Prediction and analysis of road traffic injury death trend based on ARIMA model

XUN Lu-ning; ZHANG Fan; SUN Ji-xin; CAO Ya-jing; SUN Zhen; SHI Wei-wei; LI Mei; CUI Ze

doi:10.16462/j.cnki.zhjbkz.2020.04.019

Volume 24 Issue 4

Jun. 2020

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Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2020 > 24(4): 467-472

XUN Lu-ning, ZHANG Fan, SUN Ji-xin, CAO Ya-jing, SUN Zhen, SHI Wei-wei, LI Mei, CUI Ze. Prediction and analysis of road traffic injury death trend based on ARIMA model[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2020, 24(4): 467-472. doi: 10.16462/j.cnki.zhjbkz.2020.04.019

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XUN Lu-ning, ZHANG Fan, SUN Ji-xin, CAO Ya-jing, SUN Zhen, SHI Wei-wei, LI Mei, CUI Ze. Prediction and analysis of road traffic injury death trend based on ARIMA model[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2020, 24(4): 467-472. doi: 10.16462/j.cnki.zhjbkz.2020.04.019

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Prediction and analysis of road traffic injury death trend based on ARIMA model

doi: 10.16462/j.cnki.zhjbkz.2020.04.019

1.
College of Public Health, North China University of Science and Technology, Tangshan 063210, China
2.
Department of Chronic Non-communicable Disease Control and Prevention, Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang 050011, China

Funds: 2017 Hebei Provincial Medical Science Research Key Project Plan(20170447)

More Information

Corresponding author: CUI Ze, E-mail:cuize11@163.com
Received Date: 2019-11-08
Rev Recd Date: 2020-02-03
Publish Date: 2020-04-10

Abstract

Abstract

Objective To analyze the death trend of road traffic injury in Hebei province from 2014 to 2018, and to discuss the feasibility of autoregressive integrated moving average model(ARIMA) in the prediction of road traffic injury deaths trend. Methods Descriptive epidemiological method was used to analyze the general situation of road traffic injury deaths in Hebei province from 2014 to 2018. R 3.5.3 was used to establish the ARIMA prediction model for the monthly death cases of road traffic injury in Hebei province from January 2014 to June 2018. The overall regression was used to observe the fitting effect, the predicted value and the real value were compared from July to December in 2018 to evaluate the prediction effect. Results A total of 13 147 road traffic injury deaths from 2014 to 2018 were reported by Hebei province. The number of road traffic injury deaths was 10 071 males and 3 076 females, with an annual mortality rate of 17.79/100 000, showing a downward trend overall. The best prediction model is ARIMA(0, 1, 1)(0, 1, 1)₁₂. Akaike information criterion(AIC) is 390.64, Schwarz Bayesian criterion(SBC) is 395.78, the residual sequence is white noise sequence(P > 0.05), and the parameters of the model are significantly non-zero(P < 0.05). The actual values of the prediction results all fall within the 95% confidence interval of the predicted values, and the relative error between the predicted values and the actual values is between 1.15% and 11.85%. The root mean square error(RMSE) is 13.65, the mean absolute error(MAE) is 10.88, and the mean average percentage error(MAPE) is 4.80%. The prediction performance of the model is good. Conclusions The overall road traffic injury deaths in Hebei province show a downward trend year by year. ARIMA model can be used to predict the short-term trend of road traffic injury deaths.
- ARIMA model,
- Road traffic injury,
- Death trend,
- Prediction

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References(19)

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