id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-179749-qdbmpi7j	Sacks, Daniel W.	What can we learn about SARS-CoV-2 prevalence from testing and hospital data?	2020-08-01		.txt	text/plain	10732	621	56	We estimate upper and lower bounds on the prevalence of the virus in the general population and the population of non-COVID hospital patients under weak assumptions on who gets tested, using Indiana data on hospital inpatient records linked to SARS-CoV-2 virological tests. In this paper, we propose a new approach to measuring the point-in-time prevalence of active SARS-CoV-2 infections in the overall population using data on patients who are hospitalized for non-COVID reasons. The combination of these assumptions with linked testinghospital data leads to relatively tight upper and lower bounds on the prevalence of active SARS-CoV-2 infections in the overall population in Indiana in each week from mid-March to mid-June. We maintain the test monotonicity assumption throughout, and we derive upper and lower bounds on prevalence in the population under two alternative assumptions about the representativeness of non-COVID hospitalizations for the broader population. Equivalently, the independence assumption implies that SARS-CoV-2 prevalence is the same among people who are hospitalized for non-COVID conditions and the general population.	./cache/cord-179749-qdbmpi7j.txt	./txt/cord-179749-qdbmpi7j.txt