Repository of Research and Investigative Information

Repository of Research and Investigative Information

Ilam University of Medical Sciences

Predicting Number of Traumas Using the Seasonal Time Series Model

Sun Sep 25 11:12:47 2022

(2019) Predicting Number of Traumas Using the Seasonal Time Series Model. Archives of Trauma Research. pp. 23-27. ISSN 2251-953X

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Abstract

Background: Road accidents and casualties resulted are among the current challenges of human societies, which have imposed a high cost on the economies of countries. Objectives: Prediction of accidents caused by driving incidents helps planners achieve a suitable model to reduce the occurrence of traumas resulted from the driving accidents. Materials and Methods: In this study, a seasonal time series model was used for predicting the number of road accident traumas. Data related to the patients referring to Imam Khomeini Hospital in Ilam Province were evaluated from March 2012 to June 2017. Results: The results showed that during November and October in 2015 and 2016, we had the highest number of accidents due to high traffic during New Year's Vacation, summer trips, and religious pilgrimages including the Arbaeen. Moreover, the results depicted that the seasonal Arima model was effective in predicting the number of traumas due to accidents. Furthermore, forecasting the model showed an ascending trend in the number of accidents in the following 3 years. Conclusion: The number of accident traumas in the forthcoming months can be predicted through time series models. Of course, these models can be used by managers as appropriate tools for traffic analysis. Furthermore, the increasing trend in the number of traumas indicates that serious consideration for planning and managing such events seems necessary for the administrators in the near future.

Item Type: Article
Creators:
CreatorsEmail
Nademi, A.UNSPECIFIED
Shafiei, E.UNSPECIFIED
Fakharian, E.UNSPECIFIED
Kalvandi, G.UNSPECIFIED
Talaeizadeh, K.UNSPECIFIED
Keywords: Accidents forecasting interrupted time series analysis traffic road traffic accidents burden Orthopedics
Divisions:
Page Range: pp. 23-27
Journal or Publication Title: Archives of Trauma Research
Journal Index: ISI
Volume: 8
Number: 1
Identification Number: https://doi.org/10.4103/atr.atr₆₅₁₈
ISSN: 2251-953X
Depositing User: مهندس مهدی شریفی
URI: http://eprints.medilam.ac.ir/id/eprint/2425

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