Your browser doesn't support javascript.
Efficient high-throughput SARS-CoV-2 testing to detect asymptomatic carriers.
Shental, Noam; Levy, Shlomia; Wuvshet, Vered; Skorniakov, Shosh; Shalem, Bar; Ottolenghi, Aner; Greenshpan, Yariv; Steinberg, Rachel; Edri, Avishay; Gillis, Roni; Goldhirsh, Michal; Moscovici, Khen; Sachren, Sinai; Friedman, Lilach M; Nesher, Lior; Shemer-Avni, Yonat; Porgador, Angel; Hertz, Tomer.
  • Shental N; Department of Computer Science, The Open University of Israel, Ra'anana, Israel. angel@bgu.ac.il shental@openu.ac.il thertz@bgu.ac.il.
  • Levy S; Department of Microbiology and Immunology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Wuvshet V; National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Skorniakov S; Department of Microbiology and Immunology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Shalem B; National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Ottolenghi A; Department of Microbiology and Immunology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Greenshpan Y; National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Steinberg R; Department of Computer Science, Bar-Ilan University, Ramat Gan, Israel.
  • Edri A; Department of Microbiology and Immunology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Gillis R; National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Goldhirsh M; Department of Microbiology and Immunology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Moscovici K; National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Sachren S; Soroka University Medical Center, Beer-Sheva, Israel.
  • Friedman LM; Department of Microbiology and Immunology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Nesher L; National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Shemer-Avni Y; Goldman Medical School, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Porgador A; Goldman Medical School, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
  • Hertz T; Goldman Medical School, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Sci Adv ; 6(37)2020 09.
Article in English | MEDLINE | ID: covidwho-760206
ABSTRACT
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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Carrier State / Coronavirus Infections / Clinical Laboratory Techniques / Asymptomatic Infections Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Year: 2020 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Carrier State / Coronavirus Infections / Clinical Laboratory Techniques / Asymptomatic Infections Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Year: 2020 Document Type: Article