Abstract

BackgroundChina 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.MethodsThe 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.ResultsSix 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.ConclusionsIt 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.

Highlights

  • China Centre for Diseases Control and Prevention (CDC) developed the China Infectious Disease Automated Alert and Response System (CIDARS) in 2005

  • The CIDARS has been integrated into the routine outbreak monitoring efforts of the CDCs at all levels in China [8]

  • Jie Kuang [9] previously reported that the moving percentile method (MPM) was a useful algorithm for outbreak detection

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Summary

Introduction

China Centre for Diseases Control and Prevention (CDC) developed the China Infectious Disease Automated Alert and Response System (CIDARS) in 2005. In order to enhance infectious disease surveillance, the China Centre for Disease Control and Prevention (China CDC) established a webbased Nationwide Notifiable Infectious Diseases Reporting Information System (NIDRIS) in 2004 [5]. According to the Law on Prevention and Control of Infectious Disease in China, all cases of notifiable infectious disease are diagnosed by clinicians in all levels of healthcare institutions using the uniform case definition issued by the Chinese Ministry of Health, and clinicians are obligated to report all diagnosed infectious disease cases through the NIDRIS in real time. In 2005, the China CDC developed the China Infectious Disease Automated-alert and Response System (CIDARS), and the CIDARS was successfully implemented and has become operational nationwide since 2008 [7]. The CIDARS has been integrated into the routine outbreak monitoring efforts of the CDCs at all levels (including the national level, provincial level, municipal level, and county or district level) in China [8]

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