Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Apr 14;13(589):eabf2823.
doi: 10.1126/scitranslmed.abf2823. Epub 2021 Feb 22.

Lessons from applied large-scale pooling of 133,816 SARS-CoV-2 RT-PCR tests

Netta Barak  1 , Roni Ben-Ami  2   3 , Tal Sido  3   4 , Amir Perri  5 , Aviad Shtoyer  5 , Mila Rivkin  3 , Tamar Licht  6 , Ayelet Peretz  2 , Judith Magenheim  2 , Irit Fogel  3 , Ayalah Livneh  3 , Yutti Daitch  3 , Esther Oiknine-Djian  3 , Gil Benedek  3   7 , Yuval Dor  8 , Dana G Wolf  9   10 , Moran Yassour  11   12 ; Hebrew University-Hadassah COVID-19 Diagnosis Team
Collaborators, Affiliations

Lessons from applied large-scale pooling of 133,816 SARS-CoV-2 RT-PCR tests

Netta Barak et al. Sci Transl Med. .

Abstract

Pooling multiple swab samples before RNA extraction and real-time reverse transcription polymerase chain reaction (RT-PCR) analysis has been proposed as a strategy to reduce costs and increase throughput of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tests. However, reports on practical large-scale group testing for SARS-CoV-2 have been scant. Key open questions concern reduced sensitivity due to sample dilution, the rate of false positives, the actual efficiency (number of tests saved by pooling), and the impact of infection rate in the population on assay performance. Here, we report an analysis of 133,816 samples collected between April and September 2020 and tested by Dorfman pooling for the presence of SARS-CoV-2. We spared 76% of RNA extraction and RT-PCR tests, despite the frequently changing prevalence (0.5 to 6%). We observed pooling efficiency and sensitivity that exceeded theoretical predictions, which resulted from the nonrandom distribution of positive samples in pools. Overall, our findings support the use of pooling for efficient large-scale SARS-CoV-2 testing.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1. Overall statistics of pool sizes of eight and five.
(A) Weekly average of eight-sample (blue) and five-sample (red) pools counts, together with the weekly average of the prevalence rate among pooled samples (black). (B and C) Pool results for eight-sample (B) and five-sample (C) pools, respectively. (D and E) Counts of positive pools aggregated by the number of positive samples identified within the pool, for eight-sample (D) and five-sample (E) pools.
Fig. 2
Fig. 2. Comparisons of pool Ct and sample Ct.
(A) Comparison of sample viral Ct (x axis) and pool viral Ct (y axis) for all 935 amplified eight-sample pools with a single positive sample. Linear regression with a predetermined slope of 1 is marked in yellow, and y = x is marked in gray. (B) As in (A), including also pools with 241 two amplified samples (light blue) and 82 three or more positive samples (gray). (C) Distributions of viral Ct values of positive samples in positive pools divided into two groups: samples with the minimal Ct in their pool (blue) and samples with the nonminimal Ct in their pool (gray).
See this image and copyright information in PMC

References

    1. Dorfman R., The detection of defective members of large populations. Ann. Math. Stat. 14, 436–440 (1943).
    1. Shental N., Levy S., Wuvshet V., Skorniakov S., Shalem B., Ottolenghi A., Greenshpan Y., Steinberg R., Edri A., Gillis R., Goldhirsh M., Moscovici K., Sachren S., Friedman L. M., Nesher L., Shemer-Avni Y., Porgador A., Hertz T., Efficient high-throughput SARS-CoV-2 testing to detect asymptomatic carriers. Sci. Adv. 6, eabc5961 (2020). - PMC - PubMed
    1. J. H. McDermott, D. Stoddard, P. Woolf, J. M. Ellingford, D. Gokhale, A. Taylor, L. A. M. Demain, W. G. Newman, G. Black, A non-adaptive combinatorial group testing strategy to facilitate healthcare worker screening during the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak. medRxiv 10.1101/2020.07.21.20157677 [Preprint]. 30 July 2020. 10.1101/2020.07.21.20157677. - DOI - DOI - PMC - PubMed
    1. S. Ghosh, A. Rajwade, S. Krishna, N. Gopalkrishnan, T. E. Schaus, A. Chakravarthy, S. Varahan, V. Appu, R. Ramakrishnan, S. Ch, M. Jindal, V. Bhupathi, A. Gupta, A. Jain, R. Agarwal, S. Pathak, M. A. Rehan, S. Consul, Y. Gupta, N. Gupta, P. Agarwal, R. Goyal, V. Sagar, U. Ramakrishnan, S. Krishna, P. Yin, D. Palakodeti, M. Gopalkrishnan, Tapestry: A single-round smart pooling technique for COVID-19 testing. medRxiv 10.1101/2020.04.23.20077727 [Preprint]. 2 May 2020. 10.1101/2020.04.23.20077727. - DOI - DOI
    1. L. Mutesa, P. Ndishimye, Y. Butera, J. Souopgui, A. Uwineza, R. Rutayisire, E. Musoni, N. Rujeni, T. Nyatanyi, E. Ntagwabira, M. Semakula, C. Musanabaganwa, D. Nyamwasa, M. Ndashimye, E. Ujeneza, I. E. Mwikarago, C. M. Muvunyi, J. B. Mazarati, S. Nsanzimana, N. Turok, W. Ndifon, A strategy for finding people infected with SARS-CoV-2: Optimizing pooled testing at low prevalence. medRxiv 10.1101/2020.05.02.20087924 [Preprint]. 3 August 2020. 10.1101/2020.05.02.20087924. - DOI - DOI

Publication types