肖正斌, 陈恺韵, 任宏, 王琳, 潘启超. 2005—2019年戊型肝炎季节性流行特征及时间序列分析[J]. 上海预防医学, 2021, 33(10): 923-928. DOI: 10.19428/j.cnki.sjpm.2021.20817
引用本文: 肖正斌, 陈恺韵, 任宏, 王琳, 潘启超. 2005—2019年戊型肝炎季节性流行特征及时间序列分析[J]. 上海预防医学, 2021, 33(10): 923-928. DOI: 10.19428/j.cnki.sjpm.2021.20817
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XIAO Zheng-bin, CHEN Kai-yun, REN Hong, WANG Lin, PAN Qi-chao. Seasonal characteristics and time series analysis of hepatitis E in Shanghai from 2005 to 2019[J]. Shanghai Journal of Preventive Medicine, 2021, 33(10): 923-928. DOI: 10.19428/j.cnki.sjpm.2021.20817
Citation: XIAO Zheng-bin, CHEN Kai-yun, REN Hong, WANG Lin, PAN Qi-chao. Seasonal characteristics and time series analysis of hepatitis E in Shanghai from 2005 to 2019[J]. Shanghai Journal of Preventive Medicine, 2021, 33(10): 923-928. DOI: 10.19428/j.cnki.sjpm.2021.20817
shu

2005—2019年戊型肝炎季节性流行特征及时间序列分析

Seasonal characteristics and time series analysis of hepatitis E in Shanghai from 2005 to 2019

    摘要
  • 摘要:
    目的分析上海市2005—2019年戊型病毒性肝炎（戊肝）季节性特征及发病趋势，为上海市戊肝的防治工作提供数据依据。
    方法运用圆形分步法分析2005—2019年上海市戊肝发病的季节性特征，运用自回归移动平均模型（ARIMA）分析戊肝的发病趋势。
    结果上海市2005—2019年戊肝发病高峰日在2月27日，高峰期为次年11月17号至6月9日。时间序列显示最优模型为SARIMA（0，1，1）×（0，1，1）12，Akaike信息标准值（AIC）和Schwartz贝叶斯标准值（SBC）分别为1 243.799和1 250.035，残差为白噪声序列，平均绝对百分比误差（MAPE）为20.253%，预测显示2020—2021年的戊肝发病数较2019年略有下降，但依然处于较高水平。
    结论上海市戊肝发病有较强的季节性特征，应在流行高峰期前做好健康宣教和防控措施。短期预测戊肝的发病数仍然较高，需制订有效的防控策略，积极采取措施。

     

    Abstract:
    ObjectiveTo analyze the seasonal characteristics and incidence trend of hepatitis E from 2005 to 2019 in Shanghai， and provide references for the prevention and treatment of hepatitis E.
    MethodsThe seasonal characteristics of hepatitis E in Shanghai from 2005 to 2019 were analyzed by circular distribution method. The incidence trend of hepatitis E was analyzed by ARIMA （autoregressive moving average model）.
    ResultsThe peak period of hepatitis E in Shanghai from 2005 to 2019 was from November 17 to June 9， and the peak day was on February 27. The time series shows that the optimal model is SARIMA（0，1，1）×（0，1，1）12， Akaike information criterion（AIC） and Schwartz Bayesian information criterion （SBC） are 1 243.799 and 1 250.035 respectively， and the residual is white noise sequence. The mean absolute percentage error（MAPE）between the predicted value， and the actual value of this model is 20.253%. The forecast shows a slight decrease in the number of cases of hepatitis E in 2020-2021 compared with 2019， but it is still at a high level.
    ConclusionThe incidence of hepatitis E in Shanghai shows a solid seasonal characteristic. Health education and prevention/control measures should be conducted well before the epidemic peak. Based on the short-term prediction， the incidence of hepatitis E would still be high. Effective prevention and control strategies should be developed， and active measures should be taken.

     

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