id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-344070-17oac3bg	Silverman, Justin D	Using ILI surveillance to estimate state-specific case detection rates and forecast SARS-CoV-2 spread in the United States	2020-04-03		.txt	text/plain	5095	284	59	ILI correlates with known patterns of SARS-CoV-2 spread across states within the US, suggesting the surge is unlikely to be due to other endemic respiratory pathogens, yet is orders of magnitude larger than the number of confirmed COVID cases reported. We find that as the seasonal surge of endemic non-influenza respiratory pathogens declines, this excess ILI correlates more strongly with state-level patterns of newly confirmed COVID cases suggesting that 75 this surge is a reflection of ILI due to SARS-CoV-2 (Pearson ρ = 0.8 and p < 10 −10 for the last two weeks; Figure S1 ). However, if we assume the excess non-influenza ILI is almost entirely due to SARS-CoV-2, an assumption that becomes more valid as the virus becomes more prevalent, we can use the excess non-influenza ILI to understand the constraints and mutual dependence of exponential growth rates, the rate of subclinical infections, and the time 95 between the onset of infectiousness and a patient reporting as ILI Figure 3 .	./cache/cord-344070-17oac3bg.txt	./txt/cord-344070-17oac3bg.txt