In Malaysia, travel activities become more intense during the festive seasons, whereby traffic volume on the roads on average increases about 30%. Consequently, this inevitably increases road traffic fatalities. An integrated enforcement program called the OPS Bersepadu has been carried out since 2011 to ensure high road safety performance. This study was carried out to develop a statistical model for predicting the seasonality of traffic fatalities. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to fit road fatalities data between 1980 and 2000 and forecast traffic fatalities from 2001 to 2019. The results showed that the SARIMA (1, 1, 2) (1, 1, 2)12 model fitted the data fairly well and suggest that the SARIMA model is a possible tool that provides an overview of the seasonal patterns of traffic fatalities in Malaysia. The forecasted traffic fatalities based on the SARIMA model were then compared with the actual traffic fatalities during the festive months to explore the effectiveness of the OPS Bersepadu programme to help enforcement authorities allocate optimal resources that could increase the efficiency of enforcement activities to reduce road traffic fatalities.

• Aida, S. M. N., Haziq, H. H., Nurul, S. H., Isnewati, A. M., & Haslinda, A. M. (2018). Modelling road accidents in Malaysia. ESTEEM Academic Journal, 14, 66-76.

• Akhtar, S., & Ziyab, A. H. (2013). Impact of the penalty points system on severe road traffic injuries in Kuwait. Traffic Injury Prevention, 14(7), 743-748. https://doi.org/10.1080/15389588.2012.749466

• Bahadorimonfared, A., Soori, H., Mehrabi, Y., Delpisheh, A., Esmaili, A., & Salehi, M. (2013). Trends of fatal road traffic injuries in Iran (2004-2011). PLoS One, 8(5), Article e65198. https://doi.org/10.1371/journal.pone.0065198

• BH Online. (2015, August 14). Kes kemalangan Op selamat 2015 terburuk sejak 1994 [The worst 2015 Op selamat accident case since 1994]. Berita Harian Online. https://www.bharian.com.my/taxonomy/term/11/2015/08/74733/kes-kemalangan-op-selamat-2015-terburuk-sejak-1994

• Claeskens, G., & Hjort, N. L. (2008). Model selection and model averaging. Cambridge University Press.

• Danlami, N., Napiah, M., Sadullah, A. F. M., & Bala, N. (2017). An overview and prediction of Malaysian road fatality: Approach using generalized estimating equations. International Journal of Civil Engineering and Technology, 8(11), 452-465.

• DOSM. (2019). Statistics on causes of death, Malaysia, 2019. Department of Statistics Malaysia.

• Farsi, M., Hosahalli, D., Manjunatha, B. R., Gad, I., Atlam, E. S., Ahmed, A., Elmarhomy, G., Elmarhoumy, M., & Ghoneim, O. A. (2021). Parallel genetic algorithms for optimizing the SARIMA model for better forecasting of the NCDC weather data. Alexandria Engineering Journal, 60, 1299-1316. https://doi.org/10.1016/j.aej.2020.10.052.

• Feng, H., Duan, G., Zhang, R., & Zhang, W. (2014). Time series analysis of hand-foot-mouth disease hospitalization in Zhengzhou: Establishment of forecasting models using climate variables as predictors. PLoS One, 9(1), Article e87916. https://doi.org/10.1371/journal.pone.0087916

• Ho, A. C. W., Sam, Y. S., & Lai, J. W. F. (2019). Fatality involving road accidents in Malaysia. In Proceedings of the 2019 2nd International Conference on Mathematics and Statistics (pp. 101-105). ACM Publishing. https://doi.org/10.1145/3343485.3343494

• Linthicum, K. J., Anyamba, A., Tucker, C. J., Kelley, P. W., Myers, M. F., & Pelers, C. J. (1999). Climate and satellite indictors to forecast Rift: Valley fever epidemics in Kenya. Science, 285(5426), 397-400. https://doi.org/10.1126/science.285.5426.397

• Low, S. F., Sold, N. F. M., Voon, W. S., & Kassim, K. A. A. (Eds.). (2017). Compilation of OPS Bersepadu studies conducted during Hari Raya Aidilfitri 2017 (Research Report MRR No. 319). Malaysian Institute of Road Safety Research.

