About: Sample pooling methods for efficient pathogen screening: Practical implications

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Sample pooling methods for efficient pathogen screening: Practical implications
Creator	Hepp, Crystal Cocking, Jill Fofanov, Viacheslav Furstenau, Tara
source	BioRxiv
abstract	Due to the large number of negative tests, individually screening large populations for rare pathogens can be wasteful and expensive. Sample pooling methods improve the efficiency of large-scale pathogen screening campaigns by reducing the number of tests and reagents required to accurately categorize positive and negative individuals. Such methods rely on group testing theory which mainly focuses on minimizing the total number of tests; however, many other practical concerns and tradeoffs must be considered when choosing an appropriate method for a given set of circumstances. Here we use computational simulations to determine how several theoretical approaches compare in terms of (a) the number of tests, to minimize costs and save reagents, (b) the number of sequential steps, to reduce the time it takes to complete the assay, (c) the number of samples per pool, to avoid the limits of detection, (d) simplicity, to reduce the risk of human error, and (e) robustness, to poor estimates of the number of positive samples. We found that established methods often perform very well in one area but very poorly in others. Therefore, we introduce and validate a new method which performs fairly well across each of the above criteria making it a good general use approach.
has issue date	2020-07-16(xsd:dateTime)
bibo:doi	10.1101/2020.07.16.206060
has license	biorxiv
sha1sum (hex)	d401d82f5a10c19bc0145ffc12a15f560232e255
schema:url	https://doi.org/10.1101/2020.07.16.206060
resource representing a document's title	Sample pooling methods for efficient pathogen screening: Practical implications
schema:publication	bioRxiv
resource representing a document's body	covid:d401d82f5a10c19bc0145ffc12a15f560232e255#body_text
is schema:about of	named entity 'rapid' named entity 'large' named entity 'computational' named entity 'sample' named entity 'positive' »more»

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