Abstract
AbstractIn this paper, we analyze the real-time infection data of COVID-19 epidemic for nine nations. Our analysis is up to 7 April 2020. For China and South Korea, who have already flattened their infection curves, the number of infected individuals (I(t)) exhibits power-law behavior before flattening of the curve. Italy has transitioned to the power-law regime for some time. For the other six nations—USA, Spain, Germany, France, Japan, and India—a power-law regime is beginning to appear after exponential growth. We argue that the transition from an exponential regime to a power-law regime may act as an indicator for flattening of the epidemic curve. We also argue that long-term community transmission and/or the transmission by asymptomatic carriers traveling long distances may be inducing the power-law growth of the epidemic.
Publisher
Cold Spring Harbor Laboratory
Reference24 articles.
1. WorldOMeter. URL https://www.worldometers.info/coronavirus/
2. Johns Hopkins University, Corona Resource Center (2020). URL https://coronavirus.jhu.edu/map.html
3. A contribution to the mathematical theory of epidemics
4. O.N. Bjørnstad , Epidemics: Models and Data using R (Springer, 2018)
5. D.J. Daley , J. Gani , Epidemic Modelling: An Introduction (Cambridge University Press, 2001)
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