Estimating Accident-Related Traumatic Injury Rate by Future Studies Models in Semnan Province, Iran

Background: Any accident is a disturbance in the balance between the human system, vehicle, road and environment. Future prediction of traumatic accidents is a valuable factor for managers to make strategic decisions in the areas of safety, health and transportation. Materials and Methods: In this study, by using Grey Model (GM) (1.1), Rolling Grey Model (RGM), Fourier Grey Model (FGM) (1.1), survival modification model, ARIMA time series, harmonic pattern and statistical data, the number of traffic injuries referred to forensic medicine centers in Semnan Province between 2017 and 2020 were predicted based on the number of traffic injured in Semnan Province from March 2009 and March 2016 . Results: The mean absolute error percentage for the GM (1.1), RGM (1), FGM (1.1), survival model, ARIMA and harmonic models were 0.994, 0.082, 0.091, 0.105, 0.05, 0.11, respectively, indicating a greater accuracy of the ARIMA method, compared to the other methods. The number of road traffic injuries in Semnan Province is decreasing and will reach 4052 in 2020. Conclusion: ARIMA model is the best method of the future studies model for the number of injured patients referred to the forensic medicine centers in Semnan Province compared to other studied methods. Future studies model shows that the injuries caused by accidents in the province of Semnan are decreasing

Estimating Accident-Related Traumatic Injury Rate by Future Studies Models in Semnan Province, Iran Keywords:

Forecasting , Accidents , Trauma