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Stochastic Network Models for Epidemiology—Application to COVID-19 Pandemic

We investigate the effects of network topology and the stochasticity in mixing processes of populations to analyze the epidemiological evolution of COVID-19 pandemic. While our preliminary results have been encouraging, more detailed comparisons of the hereby modeled outcomes with some characterized data from Europe and China will imply how appropriate our approach is and what modeling strategies might be necessary.


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