2015—2018年某综合医院儿科流感样病例预警模型的建立与评价  

Construction and evaluation of a predictive model for pediatric cases of influenza-like illness in a comprehensive hospital,2015-2018

作　　者：单旭征[1,2] 陈云 宋瑞宏 黄璜 许春琼[1] 皮仕敏[4] 陈侣林 张鸿彬[1] SHAN Xu-zheng;CHEN Yun;SONG Rui-hong;HUANG Huang;XU Chun-qiong;PI Shi-min;CHEN LYU-lin;ZHANG Hong-bin(The Affiliated Hospital of Chengdu University,Chengdu,Sichuan 610081,China;West China School of Public Health,Sichuan University,Chengdu,Sichuan 610041,China;Xichang Satellite Launch Center,Xichang,Sichuan 615000,China;Jinniu District Center for Disease Control and Prevention,Chengdu,Sichuan 610081,China)

机构地区：[1]成都大学附属医院,四川成都610081 [2]四川大学华西公共卫生学院,四川成都610041 [3]西昌卫星发射中心,四川西昌615000 [4]成都市金牛区疾病预防控制中心,四川成都610081

出　　处：《实用预防医学》2020年第10期1274-1276,共3页Practical Preventive Medicine

基　　金：四川省卫生和计划生育委员会项目(18PJ576)。

摘　　要：目的建立医院流感样病例(influenza-like illness,ILI)监测模型,为控制流感在医疗机构内传播,缩短区域流感流行发现时间提供数据支持。方法数据来源于2015—2018年每年1—6月某三甲综合医院儿科门诊诊疗数据,以2015—2017年每年1—6月流感样病例数为参考值,采用Farrington算法建立预警模型预测2018年1—6月流感样病例数及波动范围,并用2018年1—6月临床诊断流感病例数据评价模型准确性和及时性。结果预警模型以95%置信区间为阈值,超过阈值则发出预警信号。2018年1—6月共发出预警信号26次,其中2018年1月集中发出22次预警信号,流感流行期间出现连续2~5 d的预警信号。预警信号自推后2日时,预警日与非预警日流感病例差异有统计学意义(t=-2.58,P=0.015)。结论Farrington算法适用于医院儿科ILI预警系统的建立,并能比疾病诊断提前预警。Objective To establish a surveillance model for nosocomial cases of influenza-likeness illness(ILI)so as to provide data support for controlling the spread of influenza in medical institutions and shorten the discovery time of onset of influenza epidemics.Methods We collected the data from diagnosis and treatment information of pediatric outpatient department in a comprehensive grade-A tertiary hospital in January-June of each year from 2015 to 2018,and used the number of influenza-like illness(ILI)cases in January-June of each year from 2015 to 2017 as the reference data.An aberration detection model established based on Farrington algorithm was used to predict the number and fluctuation range of ILI cases in January-June,2018,and the accuracy and timeliness of the model were evaluated based on the data about clinically-diagnosed influenza cases in January-June,2018.Results The 95%confidence interval was selected as the threshold value of the aberration detection model,and an alarm signal was issued when exceeding the threshold value.A total of 26 alarm signals were issued in January-June,2018,of which 22 alarm signals were released intensively in January 2018,and alarm signals were issued for 2-5 consecutive days during the influenza epidemics.Since alarm signals were postponed by 2 days,the number of influenza cases showed a statistically significant difference between alarm days and no-alarm days(t=-2.58,P=0.015).Conclusions Farrington algorithm is applicable to the establishment of pediatric ILI aberration detection model in hospital,and can warn earlier than clinical diagnosis.

关 键 词：流感样病例 临床诊断流感病例 Farrington算法 

分 类 号：R511.7[医药卫生—内科学]