id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-320912-jfeu4tho	Fukui, M.	Power Laws in Superspreading Events: Evidence from Coronavirus Outbreaks and Implications for SIR Models	2020-06-12		.txt	text/plain	11777	786	59	This paper documents evidence from recent coronavirus outbreaks, including SARS, MERS, and COVID-19, that SSEs follow a power law distribution with fat tails, or infinite variance. We then extend an otherwise standard SIR model with estimated power law distributions, and show that idiosyncratic uncertainties in SSEs will lead to large aggregate uncertainties in infection dynamics, even with large populations. . https://doi.org/10.1101/2020.06.11.20128058 doi: medRxiv preprint Figure 3 plots the predicted ranking of infection cases given the estimated negative binomial (NB) distribution, in addition to the log-log plots and estimated power law (PL) distributions. The mean is set to the same value as power law case, R 0 = 2.5, Figure 4a shows 10 sample paths of infected population generated through the simulation of the model with α = 1.1.	./cache/cord-320912-jfeu4tho.txt	./txt/cord-320912-jfeu4tho.txt