• Pang, Y. Y., Zhang, X. J., Tu, Z. B., Cui, M. J., & Gu, Y. (2013). Autoregressive integrated moving average model in predicting road traffic injury in China. Zhonghua Liu Xing Bing Xue Za Zhi, 34(7), 736-739. https://doi.org/10.1016/j.annepidem.2014.10.015

• Paz, A., Veeramisti, N., & Fuente-Mella, H. D. L. (2015). Forecasting performance measures for traffic safety using deterministic and stochastic models. In Proceedings of 2015 IEEE 18th International Conference on Intelligent Transportation Systems (pp. 2965-2970). IEEE Publishing. https://doi.org/10.1109/ITSC.2015.475

• PLUS. (2019). Traffic advisor. Retrieved July 12, 2021, from https://paultan.org/2019/01/30/plus-travel-time-advisory-for-north-south-expressway/

• Radzuan, N. Q., Hassan, M. H. A., Majeed, A. P. A., Kassim, K. A. A., Musa, R. M., Razman, M. A. M., & Othman, N. A. (2020). Forecasting road deaths in Malaysia using support vector machine. In ECCE2019. Lecture Notes in Electrical Engineering (pp. 261-267). Springer. https://doi.org/10.1007/978-981-15-2317-5.

• Sarani, R., Allyana, S. M. R. S., Jamilah, M. M., & Wong, S. V. (2012). Predicting Malaysian road fatalities for year 2020. Malaysian Institute of Road Safety Research.

• Sunny, C. M., Nithya, K. S., Vinodini, V., Aiswaria, L. K. G., Anjana, S., & Manojkumar, T. K. (2018). Forecasting of road accident in Kerala: A case study. In Proceedings of 2018 International Conference on Data Science and Engineering (ICDSE) (pp. 1-5). IEEE Publishing. https://doi.org/10.1109/ICDSE.2018.8527825

• Wang, Z. H., Lu, C. Y., Li, G. W., & Guo, Z. J. (2017). Short-term forecast model of vehicles volume based on ARIMA seasonal model and Holt-Winters. In Proceedings of ITM Web of Conferences (Vol. 12, p. 04028). EDP Sciences. https://doi.org/10.1051/itmconf/20171204028

• Wen, J., Yuan, P., Deng, Z. H., Liu, K. L., Zhang, Y. K., Liu, L. K., Kong, B., & Huang, S. X. (2005). Time series analysis on road traffic injury in China. Sichuan Da Xue Xue Bao Yi Xue Ban 2005, 36(6), 866-869.

• WHO. (2018). Global status report on road safety. World Health Organization. https://www.who.int/publications/i/item/9789241565684

• WHO. (2021). Road traffic injuries. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries

• Zhang, W., Liu, C. H., & Xiao, L. (2019). Predicting vulnerable road user crashes based on seasonal pattern. In Proceedings of International Conference on Transportation and Development (pp. 124-134). American Society of Civil Engineers. https://doi.org/10.1061/9780784482575.013

• Zhang, X. J., Pang, Y. Y., Cui, M. J., Stallones, L., & Xiang, H. Y. (2015). Forecasting mortality of road traffic injuries in China using seasonal autoregressive integrated moving average model. Annal of Epidemiology, 25, 101-106. https://doi.org/10.1016/j.annepidem.2014.10.015

• Zolala, F., Haghdoost, A. A., Ahmadijouybari, T., Salari, A., Bahrampour, A., Baneshi, M. R., & Razzaghi, A. (2016). Forecasting the trend of traffic accident mortality in West Iran. Health Scope, 5(3), Article e31336. https://doi.org/10.17795/jhealthscope-31336