id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-304820-q3de7r1p	Griette, P.	Clarifying predictions for COVID-19 from testing data: the example of New-York State	2020-10-12		.txt	text/plain	3788	247	65	Cumulative number of reported (tested infectious) cases at time t Daily number of reported (tested infectious) cases at time t Phenomenological models for the reported cases: At the early stage of the epidemic, we assume that all the infected components of the system grow exponentially while the number of susceptible remains unchanged during a relatively short period of time t ∈ [t 1 , t 2 ]. In figure (d) we plot the cumulative number of cases coming from the model as a function of the cumulative number of tests from the data. In Figure 8 , we replace the daily number of tests n data (t) (coming from the data for New-York's state) in the model by either 2 × n data (t), 5 × n data (t), 10 × n data (t) or 100 × n data (t). Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data	./cache/cord-304820-q3de7r1p.txt	./txt/cord-304820-q3de7r1p.txt