Evaluation of efficiency and sensitivity of 1D and 2D sample pooling strategies for diagnostic screening purposes

Abstract

As SARS-CoV-2 continues to spread around the world while the pandemic lasts, testing facilities are forced to massively increment their testing capacities to handle the increasing number of samples. While sample pooling methods have been proposed or are effectively implemented in some labs, no systematic and large-scale simulations have been performed using real-life quantitative data from testing facilities. Here, we use anonymous data from 1632 positive cases to simulate and compare 1D and 2D pooling strategies. We show that the choice of pooling method and pool size is an intricate decision with a prevalence-dependent efficiency-sensitivity trade-off.