Selected article for: "epidemiological model and trend predict"

Author: Qinghe Liu; Zhicheng Liu; Junkai Zhu; Yuhao Zhu; Deqiang Li; Zefei Gao; Liuling Zhou; Junyan Yang; Qiao Wang
Title: Assessing the Global Tendency of COVID-19 Outbreak
  • Document date: 2020_3_20
  • ID: adcptyfj_7
    Snippet: On March 8, 2020, Zhang Z et al [10] , applied a data-driven coding method for the prediction of the global spreading epidemic of COVID-19. Based on the historical epidemiological data and the sets of parameters of augmented SEIR model in 367 cities of China, they selected the best fit profiles to predict the trend of epidemic with any population by comparing the given an early epidemic and the historical profiles. In their study, the peaks of in.....
    Document: On March 8, 2020, Zhang Z et al [10] , applied a data-driven coding method for the prediction of the global spreading epidemic of COVID-19. Based on the historical epidemiological data and the sets of parameters of augmented SEIR model in 367 cities of China, they selected the best fit profiles to predict the trend of epidemic with any population by comparing the given an early epidemic and the historical profiles. In their study, the peaks of infectious cases in South Korea, Italy, and Iran are expected to occur at the end of March, and the percentages of population infectious will less than 0.01%, 0.05% and 0.02%, respectively.

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