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浙江省传染病自动预警系统暴发预警效果评价

浙江省传染病自动预警系统暴发预警效果评价
浙江省传染病自动预警系统暴发预警效果评价

To evaluate the performance of China Infectious Disease Automated-alert and Response System (CIDARS). A retrospective analysis was conducted on data related to the warning signals, the outcome of signal verification, the field investigation of CIDARS, and the emergent events reported through Public Health Emergency Events Surveillance System from July 1, 2008 to June 30, 2010 in Zhejiang province. The performance of CIDARS was qualitatively evaluated by indicators on its sensitivity and rate of false alarm. In total, 26 446 signals were generated by the system which involving 17 diseases, with an average of 2.83 signals per country per week. Among all the signals, 99.95% of them were responded. 0.90% of the signals were judged as suspected events via the preliminary verification, and 30 outbreaks were finally confirmed by field investigation. The sensitivity of the system was 69.77% with the false alarm rate as 1.39%. The system seemed to have worked on the outbreak early warning of infectious diseases and could directly reflect the anomaly event emerged from the infectious disease reporting system. However, more efforts should be paid to the following areas as how to decrease the false positive signals, select suitable thresholds and increase the quality of data in order to enhance the accuracy of the system.

0254-6450
442-445
Xu, Xu Qing
a8ed7598-8906-4bd7-ace5-ec0704f0ca8e
Lu, Qin Bao
7986142c-1ee8-4a02-b154-6a578dac2d31
Wang, Zhen
964f3b2e-0c55-4cf4-add6-6fc7afb8fbdd
Lai, Sheng Jie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Li, Zhong Jie
8c060065-5459-449e-a776-29d55614adb7
Xu, Xu Qing
a8ed7598-8906-4bd7-ace5-ec0704f0ca8e
Lu, Qin Bao
7986142c-1ee8-4a02-b154-6a578dac2d31
Wang, Zhen
964f3b2e-0c55-4cf4-add6-6fc7afb8fbdd
Lai, Sheng Jie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Li, Zhong Jie
8c060065-5459-449e-a776-29d55614adb7

Xu, Xu Qing, Lu, Qin Bao, Wang, Zhen, Lai, Sheng Jie and Li, Zhong Jie (2011) 浙江省传染病自动预警系统暴发预警效果评价. Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi, 32 (5), 442-445. (doi:10.3760/cma.j.issn.0254-6450.2011.05.004).

Record type: Article

Abstract

To evaluate the performance of China Infectious Disease Automated-alert and Response System (CIDARS). A retrospective analysis was conducted on data related to the warning signals, the outcome of signal verification, the field investigation of CIDARS, and the emergent events reported through Public Health Emergency Events Surveillance System from July 1, 2008 to June 30, 2010 in Zhejiang province. The performance of CIDARS was qualitatively evaluated by indicators on its sensitivity and rate of false alarm. In total, 26 446 signals were generated by the system which involving 17 diseases, with an average of 2.83 signals per country per week. Among all the signals, 99.95% of them were responded. 0.90% of the signals were judged as suspected events via the preliminary verification, and 30 outbreaks were finally confirmed by field investigation. The sensitivity of the system was 69.77% with the false alarm rate as 1.39%. The system seemed to have worked on the outbreak early warning of infectious diseases and could directly reflect the anomaly event emerged from the infectious disease reporting system. However, more efforts should be paid to the following areas as how to decrease the false positive signals, select suitable thresholds and increase the quality of data in order to enhance the accuracy of the system.

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More information

Published date: 1 January 2011
Alternative titles: Evaluation on the performance of China Infectious Disease Automated-alert and Response System (CIDARS) in Zhejiang province

Identifiers

Local EPrints ID: 429186
URI: http://eprints.soton.ac.uk/id/eprint/429186
ISSN: 0254-6450
PURE UUID: 7b86db61-74ce-444e-a2c3-00910f6ce2e7
ORCID for Sheng Jie Lai: ORCID iD orcid.org/0000-0001-9781-8148

Catalogue record

Date deposited: 22 Mar 2019 17:30
Last modified: 06 Jun 2024 02:03

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Contributors

Author: Xu Qing Xu
Author: Qin Bao Lu
Author: Zhen Wang
Author: Sheng Jie Lai ORCID iD
Author: Zhong Jie Li

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