如何基于中国传染病自动预警与响应系统（CIDARS）选择合适的早期预警阈值以检测传染病暴发。

How to select a proper early warning threshold to detect infectious disease outbreaks based on the China infectious disease automated alert and response system (CIDARS).

作者信息

Wang Ruiping, Jiang Yonggen, Michael Engelgau, Zhao Genming

机构信息

School of Public Health, Fudan University, NO. 130 Dong-An Road, Shanghai, 200032, China.

Songjiang Center for Disease Control and Prevention, Shanghai, China.

出版信息

BMC Public Health. 2017 Jun 12;17(1):570. doi: 10.1186/s12889-017-4488-0.

DOI:10.1186/s12889-017-4488-0

PMID:28606078

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5468940/

Abstract

BACKGROUND

China Centre for Diseases Control and Prevention (CDC) developed the China Infectious Disease Automated Alert and Response System (CIDARS) in 2005. The CIDARS was used to strengthen infectious disease surveillance and aid in the early warning of outbreak. The CIDARS has been integrated into the routine outbreak monitoring efforts of the CDC at all levels in China. Early warning threshold is crucial for outbreak detection in the CIDARS, but CDCs at all level are currently using thresholds recommended by the China CDC, and these recommended thresholds have recognized limitations. Our study therefore seeks to explore an operational method to select the proper early warning threshold according to the epidemic features of local infectious diseases.

METHODS

The data used in this study were extracted from the web-based Nationwide Notifiable Infectious Diseases Reporting Information System (NIDRIS), and data for infectious disease cases were organized by calendar week (1-52) and year (2009-2015) in Excel format; Px was calculated using a percentile-based moving window (moving window [5 week*5 year], x), where x represents one of 12 centiles (0.40, 0.45, 0.50….0.95). Outbreak signals for the 12 Px were calculated using the moving percentile method (MPM) based on data from the CIDARS. When the outbreak signals generated by the 'mean + 2SD' gold standard were in line with a Px generated outbreak signal for each week during the year of 2014, this Px was then defined as the proper threshold for the infectious disease. Finally, the performance of new selected thresholds for each infectious disease was evaluated by simulated outbreak signals based on 2015 data.

RESULTS

Six infectious diseases were selected in this study (chickenpox, mumps, hand foot and mouth diseases (HFMD), scarlet fever, influenza and rubella). Proper thresholds for chickenpox (P75), mumps (P80), influenza (P75), rubella (P45), HFMD (P75), and scarlet fever (P80) were identified. The selected proper thresholds for these 6 infectious diseases could detect almost all simulated outbreaks within a shorter time period compared to thresholds recommended by the China CDC.

CONCLUSIONS

It is beneficial to select the proper early warning threshold to detect infectious disease aberrations based on characteristics and epidemic features of local diseases in the CIDARS.

摘要

背景

中国疾病预防控制中心（CDC）于2005年开发了中国传染病自动预警与响应系统（CIDARS）。CIDARS用于加强传染病监测并辅助疫情早期预警。CIDARS已整合到中国各级CDC的常规疫情监测工作中。预警阈值对于CIDARS中的疫情检测至关重要，但各级CDC目前使用的是中国CDC推荐的阈值，而这些推荐阈值存在公认的局限性。因此，我们的研究旨在探索一种根据当地传染病流行特征选择合适预警阈值的操作方法。

方法

本研究使用的数据从基于网络的全国法定传染病报告信息系统（NIDRIS）中提取，传染病病例数据按日历周（1 - 52）和年份（2009 - 2015）以Excel格式整理；使用基于百分位数的移动窗口（移动窗口[5周*5年]，x）计算Px，其中x代表12个百分位数（0.40、0.45、0.50…0.95）之一。基于CIDARS的数据，使用移动百分位数法（MPM）计算这12个Px的疫情信号。当“均值 + 2标准差”金标准产生的疫情信号与2014年各周由某个Px产生的疫情信号一致时，这个Px就被定义为该传染病的合适阈值。最后，基于2015年的数据，通过模拟疫情信号评估为每种传染病新选择的阈值的性能。