Implementation of an efficient SARS-CoV-2 specimen pooling strategy for high throughput diagnostic testing
Abstract The rapid identification and isolation of infected individuals remains a key strategy for controlling the spread of SARS-CoV-2. Frequent testing of populations to detect infection early in asymptomatic or presymptomatic individuals can be a powerful tool for intercepting transmission, espec...
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Nature Portfolio
2021
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oai:doaj.org-article:00d2faa17b5f49e284e8c2228bbcd2de2021-12-02T19:12:35ZImplementation of an efficient SARS-CoV-2 specimen pooling strategy for high throughput diagnostic testing10.1038/s41598-021-96934-z2045-2322https://doaj.org/article/00d2faa17b5f49e284e8c2228bbcd2de2021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96934-zhttps://doaj.org/toc/2045-2322Abstract The rapid identification and isolation of infected individuals remains a key strategy for controlling the spread of SARS-CoV-2. Frequent testing of populations to detect infection early in asymptomatic or presymptomatic individuals can be a powerful tool for intercepting transmission, especially when the viral prevalence is low. However, RT-PCR testing—the gold standard of SARS-CoV-2 diagnosis—is expensive, making regular testing of every individual unfeasible. Sample pooling is one approach to lowering costs. By combining samples and testing them in groups the number of tests required is reduced, substantially lowering costs. Here we report on the implementation of pooling strategies using 3-d and 4-d hypercubes to test a professional sports team in South Africa. We have shown that infected samples can be reliably detected in groups of 27 and 81, with minimal loss of assay sensitivity for samples with individual Ct values of up to 32. We report on the automation of sample pooling, using a liquid-handling robot and an automated web interface to identify positive samples. We conclude that hypercube pooling allows for the reliable RT-PCR detection of SARS-CoV-2 infection, at significantly lower costs than lateral flow antigen (LFA) tests.Lavanya SinghUgochukwu J. AnyanejiWilfred NdifonNeil TurokStacey A. MattisonRichard LessellsIlya SinayskiyEmmanuel J. SanHouriiyah TegallyShaun BarnettTrevor LorimerFrancesco PetruccioneTulio de OliveiraNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-7 (2021) |
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Medicine R Science Q Lavanya Singh Ugochukwu J. Anyaneji Wilfred Ndifon Neil Turok Stacey A. Mattison Richard Lessells Ilya Sinayskiy Emmanuel J. San Houriiyah Tegally Shaun Barnett Trevor Lorimer Francesco Petruccione Tulio de Oliveira Implementation of an efficient SARS-CoV-2 specimen pooling strategy for high throughput diagnostic testing |
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Abstract The rapid identification and isolation of infected individuals remains a key strategy for controlling the spread of SARS-CoV-2. Frequent testing of populations to detect infection early in asymptomatic or presymptomatic individuals can be a powerful tool for intercepting transmission, especially when the viral prevalence is low. However, RT-PCR testing—the gold standard of SARS-CoV-2 diagnosis—is expensive, making regular testing of every individual unfeasible. Sample pooling is one approach to lowering costs. By combining samples and testing them in groups the number of tests required is reduced, substantially lowering costs. Here we report on the implementation of pooling strategies using 3-d and 4-d hypercubes to test a professional sports team in South Africa. We have shown that infected samples can be reliably detected in groups of 27 and 81, with minimal loss of assay sensitivity for samples with individual Ct values of up to 32. We report on the automation of sample pooling, using a liquid-handling robot and an automated web interface to identify positive samples. We conclude that hypercube pooling allows for the reliable RT-PCR detection of SARS-CoV-2 infection, at significantly lower costs than lateral flow antigen (LFA) tests. |
format |
article |
author |
Lavanya Singh Ugochukwu J. Anyaneji Wilfred Ndifon Neil Turok Stacey A. Mattison Richard Lessells Ilya Sinayskiy Emmanuel J. San Houriiyah Tegally Shaun Barnett Trevor Lorimer Francesco Petruccione Tulio de Oliveira |
author_facet |
Lavanya Singh Ugochukwu J. Anyaneji Wilfred Ndifon Neil Turok Stacey A. Mattison Richard Lessells Ilya Sinayskiy Emmanuel J. San Houriiyah Tegally Shaun Barnett Trevor Lorimer Francesco Petruccione Tulio de Oliveira |
author_sort |
Lavanya Singh |
title |
Implementation of an efficient SARS-CoV-2 specimen pooling strategy for high throughput diagnostic testing |
title_short |
Implementation of an efficient SARS-CoV-2 specimen pooling strategy for high throughput diagnostic testing |
title_full |
Implementation of an efficient SARS-CoV-2 specimen pooling strategy for high throughput diagnostic testing |
title_fullStr |
Implementation of an efficient SARS-CoV-2 specimen pooling strategy for high throughput diagnostic testing |
title_full_unstemmed |
Implementation of an efficient SARS-CoV-2 specimen pooling strategy for high throughput diagnostic testing |
title_sort |
implementation of an efficient sars-cov-2 specimen pooling strategy for high throughput diagnostic testing |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/00d2faa17b5f49e284e8c2228bbcd2de |
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