About: In this paper, we analyze the real-time infection data of COVID-19 epidemic for 21 nations up to April 20, 2020. We observe that China, South Korea, Australia, Hong Kong, and Switzerland have flattened their infection curves. For these nations, the total number of infected individuals (I(t)) exhibits a succession of exponential growth and power-law growth (t2,t,{surd}t in sequence) before flattening of the curve. USA, Italy, UK, France, Spain, Germany, Belgium, Israel, Netherlands, India, and Sri Lanka have reached up to the linear growth (I(t) [~] t), but they are yet to flatten their curves. Russia and Singapore are still in the exponential growth regime. Such features of I(t) curves could be used for understanding and forecast of the epidemic evolution. Besides this detailed analysis, we compare the predictions of an extended SEIR model and a delay differential equation-based model with the reported infection data, and observed a general agreement between them.   Goto Sponge  NotDistinct  Permalink

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  • In this paper, we analyze the real-time infection data of COVID-19 epidemic for 21 nations up to April 20, 2020. We observe that China, South Korea, Australia, Hong Kong, and Switzerland have flattened their infection curves. For these nations, the total number of infected individuals (I(t)) exhibits a succession of exponential growth and power-law growth (t2,t,{surd}t in sequence) before flattening of the curve. USA, Italy, UK, France, Spain, Germany, Belgium, Israel, Netherlands, India, and Sri Lanka have reached up to the linear growth (I(t) [~] t), but they are yet to flatten their curves. Russia and Singapore are still in the exponential growth regime. Such features of I(t) curves could be used for understanding and forecast of the epidemic evolution. Besides this detailed analysis, we compare the predictions of an extended SEIR model and a delay differential equation-based model with the reported infection data, and observed a general agreement between them.
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  • Differential equations
  • Metropolitan areas of China
  • April observances
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