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[Summary and prospect of early warning models and systems for infectious disease outbreaks].
Lai, S J; Feng, L Z; Leng, Z W; Lyu, X; Li, R Y; Yin, L; Luo, W; Li, Z J; Lan, Y J; Yang, W Z.
  • Lai SJ; World Pop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK.
  • Feng LZ; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
  • Leng ZW; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
  • Lyu X; College of Systems Engineering, National University of Defence Technology, Changsha 410073, China.
  • Li RY; Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo NO-0316, Norway.
  • Yin L; Shenzhen Institute of Advanced Technologies, Chinese Academy of Sciences, Shenzhen 518055, China.
  • Luo W; Geography Department, National University of Singapore, Singapore 117570, Singapore.
  • Li ZJ; Division of Infectious Disease, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
  • Lan YJ; West China School of Public Health, Sichuan University, Chengdu 610041, China.
  • Yang WZ; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Zhonghua Liu Xing Bing Xue Za Zhi ; 42(8): 1330-1335, 2021 Aug 10.
Article in Chinese | MEDLINE | ID: covidwho-1362625
ABSTRACT
This paper summarizes the basic principles and models of early warning for infectious disease outbreaks, introduces the early warning systems for infectious disease based on different data sources and their applications, and discusses the application potential of big data and their analysing techniques, which have been studied and used in the prevention and control of COVID-19 pandemic, including internet inquiry, social media, mobile positioning, in the early warning of infectious diseases in order to provide reference for the establishment of an intelligent early warning mechanism and platform for infectious diseases based on multi-source big data.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Communicable Diseases / COVID-19 Type of study: Observational study Limits: Humans Language: Chinese Journal: Zhonghua Liu Xing Bing Xue Za Zhi Year: 2021 Document Type: Article Affiliation country: Cma.j.cn112338-20210512-00391

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Communicable Diseases / COVID-19 Type of study: Observational study Limits: Humans Language: Chinese Journal: Zhonghua Liu Xing Bing Xue Za Zhi Year: 2021 Document Type: Article Affiliation country: Cma.j.cn112338-20210512-00391