id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-117424-mp6h9dyl	Abraham, Louis	Bloom Origami Assays: Practical Group Testing	2020-07-21		.txt	text/plain	8661	620	66	Given n people, test characteristics tpr & tnr and a set of prior probabilities of sample infection (p i ) 1≤i≤n , the best multiset D of m pool designs is the one maximizing the information gain. While Bloom filters have been considered for the low-prevalence COVID-19 testing problem [19, 12] , current methods are based on a simple randomized encoding and decoding process that was designed for internet-scale applications where even linear time was prohibitive and where the keys are not known beforehand. Assuming there are no false negative pool results, one can use the decoder to identify all positive samples and derive optimal dimensions b × g that minimize the number of tests, as shown in the below theorem: The analysis borrows tools from regular Bloom filters and the results shown in [20] .	./cache/cord-117424-mp6h9dyl.txt	./txt/cord-117424-mp6h9dyl.txt