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《 MedRxiv，2月18日，Can Search Query Forecast successfully in China's 2019-nCov pneumonia?》

  • 来源专题：COVID-19科研动态监测
  • 编译者： xuwenwhlib
  • 发布时间：2020-02-19

  • Can Search Query Forecast successfully in China's 2019-nCov pneumonia?

    Li Xiaoxuan, Wu Qi, Lv Benfu

    doi: https://doi.org/10.1101/2020.02.12.20022400

    Abstract

    Recently the novel coronavirus (2019-nCov) pneumonia outbreak in China then the world, and the Number of infections and death continues to increases. Search Query performs well in forecasting the epidemics. It is still a question whether search engine data can forecast the drift and the inflexion in 2019-nCov pneumonia. Based on the Baidu Search Index, we propose three prediction models: composite Index, composite Index with filtering and suspected NCP(Novel Coronavirus Pneumonia). The result demonstrates that the predictive model of composite index with filtering performs the best while the model of suspected NCP has the highest forecast error. We further predict the out-of-the-set NCP confirmed cases and monitor that the next peak of new diagnoses will occur on February 16th and 17th.

    *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/10.1101/2020.02.12.20022400v1
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    • 来源专题：COVID-19科研动态监测
    • 编译者：zhangmin
    • 发布时间：2020-02-20
    • Can Search Query Forecast successfully in China's 2019-nCov pneumonia? Li Xiaoxuan, Wu Qi, Lv Benfu doi: https://doi.org/10.1101/2020.02.12.20022400 Abstract Recently the novel coronavirus (2019-nCov) pneumonia outbreak in China then the world, and the Number of infections and death continues to increases. Search Query performs well in forecasting the epidemics. It is still a question whether search engine data can forecast the drift and the inflexion in 2019-nCov pneumonia. Based on the Baidu Search Index, we propose three prediction models: composite Index, composite Index with filtering and suspected NCP(Novel Coronavirus Pneumonia). The result demonstrates that the predictive model of composite index with filtering performs the best while the model of suspected NCP has the highest forecast error. We further predict the out-of-the-set NCP confirmed cases and monitor that the next peak of new diagnoses will occur on February 16th and 17th. *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.
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  • 《MedRxiv，2月18日，Risk map of the novel coronavirus (2019-nCoV) in China: proportionate control is needed》
    • 来源专题：COVID-19科研动态监测
    • 编译者：xuwenwhlib
    • 发布时间：2020-02-19
    • Risk map of the novel coronavirus (2019-nCoV) in China: proportionate control is needed Xinhai Li, Xumao Zhao, Yingqiang Lou, Yuehua Sun doi: https://doi.org/10.1101/2020.02.16.20023838 Abstract Background China is running a national level antivirus campaign against the novel coronavirus (2019-nCoV). Strict control measures are being enforced in either the populated areas and remote regions. While the virus is closed to be under control, tremendous economic loss has been caused. Methods and findings We assessed the pandemic risk of 2019-nCoV for all cities/regions in China using the random forest algorithm, taking into account the effect of five factors: the accumulative and increased numbers of confirmed cases, total population, population density, and GDP. We defined four levels of the risk, corresponding to the four response levels to public health emergencies in China. The classification system has good consistency among cities in China, as the error rate of the confusion matrix is 1.58%. Conclusions The pandemic risk of 2019-nCoV is dramatically different among the 442 cities/regions. We recommend to adopt proportionate control policy according to the risk level to reduce unnecessary economic loss. *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.
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