Evaluating the Performance of Syndromic Surveillance System using High-fidelity Outbreak Simulations

Authors

  • Tao Tao School of Public Health, Fudan University, Shanghai, China.
  • Qi Zhao School of Public Health, Fudan University, Shanghai, China.
  • Shaofa Nie Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Lars Palm Future Position X (FPX), Gävle, Sweden.
  • Vinod K. Diwan Division of Global Health (IHCAR), Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
  • Biao Xu School of Public Health, Fudan University, Shanghai, China.

DOI:

https://doi.org/10.5210/ojphi.v6i1.5095

Abstract

This study introduced high-fidelity simulations based on real-world outbreaks for evaluating the performance of syndromic surveillance system. Findings showed that ISSC system was capable to detect the 3 disease outbreaks tested at an early stage, but the practical performance was to a great extent affected by the type and magnitude of outbreak event, the selection of syndromic groups for monitoring, the detection algorithm introduced in the system, and the preferred false alarm rate in real-time surveillance.

Author Biography

Tao Tao, School of Public Health, Fudan University, Shanghai, China.

Tao Tao is a senior PhD student at School of Public Health, Fudan University, Shanghai, China. He has participated in many research projects on infectious disease epidemiology and health system research, funded by the WHO, NIH and Chinese government. He is now working as a main researcher in a EU project - 'Integrated Surveillance System in rural China (ISSC)'. His research interests focus on the field implementation and performance evaluation of syndromic surveillance system.

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Published

2014-03-09

How to Cite

Tao, T., Zhao, Q., Nie, S., Palm, L., Diwan, V. K., & Xu, B. (2014). Evaluating the Performance of Syndromic Surveillance System using High-fidelity Outbreak Simulations. Online Journal of Public Health Informatics, 6(1). https://doi.org/10.5210/ojphi.v6i1.5095

Issue

Section

Oral Presentations