Group Testing: An Information
Theory Perspective

Aldridge, Matthew; Johnson, Oliver; Scarlett, Jonathan

doi:10.1561/0100000099

Cited by 185 publications

(202 citation statements)

References 167 publications

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“…If a pool of n samples tests negative, all samples must be negative, and therefore their status has been determined in only one test instead of n individual tests. Various group testing algorithms exist, with different assumptions and constraints [16,17]. While many such algorithms, most notably binary splitting, may be very efficient in theory, they might be unsuitable because of practical limitations.…”

Section: Introductionmentioning

confidence: 99%

Large-scale implementation of pooled RNA extraction and RT-PCR for SARS-CoV-2 detection

Ben-Ami¹,

Klochendler²,

Seidel³

et al. 2020

Clinical Microbiology and Infection

183

147

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Introduction: Testing for active SARS-CoV-2 infection is a fundamental tool in the public health measures taken to control the COVID-19 pandemic. Because of the overwhelming use of SARS-CoV-2 reverse transcription (RT)-PCR tests worldwide, the availability of test kits has become a major bottleneck and the need to increase testing throughput is rising. We aim to overcome these challenges by pooling samples together, and performing RNA extraction and RT-PCR in pools. Methods: We tested the efficiency and sensitivity of pooling strategies for RNA extraction and RT-PCR detection of SARS-CoV-2. We tested 184 samples both individually and in pools to estimate the effects of pooling. We further implemented Dorfman pooling with a pool size of eight samples in large-scale clinical tests. Results: We demonstrated pooling strategies that increase testing throughput while maintaining high sensitivity. A comparison of 184 samples tested individually and in pools of eight samples showed that test results were not significantly affected. Implementing the eight-sample Dorfman pooling to test 26 576 samples from asymptomatic individuals, we identified 31 (0.12%) SARS-CoV-2 positive samples, achieving a 7.3-fold increase in throughput. Discussion: Pooling approaches for SARS-CoV-2 testing allow a drastic increase in throughput while maintaining clinical sensitivity. We report the successful large-scale pooled screening of asymptomatic

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Section: Introductionmentioning

confidence: 99%

Large-scale implementation of pooled RNA extraction and RT-PCR for SARS-CoV-2 detection

Ben-Ami¹,

Klochendler²,

Seidel³

et al. 2020

Clinical Microbiology and Infection

183

147

View full text Add to dashboard Cite

show abstract

“…It should be acknowledged that this valuable boost does not explore the theoretical and practically achievable rates of compressive sampling capabilities. While theoretically perfect, reconstruction of original test results available with not much more than k log 2 (N/k) measurements (25), where N is the number of samples and k is the number of positive cases, with the use of modern decoding algorithms, the achievable rates are close to the theoretical bounds. This means a 10-to 20-fold rate increase for a 1-0.1% prevalence band is possible with more sophisticated pooling schemes and decoding algorithms.…”

Section: Population Level Scanning For Covid-19mentioning

confidence: 77%

“…As collecting blood samples and performing a single Wassermann test for each man appeared to be quite resource demanding in the circumstances of World War II, pooling blood samples and performing group tests was observed to be quite effective since the disease was relatively rare. Later on, group testing has become a popular topic in the information theory field, enabling orders of magnitude saving from the test numbers while being able to pinpoint sparse positives accurately (25). Similarly, the attractiveness of recovering sparse signals from a small number of measurements led, in the mid-2000s, to the birth of an entire research area called compressive sampling (compressed sensing) in the signal processing field around (26).…”

Section: Population Level Scanning For Covid-19mentioning

confidence: 99%

COVID-19 Pandemic: Group Testing

Nalbantoğlu

Gündoğdu

2020

Front. Med.

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“…Thus, a few definitions may be useful here. A group test is noiseless if a negative test outcome is guaranteed when all items in the testing pool are nondefective, and a positive outcome when a least one item in the pool is defective (Aldridge, Johnson and Scarlett, 2019). Otherwise, the test is noisy.…”

Section: Using Homophily To Push Information-theoretic Limitsmentioning

confidence: 99%

Group Testing with Homophily to Curb Epidemics with Asymptomatic Carriers

Belleville

2020

Preprint

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The global fight against COVID-19 is plagued by asymptomatic transmission and false negatives. Group testing is increasingly recognized as necessary to fight this epidemic. I examine the gains from considering heterogeneous interpersonal interactions (homophily), which induce potential contamination, when designing testing pools. Homophily can be identified ex ante at a scale commensurate with pool size, so that the risk of contamination is higher within a well-designed pool than with an outsider. This makes it possible to overcome the usual information-theoretic limits of group testing which rely on an implicit homogeneity assumption. More importantly, group testing with homophily detects asymptomatic carriers that would be missed even by exhaustive individual testing because of false negatives. Such a strategy should be implemented at least at a weekly frequency to fit the time profile of test positivity. It can be used either to avoid unnecessary lockdowns or to make lockdowns more efficient.

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Group Testing: An Information Theory Perspective

Cited by 185 publications

References 167 publications

Large-scale implementation of pooled RNA extraction and RT-PCR for SARS-CoV-2 detection

Large-scale implementation of pooled RNA extraction and RT-PCR for SARS-CoV-2 detection

COVID-19 Pandemic: Group Testing

Group Testing with Homophily to Curb Epidemics with Asymptomatic Carriers

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