Covid-19 spread: Reproduction of data and prediction using a SIR model on Euclidean network.
@article{Biswas2020Covid19SR, title={Covid-19 spread: Reproduction of data and prediction using a SIR model on Euclidean network.}, author={Kathakali Biswas and Abdul Khaleque and Parongama Sen}, journal={arXiv: Physics and Society}, year={2020} }
We study the datafor the cumulative as well as daily number of cases in the Covid-19 outbreak in China. The cumulative data can be fit to an empirical form obtained from a Susceptible-Infected-Removed (SIR) model studied on an Euclidean network previously. Plotting the number of cases against the distance from the epicenter for both China and Italy, we find an approximate power law variation with an exponent $\sim 1.85$ showing strongly that the spatial dependence plays a key role, a factor…
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