状态空间模型在我国肝炎发病率预测中的应用
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江苏省大学生实践创新训练计划项目(201310312036Y);江苏省高校自然科学基金(13KJB310007);南京医科大学科技发展基金重点项目(2013NJMU006)


Application of state space model in forecasting the incidence of hepatitis in China
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    目的:应用状态空间模型对我国甲肝-乙肝-丙肝的月发病率进行拟合和预测,分析预测准确率与发病周期规律的关系,为肝炎发病率的预测提供新方法。方法:对2005—2013年我国甲肝-乙肝-丙肝的月发病率建立状态空间模型,应用MATLAB软件中的SSM工具包对模型进行拟合,并对2014年1—12月的发病率进行预测;通过数据标准化,建立发病率周期规律性评价指标。结果:甲肝-乙肝和丙肝的月发病率预测相对误差的平均值分别为17.03%-6.30%和2.03%,标准化数据周期标准差均值分别为0.214 3-0.195 2和0.172 4。结论:状态空间模型能较好地应用于肝炎发病率的拟合和预测,标准化数据周期评价指标的标准差越小,预测效果越好。

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    Objective:To forecast the monthly incidence of hepatitis A,B and C in China by state space model. To analyze the relationship between the accuracy of prediction and the cycle regularity of the incidence,and to provide a new approach to forecast the incidence of hepatitis. Methods:State space model was fitted with data of monthly reported cases of hepatitis A,B and C in China from 2005 to 2013. The SSM toolbox of MATLAB software was performed to construct the state space model,and the constructed model was applied to predict the monthly incidence of 2014. The evaluation index of the cycle regularity of the incidence was established by standardizing data. Results:The average relative error of prediction of hepatitis A,B and C was 17.03%,6.30% and 2.03%,respectively,and the mean periodic standard deviation of the standard data was 0.2143,0.1952 and 0.1724,respectively. Conclusion:The state space model can be fitted and performed to make a short-term prediction of the incidence of hepatitis. When the periodic standard deviation of the standardized data is smaller,the predicted result is more accurate.

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阮 俊,王 玥,郁婷燕,戚凯莉,陈冠军,丁 勇,吴 静.状态空间模型在我国肝炎发病率预测中的应用[J].南京医科大学学报(自然科学版),2016,(3):380-384

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  • 收稿日期:2015-09-07
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  • 在线发布日期: 2016-03-24
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