基于季节趋势模型预测2018—2019年流行性感冒的发病情况
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摘要
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 mainland China 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.
Objective To analyze the incident cases of influenza in mainland China 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.
引文
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[12]张春涛,任曲.中国流行性感冒流行病学及疾病负担浅析[J].中国病毒病杂志,2013,3(6):423-427.
[2]王喜民.流行性感冒的预防与治疗[J].中国实用医药,2011,6(4):240-241.
[3]李立,赵静,姜帆,等.流行性感冒中医药预防方法概况[J].中国中医基础医学杂志,2015,21(8):1055-1058.
[4]王旭,马可佳,江云飞,等.流行性感冒病毒的微生物检验[J].中国微生物标准管理,2016,7(7):157-158.
[5]孙波.流行性感冒危害及接种流行性感冒疫苗的研究[J].中国卫生产业,2016(4):76-78.
[6]代丽丽.国家卫计委回应:为何今年流感最凶猛[N].北京晚报,2018-01-10(06).
[7]周密,李雷雷,毛晨梅,等.今年我国流感流行的深度解析[J].中华医院感染杂志,2018,28(4):631-635.
[8]国家卫生和计划生育委员会.流行性感冒诊疗方案(2018年版)[J].中国病毒病杂志,2018,8(3):391-393.
[9]国家卫生健康委员会.2011—2017年中华人民共和国国家健康委员会公报[EB/OL].[2018-03-24]. http://www.nhfpc.gov.cn/zwgk/gongb/ejlist.shtml.
[10]孙玉英.应用季节趋势模型对儿童呼吸系统住院患者的分析[J].中国卫生统计,2007,24(3):327-328.
[11]马俐,王燕庆.应用季节模型预测医院门诊人次[J].中国病案,2012,13(11):48-49.
[12]张春涛,任曲.中国流行性感冒流行病学及疾病负担浅析[J].中国病毒病杂志,2013,3(6):423-427.