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10.1016/j.procs.2021.04.092

http://scihub22266oqcxt.onion/10.1016/j.procs.2021.04.092
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suck abstract from ncbi


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pmid34149970      Procedia+Comput+Sci 2021 ; 187 (ä): 512-517
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  • Estimate the Trend of COVID-19 Outbreak in China: a Statistical and Inferential Analysis on Provincial-level Data #MMPMID34149970
  • Li K; Zhang Y; Wang C
  • Procedia Comput Sci 2021[]; 187 (ä): 512-517 PMID34149970show ga
  • The ongoing COVID-19 epidemic spreads with strong transmission power in every part of China. Analyses of the trend is highly need when the Chinese government makes plans and policies on epidemic control. This paper provides an estimation process on the trend of COVID-19 outbreak using the provincial-level data of the confirmed cases. On the basis of the previous studies, we introduce an effective and practical method to compute accurate basic reproduction numbers (R (0) s) in each province-level division of China. The statistical results show a non-stop downward trend of the R (0) s in China, and confirm that China has made significant progress on the epidemic control by lowering the provincial R (0) s from 10 or above to 3.21 or less. In the inferential analysis, we introduce an effective AR(n) model for the trend forecasting. The inferential results imply that the nationwide epidemic risk will fall to a safe level by the end of April in China, which matches the actual situation. The results provide more accurate method and information about COVID-19.
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