Recycled incomplete identification procedures for blood screening

Bar‐Lev, Shaul K.; Boxma, Onno; Kleiner, Igor; Perry, David; Stadje, Wolfgang

doi:10.1016/j.ejor.2016.10.005

Cited by 7 publications

(6 citation statements)

References 39 publications

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“…Group testing is concerned with finding efficient algorithms to test groups of individual samples that provide these identifications with a minimum number of tests. Group testing (GT) procedures are cost- and time-saving identification procedures that have broad applications to blood screening for HIV, hepatitis, and other infectious diseases (Gastwirth and Johnson 1994; Bilder, Tebbs, and Chen 2010; Stramer et al 2011; Tebbs, McMahan, and Bilder 2013; Bar-Lev et al 2017), quality control in product testing (Sobel and Groll 1959; Bar-Lev, Boneh, and Perry 1990), veterinary medicine (Graaesbøll et al 2016), drug discovery (Zhu, Hughes-Oliver, and Young 2001), DNA screening (Du and Hwang 2006; Cao and Sun 2016), communication and security networks (Wolf 1985; Laarhoven 2013), and experimental physics (Brady and Greighton 2000; Meinshausen, Bickel, and Rice 2009), among others.…”

Section: Introductionmentioning

confidence: 99%

Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness

Malinovsky

Albert

2018

The American Statistician

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Group testing has its origin in the identification of syphilis in the U.S. army during World War II. Much of the theoretical framework of group testing was developed starting in the late 1950s, with continued work into the 1990s. Recently, with the advent of new laboratory and genetic technologies, there has been an increasing interest in group testing designs for cost saving purposes. In this article, we compare different nested designs, including Dorfman, Sterrett and an optimal nested procedure obtained through dynamic programming. To elucidate these comparisons, we develop closed-form expressions for the optimal Sterrett procedure and provide a concise review of the prior literature for other commonly used procedures. We consider designs where the prevalence of disease is known as well as investigate the robustness of these procedures, when it is incorrectly assumed. This article provides a technical presentation that will be of interest to researchers as well as from a pedagogical perspective. Supplementary material for this article available online.

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Section: Introductionmentioning

confidence: 99%

Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness

Malinovsky

Albert

2018

The American Statistician

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“…Their engagement has resulted in several papers, (c.f., (Bar-Lev et al, 2009;2017;2017a;2017b;Bar-Lev and Perry, 1989;Bar-Lev et al, 2005;2007;2013;. Other works can be found in (Abolnikov and Dukhovny, 2003;Kopach et al, 2008;Beliën and Forcé, 2012;Civelek et al, 2015;Ghandforoush and Sen, 2010;Karaesmen et al, 2011;Marshall et al, 2004;Sebastian et al, 2012;Shi and Zhao, 2010;Deniz et al, 2010;Blake and Hardy, 2014;Xie et al, 2012).…”

Section: Some Research Work Related To the Stochastic Approachmentioning

confidence: 98%

“…The idea of an Incomplete Identification group testing Procedure (IIP) was first introduced in (Bar-Lev et al, 1990) for some industrial problem and was subsequently further developed for blood screening (e.g. (Bar-Lev et al, 2017a;). An IIP starts as above by first testing groups of size m in the ELISA station.…”

Section: Complete Versus Incomplete Identificationmentioning

confidence: 99%

A Stochastic Approach to Blood Supply, Demand and Screening in Central Blood Banks - A Review

Bar‐Lev¹

2017

Current Research in Biostatistics

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Abstract:One of the major issues in securing blood supply to patients worldwide is to provide blood of the best achievable quality, in the needed quantities. Central Blood Services (CBS's) worldwide are daily faced with the problem how to satisfy demands for blood from various hospitals. These hospitals, in their turn, are faced with the problem how to satisfy demands for blood from their patients. To solve these problems in a costeffective way is notoriously difficult, because (i) the amounts of available blood and of blood demand are random, (ii) blood can only be used during a limited amount of time, (iii) one must distinguish various blood components (red blood cells, plasma and platelets) with different associated costs and perishability and (iv) one must distinguish persons with different blood types (like AB + and O − ) with different capabilities to act as donor or as recipient. In this review paper we provide the subject background, describing the blood characteristics and the operation of CBS and hospital blood banks. In particular we describe blood demand, blood components and blood types. We depict blood screening procedures and their processing times and provide with some real data. Particularly we describe a stochastic approach to blood screening and inventory. An emphasis will be given to inventory management and blood allocation, stochastic imput-output of the inventory system and some cost functions involved.

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“…To date, GT has exploited a wide range of applications in biology [2,3], communication theory [4][5][6][7], signal processing [8], computer science [9][10][11], and mathematics [12]. The use of fundamental GTs extend to error correction code [13], identifying available multiple access channel [14,15], recovering sparse signals [1,8], detecting malicious attacks in security networks [16], testing good quality of products [17], and many others.…”

Section: Introductionmentioning

confidence: 99%

Theoretical Bounds on Performance in Threshold Group Testing Schemes

Seong

2020

Mathematics

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A threshold group testing (TGT) scheme with lower and upper thresholds is a general model of group testing (GT) which identifies a small set of defective samples. In this paper, we consider the TGT scheme that require the minimum number of tests. We aim to find lower and upper bounds for finding a set of defective samples in a large population. The decoding for the TGT scheme is exploited by minimization of the Hamming weight in channel coding theory and the probability of error is also defined. Then, we derive a new upper bound on the probability of error and extend a lower bound from conventional one to the TGT scheme. We show that the upper and lower bounds well match with each other at the optimal density ratio of the group matrix. In addition, we conclude that when the gaps between the two thresholds in the TGT framework increase, the group matrix with a high density should be used to achieve optimal performance.

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Recycled incomplete identification procedures for blood screening

Cited by 7 publications

References 39 publications

Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness

Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness

A Stochastic Approach to Blood Supply, Demand and Screening in Central Blood Banks - A Review

Theoretical Bounds on Performance in Threshold Group Testing Schemes

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