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An Online Real-Time System to Detect Risk for Infectious Diseases and Provide Early Alert

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Intelligence and Security Informatics (PAISI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 6749))

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Abstract

The purpose of this research was to design and develop an online real-time system to detect risk for infectious diseases and provide an early alert to improve the ability to deal with epidemics. The system is composed of report submission module for collecting data through web form, a report reception module for delivering real-time epidemic intelligence on emerging infectious diseases for a diverse audience, and an epidemic early alert module suggests an approach for detecting an epidemic outbreak at an early stage through time and spatial analysis. Advanced data analysis on the data may detect predominant numbers of incidences, indicating a possible outbreak. This gives the health authorities the possibilities to take actions to limit the outbreak and its consequences for all the inhabitants in an affected area. In field experiments, the system has been proven to be of substantial value in visualizing the epidemic data and perceiving the infectious diseases out-break.

This work was supported by Ministry of Health of the People’s Republic of China(Grant No. 2009ZX10004-315 and 2008ZX10005-013), Chinese Academy of Sciences(Grant No. 2F070C01 and 2F08N03), and National Natural Science Foundation of China(Grant No. 71050001, 90924302, 60621001, 40901219 and 91024030).

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Author information

Authors and Affiliations

  1. Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, No.95, ZhongGuanCun East Road, HaiDian District, 100190, Beijing, China

    Liang Fang & Zhidong Cao

  2. University of Science and Technolgoy of China, No.96, Jinzhai Road, Hefei, Anhui Province, 230026, China

    Liang Fang

Authors
  1. Liang Fang
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  2. Zhidong Cao
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Editor information

Editors and Affiliations

  1. The University of Hong Kong, 7/F Meng Wah Complex, Pokfulam, Hong Kong

    Michael Chau

  2. Virginia Tech, 1007 Pamplin Hall, 24061, Blacksburg, VA, USA

    G. Alan Wang

  3. Chinese Academy of Sciences, Beijing, China

    Xiaolong Zheng , Daniel Zeng  & Wenji Mao ,  & 

  4. The University of Arizona, Tucson, AZ, USA

    Hsinchun Chen

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© 2011 Springer-Verlag Berlin Heidelberg

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Fang, L., Cao, Z. (2011). An Online Real-Time System to Detect Risk for Infectious Diseases and Provide Early Alert. In: Chau, M., Wang, G.A., Zheng, X., Chen, H., Zeng, D., Mao, W. (eds) Intelligence and Security Informatics. PAISI 2011. Lecture Notes in Computer Science, vol 6749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22039-5_11

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  • DOI: https://doi.org/10.1007/978-3-642-22039-5_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22038-8

  • Online ISBN: 978-3-642-22039-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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