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新型冠状病毒肺炎疫情预测建模、数据融合与防控策略分析

  • Tang Sanyi
  • , Xiao Yanni
  • , Peng Zhihang
  • , Shen Hongbing
  • Shaanxi Normal University
  • Nanjing Medical University

科研成果: 期刊稿件文章同行评审

34 引用 (Scopus)

摘要

Since December 2019, the outbreak of COVID-19 in Wuhan has spread rapidly due to population movement during the Spring Festival holidays. Since January 23rd, 2020, the strategies of containment and contact tracing followed by quarantine and isolation has been implemented extensively in mainland China, and the rates of detection and confirmation have been continuously increased, which have effectively suppressed the rapid spread of the epidemic. In the early stage of the outbreak of COVID-19, it is of great practical significance to analyze the transmission risk of the epidemic and evaluate the effectiveness and timeliness of prevention and control strategies by using mathematical models and combining with a small amount of real-time updated multi-source data. On the basis of our previous research, we systematically introduce how to establish the transmission dynamic models in line with current Chinese prevention and control strategies step by step, according to the different epidemic stages and the improvement of the data. By summarized our modelling and assessing ideas, the model formulations vary from autonomous to non-autonomous dynamic systems, the risk assessment index changes from the basic regeneration number to the effective regeneration number, and the epidemic development and assessment evolve from the early SEIHR transmission model-based dynamics to the recent dynamics which are mainly associated with the variation of the isolated and suspected population sizes.

投稿的翻译标题Prediction modeling with data fusion and prevention strategy analysis for the COVID-19 outbreak
源语言繁体中文
页(从-至)480-484
页数5
期刊Chinese Journal of Epidemiology
41
4
DOI
出版状态已出版 - 2020

关键词

  • COVID-19
  • Dynamical model
  • Reproductive number

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