2014—2019年乌鲁木齐市水痘流行特征以及预测模型分析
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王芝梦,在读研究生,主要研究方向:流行病学与卫生统计学

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R181

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Epidemic characteristics and prediction model analysis of chickenpox in Urumqi in 2014 - 2019
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    摘要:

    目的 构建乌鲁木齐市水痘发病的预测模型,为制定水痘的预防控制策略提供参考依据。方法 选取2014—2018年乌鲁木齐市水痘月发病率分别建立多元自回归移动平均(Multivariate Autoregressive Moving Average ,ARIMAX)模型和随机森林(Random Forest ,RF)模型,并用2019年水痘月发病率测试模型以及评价模型的预测效果。对两模型预测性能进行比较,选取预测乌鲁木齐市水痘发病的模型。结果 乌鲁木齐市水痘发病呈有规律的双峰分布,具有明显季节性,2014年7月-2019年12月呈整体缓慢上升趋势。拟合模型为 ARIMA(0,1,0)(0,1,1)[12],ARIMAX模型训练集均方根误差(Root Mean Square Error ,RMSE)和均绝对误差(Mean Absolute Error ,MAE)分别为1.29和0.95,测试集RMSE和MAE分别为1.88和1.44。RF模型训练集RMSE和MAE分别为1.56和1.56,测试集RMSE和MAE分别为4.83和3.96。结论 ARIMAX模型性能优于RF模型,能较好的预测乌鲁木齐市的水痘发病趋势,需根据实际情况不断优化模型,为水痘疫情防控提供科学指导。

    Abstract:

    Objective To construct an optimal prediction model of chickenpox in Urumqi, and to provide reference for formulating the prevention and control strategies of chickenpox. Methods The multivariate autoregressive moving average model (ARIMAX) and random forest model (RF) were established based on the monthly incidence of chickenpox in Urumqi from 2014 to 2018, and the monthly incidence of chickenpox in 2019 was used to test the models and evaluate their prediction effect. The prediction performance of the two models was compared, and the best model was selected to predict the incidence of chickenpox in Urumqi. Results The incidence of chickenpox in Urumqi showed a regular bimodal distribution with obvious seasonality, and it showed a slow upward trend from July 2014 to December 2019. The fitting model was ARIMA(0,1,0)(0,1,1)[12], the root mean square error (RMSE) and mean absolute error (MAE) of ARIMAX model training set were 1.29 and 0.95, respectively, and the RMSE and MAE of the test set were 1.88 and 1.44, respectively. The training set RMSE and MAE of RF model were 1.56 and 1.56, respectively, and the test set RMSE and MAE were 4.83 and 3.96, respectively. Conclusion The performance of ARIMAX model is better than that of RF model, which can better predict the incidence trend of chickenpox in Urumqi. It is necessary to optimize the prediction model according to the actual situation and provide scientific guidance for the prevention and control of chickenpox.

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  • 收稿日期:2024-12-03
  • 最后修改日期:2024-12-03
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  • 在线发布日期: 2025-01-15
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