Forecasting the Trend of Traffic Accident Mortality in West Iran

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Author(s)
Zolala, Farzaneh
Haghdoost, Ali Akbar
Ahmadijouybari, Touraj
Salari, Arash
Bahrampour, Abbas
Baneshi, Mohamad Reza
Razzaghi, Alireza
Griffith University Author(s)
Year published
2016
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Background: Traffic accidents are the main cause of deaths in developing countries. Fatalities due to traffic accidents are assessed through a three-year time series forecast.
Objectives: The aim of this study is to use trend assessment to predict traffic accident fatalities for January 2013 to December 2015 in Kermanshah province, Iran.
Materials and Methods: This is a historical longitudinal study using time series analysis to identify the best fit model. The criteria of MSE (mean square of error) were used to determine the model with the best goodness of fit. The model that had the smaller MSE value was introduced as a ...
View more >Background: Traffic accidents are the main cause of deaths in developing countries. Fatalities due to traffic accidents are assessed through a three-year time series forecast. Objectives: The aim of this study is to use trend assessment to predict traffic accident fatalities for January 2013 to December 2015 in Kermanshah province, Iran. Materials and Methods: This is a historical longitudinal study using time series analysis to identify the best fit model. The criteria of MSE (mean square of error) were used to determine the model with the best goodness of fit. The model that had the smaller MSE value was introduced as a suitable model. The selected model was used to forecast the number of deaths related to traffic accidents in the next three years. Results: A decreasing trend was observed in accident mortality. The highest and lowest deaths were seen annually in the spring and autumn months, respectively. The SARIMA (0, 0, 0) × (1, 1, 1) 12 model was identified as the best-fit model for data. Prediction values of traffic accident fatalities showed a decreasing trend in deaths in the coming years. Conclusions: Applying this information can be useful to policy makers and managers for planning and implementing special interventions to prevent and limit future accidental deaths.
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View more >Background: Traffic accidents are the main cause of deaths in developing countries. Fatalities due to traffic accidents are assessed through a three-year time series forecast. Objectives: The aim of this study is to use trend assessment to predict traffic accident fatalities for January 2013 to December 2015 in Kermanshah province, Iran. Materials and Methods: This is a historical longitudinal study using time series analysis to identify the best fit model. The criteria of MSE (mean square of error) were used to determine the model with the best goodness of fit. The model that had the smaller MSE value was introduced as a suitable model. The selected model was used to forecast the number of deaths related to traffic accidents in the next three years. Results: A decreasing trend was observed in accident mortality. The highest and lowest deaths were seen annually in the spring and autumn months, respectively. The SARIMA (0, 0, 0) × (1, 1, 1) 12 model was identified as the best-fit model for data. Prediction values of traffic accident fatalities showed a decreasing trend in deaths in the coming years. Conclusions: Applying this information can be useful to policy makers and managers for planning and implementing special interventions to prevent and limit future accidental deaths.
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Journal Title
Health Scope
Volume
5
Issue
3
Copyright Statement
© 2016, Health Promotion Research Center. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.
Subject
Transport planning
Science & Technology
Life Sciences & Biomedicine
Public, Environmental & Occupational Health
Traffic Accidents
Mortality