摘要
目的 探讨X-12和季节性差分自回归滑动平均模型(seasonal autoregressive integrated moving average, SARIMA)在甘肃省猩红热疫情分析及短期预测中的应用。方法 利用2010-2017年甘肃省猩红热月发病率数据建立SARIMA模型并进行短期预测,运用X-12季节调整法分析疾病流行的季节波动等特征。结果 建立的SARIMA(3,1,1)(1,1,1)_(12)模型参数估计值均有统计学意义,残差为白噪声序列,预测值的精度评价指标和误差衡量指标均符合标准。2010-2018年甘肃省猩红热月发病率存在明显季节波动,季节因子影响6月最大且呈缓慢下降趋势,循环-趋势成分影响呈缓慢上升趋势,不规则因子影响规律平稳。结论 X-12季节调整方法能较好地分析具有一定季节波动和长期趋势传染病的时间变化规律,SARIMA模型对于甘肃省猩红热的短期预测效果较好。
Objective To explore the application of X-12 and seasonal autoregressive integrated moving average(X-12-SARIMA) model to epidemic analysis and short-term prediction of scarlet fever in Gansu Province.Methods Using the monthly incidence data of scarlet fever in Gansu Province from 2010 to 2017,a SARIMA model was established for short-term prediction.X-12 seasonal adjustment method was used to analyze the seasonal fluctuation characteristics of the disease epidemic.Results The estimated values of all parameters in the SARIMA(3,1,1)(1,1,1)_(12)model established were significant in statistics.The residuals were proved to be white-nose series.The accuracy evaluation and error measurement indicators of the predicted value were up to the standards.The monthly incidence rates of scarlet fever in Gansu Province from 2010 to 2018 had obvious seasonal fluctuations.The influence of seasonal factors was most obvious in June and showed a slow decreasing trend,while the influence of cycle-trend factors showed a slow increasing trend.The influence of irregular factors was regular and smooth.Conclusion X-12 seasonal adjustment method is fit for the analysis of time variation of infectious diseases with seasonal fluctuations and long-term trends.The SARIMA model is effective to forecast short-term epidemic level of scarlet fever in Gansu Province.
作者
蒋小娟
刘新凤
成瑶
杨筱婷
JIANG Xiao-juan;LIU Xin-feng;CHENG Yao;YANG Xiao-ting(Gansu Provincial Center for Disease Control and Prevention,Lanzhou,Gansu 730000,China)
出处
《实用预防医学》
CAS
2022年第12期1541-1544,共4页
Practical Preventive Medicine
基金
“十三五”国家科技重大专项“甘肃及周边省区传染病病原谱流行规律研究”课题(2017ZX10103006)
甘肃省卫生行业科研计划项目(GSWKY-2019-67)。
