Nested pooling for the efficient detection of infected samples

PONCE DAWSON, SILVINA

Seminario; Coloquios Departamento de Matemática, Universidad Católica del Norte, Antofagasta, Chile; 2021

The rapid spread of the SARS-CoV-2 pandemic confronted us with the need of designing large-scale, cost-effective testing programs. To this end, running the test on pooled samples can be a solution if the detection method (in the case of SARS-CoV-2, the method to detect the viral RNA) is sensitive enough. Cost-effective strategies, on the other hand, require the definition of efficient deconvolution and re-testing procedures for the identifcation of the carrier. In this talk I will describe an efficient nested pooling strategy that we have devised in collaboration with Ines Armendariz, Pablo Ferrari, Daniel Fraiman and Mario Martinez and discuss its practical implementation using droplet digital PCR (ddPCR), which was shown to be 10-100 times more sensitive than the current gold standard for viral RNA detection, RT-qPCR. The latter part of the work was also done with Hugo Menzella. Among other aspects, I will discuss how the RNA quantification that ddPCR provides at the end of the test and the nested nature of the strategy can be combined to perform self-consistency tests for a better identification of infected individuals and unviable samples. A user-friendly interface is available at pooling.df.uba.ar for those who want to define the best pooling strategy under different constraints.