id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-328787-r0i3zo6t	Xue, Ling	A data-driven network model for the emerging COVID-19 epidemics in Wuhan, Toronto and Italy	2020-06-01		.txt	text/plain	5327	326	60	The transmission network model was respectively fitted to the reported data for the COVID-19 epidemic in Wuhan (China), Toronto (Canada), and the Italian Republic using a Markov Chain Monte Carlo (MCMC) optimization algorithm. The transmission network model was respectively fitted to the reported data for the COVID-19 epidemic in Wuhan (China), Toronto (Canada), and the Italian Republic using a Markov Chain Monte Carlo (M-CMC) optimization algorithm. Ziff and Ziff analyzed the number of reported cases for Wuhan (China) and showed that the growth of the daily number of confirmed new cases indicates an underlying fractal or small-world network of connections between susceptible and infected individuals [2]. The model then projected the trends of COVID-19 spread by simulating epidemics in the Wuhan, Toronto, and Italy networks. Simulation results showed that personal protection, reducing the node degrees of symptomatically infected individuals, and quarantine of close contacts are effective in reducing the peak epidemic size and final epidemic size.	./cache/cord-328787-r0i3zo6t.txt	./txt/cord-328787-r0i3zo6t.txt