Construction and evaluation of a predictive model for pediatric cases of influenza-like illness in a comprehensive hospital, 2015-2018
SHAN Xu-zheng1,2, CHEN Yun3, SONG Rui-hong1, HUANG Huang1, XU Chun-qiong1, PI Shi-min4, CHEN LYU-lin1, ZHANG Hong-bin1
1. The Affiliated Hospital of Chengdu University, Chengdu, Sichuan 610081, China; 2. West China School of Public Health, Sichuan University, Chengdu, Sichuan 610041, China; 3. Xichang Satellite Launch Center, Xichang, Sichuan 615000, China; 4. Jinniu District Center for Disease Control and Prevention, Chengdu, Sichuan 610081, China
Abstract：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.
单旭征, 陈云, 宋瑞宏, 黄璜, 许春琼, 皮仕敏, 陈侣林, 张鸿彬. 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[J]. 实用预防医学, 2020, 27(10): 1274-1276.
SHAN Xu-zheng, CHEN Yun, SONG Rui-hong, HUANG Huang, XU Chun-qiong, PI Shi-min, CHEN LYU-lin, ZHANG Hong-bin. Construction and evaluation of a predictive model for pediatric cases of influenza-like illness in a comprehensive hospital, 2015-2018. , 2020, 27(10): 1274-1276.
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2020, Vol. 27 
