Construction of ARIMA and exponential smoothing models based on cardiovascular and cerebrovascular disease mortality data and comparison of their predictive efficacy
Objective Based on the death data of cardiovascular and cerebrovascular diseases,the differential autoregres-sive moving average model(ARIMA model)and the exponential smoothing model were constructed to compare the predic-tion efficiency of the two models for disease death,and the prediction model was selected to provide scientific basis for the prevention and control of cardiovascular and cerebrovascular diseases.Methods The data of deaths from cardiovascular and cerebrovascular diseases of residents in Jiamusi city from 2017 to 2021 were collected from Population Death Information Registration Management System of China Disease Control and Prevention Information System,and the ARIMA model and exponential smoothing model were constructed to predict the number of deaths from cardievascular and cerebrovascular diseases from January to December 2022,and to compare it with the actual values in January-December in 2022,in order to assess the predictive efficacy of the 2 models.Results From 2017 to 2021,the number of deaths from cardiovascular and cerebrovascular diseases of Jiamusi residents was 44 230,and the mortality rate was 381.94/105,show-ing an increasing trend.The optimal model for constructing ARIMA model of cardiovascular and cerebrovascular diseases was:ARIMA(0,1,1)(1,0,0),The prediction parameters of the model were mean absolute percentage error(MAPE)=8.37％,bayesian information criterion(BIC)=8.696,root mean square error(RMSE)=69.722,mean absolute error(MAE)=53.143.The Holt-Winters additivity model of the exponential smoothing method was the optimal model.The predicted parameters of the model were MAPE=6.91％,BIC=8.200,RMSE=54.462,MAE=539.722.The average ab-solute percentage error of the exponential smoothing model was smaller than that of the ARIMA model.Conclusion Based on the data of cardiovascular and cerebrovascular disease deaths,ARIMA model and exponential smoothing method model are successfully constructed.The exponential smoothing method model is more effective than the ARIMA model in predicting cardiovascular disease deaths and is suitable for short-term prediction of cardiovascular disease deaths.
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万方数据
