方益荣, 牛文柯, 卢巧玲, 孙佳美, 张丽杰. 应用移动平均法预警学校结核病疫情的分析[J]. 疾病监测, 2017, 32(5): 418-422. DOI: 10.3784/j.issn.1003-9961.2017.05.016
引用本文: 方益荣, 牛文柯, 卢巧玲, 孙佳美, 张丽杰. 应用移动平均法预警学校结核病疫情的分析[J]. 疾病监测, 2017, 32(5): 418-422. DOI: 10.3784/j.issn.1003-9961.2017.05.016
FANG Yi-rong, NIU Wen-ke, LU Qiao-ling, SUN Jia-mei, ZHANG Li-jie. Study on early warning for tuberculosis outbreaks in school using moving average method[J]. Disease Surveillance, 2017, 32(5): 418-422. DOI: 10.3784/j.issn.1003-9961.2017.05.016
Citation: FANG Yi-rong, NIU Wen-ke, LU Qiao-ling, SUN Jia-mei, ZHANG Li-jie. Study on early warning for tuberculosis outbreaks in school using moving average method[J]. Disease Surveillance, 2017, 32(5): 418-422. DOI: 10.3784/j.issn.1003-9961.2017.05.016

应用移动平均法预警学校结核病疫情的分析

Study on early warning for tuberculosis outbreaks in school using moving average method

  • 摘要: 目的 建立学校结核病预警模型,以便及时发现浙江省绍兴市学校结核病聚集性/暴发疫情。方法 从《结核病管理信息系统》收集2010-2015年绍兴市学校每半月报告结核病病例数,以半月顺序号(1~144)为自变量,报告病例数为因变量,获得回归方程。再以回归方程得到每半月(1~144)的模拟病例数,计算1~24个半月的残差、残差移动平均、残差标准差。根据实际病例数,分别以x +1.0s、x +1.6s、x +2.0s作为预警线,建立预警图。结果 获得回归方程y=-0.014x+6.34。每半个月的模拟发病数的移动平均残差的标准差分别为3.26、2.11、2.13、2.31、3.88、4.22、 4.02、 3.84、3.90、3.03、2.34、2.21、2.07、2.19、2.08、2.21、2.32、2.43、2.63、2.41、 3.11、3.19、3.46和3.23。2010-2015年,绍兴市共发生结核病暴发疫情3起,聚集性疫情Ⅱ级7起,聚集性疫情Ⅲ级14起。预警模型预警结核病暴发疫情、聚集性疫情Ⅱ级和聚集性疫情Ⅲ级灵敏度和特异度分别为100%、 98.61%; 100%、 99.30%; 71.43%、 99.30%。结论 利用移动平均方法建立的预警模型有助于发现学校结核病疫情。

     

    Abstract: Objective To establish an early warning model of tuberculosis (TB) for the early detection of epidemic of TB in schools in Shaoxing. Methods The semimonthly reported TB cases in schools in Shaoxing from 2010 to 2015 were collected from Tuberculosis Information Management System. The semimonthly serial number of TB cases in schools from 2010 to 2015 (1-144) were used as independent variable and the semimonthly reported cases of TB were used as dependent variable, then the regression equation was established. According to this regression equation, the semimonthly simulated cases, residual, average moving residual, standard deviation of residual were calculated. According to the characteristics of infectious diseases, x +1.0s, x +1.6s, x +2.0s of warning values were used as the alert thresholds respectively for grade Ⅲ TB cluster (case number 2 within 3 months), gradeⅡTB cluster (case number 6 within 3 months) and TB outbreak(case number 10 within a semester). Results The established regression equation was y=-0.014x+6.34. The average moving residual of semimonthly simulated cases from 2010 to 2015 were 3.26, 2.11, 2.13, 2.31, 3.88, 4.22, 4.02, 3.84, 3.90, 3.03, 2.34, 2.21, 2.07, 2.19, 2.08, 2.21, 2.32, 2.43, 2.63, 2.41, 3.11, 3.19, 3.46 and 3.23 respectively. Fourteen TB cluster Ⅲ grade, 7 TB cluster Ⅱ grade and 3TB outbreak occurred in school in shaoxing from 2010 to 2015. The sensitivity and specificity of early warning model for TB outbreak,TB cluster Ⅱgrade and TB cluster Ⅲ grade were 100%, 98.61%; 100%, 99.30%; 71.43%, 99.30% respectively. Conclusion The early warning models established by use moving average method is helpful for the early detection of TB epidemic in schools.

     

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