id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-185125-be11h9wn	Baldea, Ioan	What Can We Learn from the Time Evolution of COVID-19 Epidemic in Slovenia?	2020-05-25		.txt	text/plain	2402	146	51	In the unprecedented difficulty created by the COVID-19 pandemic outbreak, 1 mathematical modeling developed by epidemiologists over many decades 2-7 may make an important contribution in helping politics to adopt adequate regulations to efficiently fight against the spread of SARS-CoV-2 virus while mitigating negative economical and social consequences. As an aggravating circumstance, one should also add the difficulty not encountered in the vast majority of previous studies: how do the input parameters needed in model simulations change in time under so many restrictive measures (wearing face masks, social distancing, movement restrictions, isolation and quarantine policies, etc) unknown in the pre-COVID-19 era? Rather, we use raw epidemiological data to validate the logistic growth and straightforwardly extract the time dependent infection rate, which is the relevant model parameter for the specific case considered and makes it possible to compare how efficient different restrictive measures act to mitigate the COVID-19 pandemic, and even to get insight significant for behavioral and social science.	./cache/cord-185125-be11h9wn.txt	./txt/cord-185125-be11h9wn.txt