基于季节趋势模型预测2018—2019年流行性感冒的发病情况

Predicting morbidity of influenza in 2018-2019 based on seasonal trend model

目的分析2011—2017年《中华人民共和国国家卫生与计划生育委员会公报》公布的全国大陆地区流行性感冒发病例数,利用季节趋势模型预测2018—2019年流行性感冒的发病情况。方法收集、整理2011—2017年《中华人民共和国国家卫生与计划生育委员会公报》公布的我国历年流行性感冒逐月发病例数。以每年3—5月为一季度,6—8月为二季度,9—11月为三季度,12月至次年2月为四季度,按季度统计发病例数。应用Excel建立数据库,采用SPSS 22.0统计软件进行统计分析。结果建立季节趋势模型:Yt=(11 682.860+2 732.491t) S,其中t为季序,S为各季度所对应的调整季节指数。方差分析显示回归方程具有统计学意义(F=19.855,P<0.001)。预测结果显示2018—2019年各季度流行性感冒发病例数分别为:110 928,73 053,66 509,135 798,110 011,72 466,65 990,150 772例。结论 2018—2019年流行性感冒发病例数继续保持增长的趋势,提示有关部门应继续加强对流行性感冒的监测力度,采取应对流行性感冒高发的相关措施。

Objective To analyze the incident cases of influenza in China's Mainland published in "National Health and Family Planning Commission of PRC Gazette"in 2011-2017,and further to predict the morbidity of influenza in 2018-2019 using seasonal trend model. Methods We collected and sorted out the monthly data of incident cases of influenza in China in 2011-2017,published in "National Health and Family Planning Commission of PRC Gazette". Each year was divided into quarters( Q) including March to May as Q1,June to August as Q2,September to November as Q3,and December to February as Q4. The statistics of the incident cases were kept by the quarter. Data was input in Excel and analyzed with SPSS 22.0. Results The seasonal trend model was established:Yt =( 11 682.860+2 732.491 t) S,among it t stood for sequence of Q,and S stood for adjustment index corresponding to each Q. Anova showed that the regression equation had statistical significance( F = 19.855,P<0.001). The predictive incident cases in every quarter in 2018-2019 were 110 928,73 053,66 509,135 798,110 011,72 466,65 990 and 150 772,respectively. Conclusion The incident cases of influenza in 2018-2019 generally maintain a high growing trend,which suggests that the authorities concerned should continue to strengthen the surveillance of it,and take relevant measures to cope with it.