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《MedRxiv，3月10日，Prediction of COVID-19 Spreading Profiles in South Korea, Italy and Iran by Data-Driven Coding》

  • 来源专题：COVID-19科研动态监测
  • 编译者： zhangmin
  • 发布时间：2020-03-11

  • Prediction of COVID-19 Spreading Profiles in South Korea, Italy and Iran by Data-Driven Coding

    Choujun Zhan, Chi K. Tse, Zhikang Lai, Tianyong Hao, Jingjing Su

    doi: https://doi.org/10.1101/2020.03.08.20032847

    Abstract

    This work applies a data-driven coding method for prediction of the COVID-19 spreading profile in any given population that shows an initial phase of epidemic progression. Based on the historical data collected for COVID-19 spreading in 367 cities in China and the set of parameters of the augmented Susceptible-Exposed-Infected-Removed (SEIR) model obtained for each city, a set of profile codes representing a variety of transmission mechanisms and contact topologies is formed. By comparing the data of an early outbreak of a given population with the complete set of historical profiles, the best fit profiles are selected and the corresponding sets of profile codes are used for prediction of the future progression of the epidemic in that population.

    *注，本文为预印本论文手稿，是未经同行评审的初步报告，其观点仅供科研同行交流，并不是结论性内容，请使用者谨慎使用.

  • 原文来源：https://www.medrxiv.org/content/10.1101/2020.03.08.20032847v1
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