id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-292537-9ra4r6v6	Liu, Fenglin	Predicting and analyzing the COVID-19 epidemic in China: Based on SEIRD, LSTM and GWR models	2020-08-27		.txt	text/plain	5662	259	52	For the study of infectious diseases like COVID-19, SARS, and Ebola, most of the literature used descriptive research or model methods to assess indicators and analyze the effect of interventions, such as combining migration data to evaluate the potential infection rate [18, 19] , understanding the impact of factors like environmental temperature and vaccines that might be potentially linked to the diseases [20, 21] , using basic and time-varying reproduction number (R 0 & R t ) to estimate changeable transmission dynamics of epidemic conditions [22] [23] [24] [25] [26] [27] , calculating and predicting the fatal risk to display any stage of outbreak [28] [29] [30] , or providing suggestions and interventions from risk management and other related aspects based on the results of modeling tools or historical lessons [31] [32] [33] [34] [35] [36] [37] [38] [39] .	./cache/cord-292537-9ra4r6v6.txt	./txt/cord-292537-9ra4r6v6.txt