Abstract
We analyse the data for the global corona virus (COVID-19) outbreak using the results of a previously studied Susceptible-Infected-Removed (SIR) model of epidemic spreading on Euclidean networks. We also directly study the correlation of the distance from the epicenter and the number of cases. An inverse square law is seen to exist approximately. The studies are made for China and the rest of the world separately.
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