| 基于自回归移动平均模型的浙江省肺结核发病趋势预测 |
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| 引用本文： | 茅蓉,王远航,葛锐. 基于自回归移动平均模型的浙江省肺结核发病趋势预测[J]. 疾病监测, 2022, 37(5): 652-656. DOI: 10.3784/jbjc.202109240520 |
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| 作者姓名： | 茅蓉 王远航 葛锐 |
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| 作者单位： | 嘉兴市疾病预防控制中心, 浙江 嘉兴 314050 |
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| 摘 要： | 目的应用自回归移动平均(ARIMA)模型对浙江省肺结核疫情预测分析,为浙江省肺结核精准化防控工作提供科学依据。方法收集2011年1月至2021年8月的浙江省肺结核发病率数据,基于R软件(4.0.3)利用2011—2020年肺结核发病率数据建立ARIMA模型,比较2021年1—8月预测数据和实际数据并选择最优模型。结果2011年1月至2020年12月浙江省报告新发肺结核患者总计374718例,呈逐年下降趋势,每年12月至次年2月发病率较低,3—5月相对较高。确定最优模型为ARIMA(2,1,0)(1,1,2)12,该模型拟合的2021年1—8月浙江省肺结核发病率预测值与真实值的平均相对误差为8.87%,赤池信息准则值、贝叶斯信息准则值、均方根误差值和平均绝对百分比误差值分别为95.02、111.05、0.30和4.39。结论ARIMA(2,1,0)(1,1,2)12模型能较好地拟合预测浙江省肺结核发病率在时间序列上的变动趋势,但需根据实际情况动态调整,提高预测精度。
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| 关 键 词： | 预测 自回归移动平均模型 结核 肺 |
| 收稿时间： | 2021-09-24 |
Prediction of incidence of pulmonary tuberculosis in Zhejiang based on autoregressive integrated moving average model |
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| Affiliation: | Outpatient Department, Jiaxing Center for Disease Control and Prevention, Jiaxing 314050, Zhejiang, China |
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| Abstract: | Objective Autoregressive integrated moving average (ARIMA) model was used to predict the incidence of pulmonary tuberculosis (TB) in Zhejiang province to provides scientific basis for the precise prevention and control of pulmonary TB. Methods The monthly incidence rate of pulmonary TB in Zhejiang from January 2011 to August 2021 was collected. Software R (4.0.3) was used to build the ARIMA model based on the incidence rate of TB from 2011 to 2020. The model prediction was compared with the actual data from January to August in 2021 to select some optimal models. Results A total of new 374718 pulmonary TB cases were reported in Zhejiang from January 2011 to August 2021 was, showing a decrease trend. The incidence rate was relatively lower from December to February and relatively higher from March to May. The optimal model was ARIMA (2, 1, 0) (1, 1, 2)12. The mean relative error (MRE) between the predicted value and the actual value of the incidence of pulmonary TB in Zhejiang from January to August in 2021 fitted by this model was 8.87%. The values of AIC, BIC, RMSE and MAPE were 95.02, 111.05, 0.30, and 4.39, respectively. Conclusion The ARIMA (2, 1, 0) (1, 1, 2)12 model can fit and predict the incidence trend of pulmonary TB in Zhejiang, but it needs to be adjusted dynamically according to the actual situation to improve the prediction accuracy. |
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