashworthiness, 27(2), 543–553. https://doi.org/10.1080/13588265.2020.1826800
Loghmari, D., Hicheri, Y., Soua, S., Mbarek, R., Boudriga, M., Lihiou, F., & Chebili, N. (2023). Epidemiological and prognostic factors associated with road traffic accidents occurring in the Center East of Tunisia. Tunisian Journal of Emergency Medicine, 2(3). https://doi.org/10.66759/b506de43
Mann, H. B. (1945). Nonparametric tests against trend. Econometrica, 13(3), 245–259. https://doi.org/10.2307/1907187
Miao, C., Chen, X., & Zhang, C. (2024). Assessing network-based traffic crash risk using prospective space-time scan statistic method. Journal of Transport Geography, 119, 103958. https://doi.org/10.1016/j.jtrangeo.2024.103958
Mohammadi, R. (2024). Analyzing urban crash incidents: An advanced endogenous approach using spatiotemporal weights matrix. Transactions in GIS, 28(2), 368–410. https://doi.org/10.1111/tgis.13138
Ouni, M., & Mraihi, R. (2025). Impact of socioeconomic determinants on road traffic accidents in Tunisia: Insights from the dynamic ARDL and machine learning approaches. Transportation Letters, 17(9), 1665–1681. https://doi.org/10.1080/19427867.2025.2479190
Qian, K., & Li, Y. (2024). Safer traffic recovery from the pandemic in London – Spatiotemporal data mining of car crashes. Applied Spatial Analysis and Policy, 17, 87–113. https://doi.org/10.1007/s12061-023-09533-y
Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall's tau. Journal of the American Statistical Association, 63(324), 1379–1389. https://doi.org/10.2307/2285891
Wang, T., Lu, Z.-L., Chu, J., Li, Q., Yao, Z., Guo, X.-L., & Jia, C.-X. (2025). Spatio-temporal distribution and aggregation analysis of road traffic fatalities in Shandong Province, China, 2012–2022. Frontiers in Public Health, 13, 1711959. https://doi.org/10.3389/fpubh.2025.1711959
Wang, T., Yao, Z.-Y., Liu, B.-P., & Jia, C.-X. (2023). Temporal and spatial trends in road traffic fatalities from 2001 to 2019 in Shandong Province, China. PLOS ONE, 18(7), e0287988. https://doi.org/10.1371/journal.pone.0287988
Yue, S., & Wang, C. Y. (2004). The Mann–Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resources Management, 18, 201–218. https://doi.org/10.1023/B:WARM.0000043140.61082.60
Zhang, R., Shuai, B., Gao, P., & Li, Y. (2025). Capturing signals of road traffic safety risk: Based on the spatial-temporal correlation between traffic violations and crashes. Traffic Injury Prevention, 26(5), 557–566. https://doi.org/10.1080/15389588.2024.2427270
Zhou, W., Xu, P., Wu, J., & Huang, J. (2025). Examining macro-level traffic crashes considering nonlinear and spatiotemporal spillover effects. Accident Analysis & Prevention, 211, 107852. https://doi.org/10.1016/j.aap.2024.107852
Official Data and Reports
National Institute of Statistics (INS). (n.d.). Demographic statistics of Tunisia. https://www.ins.tn/
Natural Earth. (n.d.). Admin 0 – Countries, 1:50m. https://www.naturalearthdata.com/
National Road Safety Observatory (ONSR). (n.d.). Traffic accident statistics. https://www.onsr.nat.tn/onsr/statistiques.php
World Health Organization. (2023). Global status report on road safety 2023. https://www.who.int/publications/i/item/9789240086517
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Mongi Belarem

This work is licensed under a Creative Commons Attribution 4.0 International License.
