Efficient high-throughput SARS-CoV-2 testing to detect asymptomatic carriers

Noam Shental, Shlomia Levy, Vered Wuvshet, Shosh Skorniakov, Bar Shalem, Aner Ottolenghi, Yariv Greenshpan, Rachel Steinberg, Avishay Edri, Roni Gillis, Michal Goldhirsh, Khen Moscovici, Sinai Sachren, Lilach M. Friedman, Lior Nesher, Yonat Shemer-Avni, Angel Porgador, Tomer Hertz

Research output: Contribution to journalArticlepeer-review


Recent reports suggest that 10 to 30% of severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) infected patients are asymptomatic and that viral shedding may occur before symptom onset. Therefore, there is an urgent need to increase diagnostic testing capabilities to prevent disease spread. We developed P-BEST, a method for Pooling-Based Efficient SARS-CoV-2 Testing, which identifies all positive subjects within a set of samples using a single round of testing. Each sample is assigned into multiple pools using a combinatorial pooling strategy based on compressed sensing. We pooled sets of 384 samples into 48 pools, providing both an eightfold increase in testing efficiency and an eightfold reduction in test costs, while identifying up to five positive carriers. We then used P-BEST to screen 1115 health care workers using 144 tests. P- BEST provides an efficient and easy-to-implement solution for increasing testing capacity that can be easily integrated into diagnostic laboratories.

Original languageEnglish
Article numbereabc5961
JournalScience advances
Issue number37
StatePublished - Sep 2020

Bibliographical note

Funding Information:
We thank J. Racah and S. Levy-Tzedek for discussions and manuscript editing. N.S. thanks D. Shental and M. Sobel for discussions. Funding for this study was provided by a donation to BGU from the Rosetrees Trust. A.P. was supported by an Israeli Science Foundation grant ISF-2484/19 (10/2019-9/2023). T.H. was supported by an Israeli Science Foundation grant ISF-882/17 (10/2017-9/2021).

Publisher Copyright:
© 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC)


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