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Abstract
To increase the throughput, lower the cost, and save scarce test reagents, laboratories can pool patient samples before SARS-CoV-2 RT-qPCR testing. While different sample pooling methods have been proposed and effectively implemented in some laboratories, no systematic and large-scale evaluations exist using real-life quantitative data gathered throughout the different epidemiological stages. Here, we use anonymous data from 9673 positive cases to model, simulate and compare 1D and 2D pooling strategies. We show that the optimal choice of pooling method and pool size is an intricate decision with a testing population-dependent efficiency-sensitivity trade-off and present an online tool to provide the reader with custom real-time 1D pooling strategy recommendations.
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1 Cancer Research Institute Ghent, OncoRNALab, Ghent, Belgium (GRID:grid.510942.b); Ghent University, Department of Biomolecular Medicine, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Ghent University, Center for Medical Genetics, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798)
2 Biogazelle, Zwijnaarde, Belgium (GRID:grid.5342.0)
3 Ghent University, Department of Biomolecular Medicine, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Ghent University, Center for Medical Genetics, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798)
4 Cancer Research Institute Ghent, OncoRNALab, Ghent, Belgium (GRID:grid.510942.b); Ghent University, Department of Biomolecular Medicine, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Ghent University, Center for Medical Genetics, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Biogazelle, Zwijnaarde, Belgium (GRID:grid.5342.0)