id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-241057-cq20z1jt	Han, Jungmin	Statistical Physics of Epidemic on Network Predictions for SARS-CoV-2 Parameters	2020-07-06		.txt	text/plain	3012	155	49	We reformulated this problem as the statistical physics of independent location-specific 'balls' attached to every model in a six-dimensional lattice of 56448 parametrized models by elastic springs, with model-specific 'spring constants' determined by the stochasticity of network epidemic simulations for that model. The first problem that one must contend with is that even rough estimates of the high infection transmission rate and a death rate with strong age dependence imply that one must use large networks for simulations, on the order of 10 5 nodes, because one must avoid finite-size effects in order to accurately fit the early stochastic events. Finally, we simulated the effects of various partially effective social-distancing measures on random networks and parameter sets given by the posterior expectation values of our Bayes model comparison. We compared the posterior expectation for this parameter for a location with the actual population density in an attempt to predict the appropriate way to incorporate measurable population densities in epidemic on network models [37, 38] .	./cache/cord-241057-cq20z1jt.txt	./txt/cord-241057-cq20z1jt.txt