id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-289647-14ba5sro	Panuganti, Bharat A.	Predicting COVID-19 Incidence Using Anosmia and Other COVID-19 Symptomatology: Preliminary Analysis Using Google and Twitter	2020-06-02		.txt	text/plain	3219	157	45	OBJECTIVE: To determine the relative correlations of Twitter and Google Search user trends concerning smell loss with daily coronavirus disease 2019 (COVID-19) incidence in the United States, compared to other severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) symptoms. 5 As such, although significant correlations between Google searches pertaining to anosmia and COVID-19 incidence have already been reported, our intention in the present study is to better understand the relative value of alternative infodemiological parameters (nonsmell symptoms, COVID-19 searches and tweets) and platforms (Twitter) in estimating COVID-19 infection trajectory in the United States. Table SA in the online version of the article); data pertaining to March 22, 2020, and the 2 following days were excluded in 1 iteration of the analysis to help evaluate quantitatively the effect of discrete, lay media transmissions on Twitter and Google search trend correlations with COVID-19 incidence.	./cache/cord-289647-14ba5sro.txt	./txt/cord-289647-14ba5sro.txt