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Assessing the Global Tendency of COVID-19 Outbreak
Qinghe Liu; Zhicheng Liu; Junkai Zhu; Yuhao Zhu; Deqiang Li; Zefei Gao; Liuling Zhou; Yuanbo Tang; Xiang Zhang; Junyan Yang; Qiao Wang.
Affiliation
  • Qinghe Liu; Southeast University, China
  • Zhicheng Liu; Southeast University, China
  • Junkai Zhu; Southeast University, China
  • Yuhao Zhu; Erasmus University Rotterdam, Rotterdam, the Netherlands
  • Deqiang Li; Southeast University, China
  • Zefei Gao; Southeast University, China
  • Liuling Zhou; Southeast University, China
  • Yuanbo Tang; Southeast University, School of Information Science and Engineering
  • Xiang Zhang; Southeast University
  • Junyan Yang; Southeast University, China
  • Qiao Wang; Southeast University
Preprint in English | medRxiv | ID: ppmedrxiv-20038224
ABSTRACT
COVID-19 is now widely spreading around the world as a global pandemic. In this report, we estimated the global tendency of COVID-19 and analyzed the associated global epidemic risk, given that the status quo is continued without further measures being taken. Based on official data of confirmed and recovered cases until May 21, 2020, the results showed that the global R0, excluding China, was estimated to be 2.76 (95% CI 2.57 - 2.95). The United States, Germany, Italy, and Spain have peak values over 100,000. Using dynamical model and cluster analysis, we partition the globe into four regional epicenters of the outbreak Southeast Asia extending southward to Oceania, the Middle East, Western Europe, and North America. Among them, Western Europe would become the major center of the outbreak. The peak values in Germany, Italy, and Spain were estimated to be 228,000, 291,000, and 298,000, respectively. Based on the current control measures by May 21, 2020, the peak value in the United States will reach 2,114,000. The cumulative number of 51 mainly researched countries patients might finally attain 6,542,000 (95% CI 4,772,000 - 40,735,000). We also estimated the diagnosis rate, recovery rate, and infection degree of each country or region, and used clustering algorithm to retrieve countries or regions with similar epidemic characteristics. Several suggestions have been proposed for countries or regions in different clusters.
License
cc_by_nd
Full text: Available Collection: Preprints Database: medRxiv Type of study: Observational study / Prognostic study Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Observational study / Prognostic study Language: English Year: 2020 Document type: Preprint
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