Effective matrix designs for COVID-19 group testing.

ABSTRACT:

Background

Grouping samples with low prevalence of positives into pools and testing these pools can achieve considerable savings in testing resources compared with individual testing in the context of COVID-19. We review published pooling matrices, which encode the assignment of samples into pools and describe decoding algorithms, which decode individual samples from pools. Based on the findings we propose new one-round pooling designs with high compression that can efficiently be decoded by combinatorial algorithms. This expands the admissible parameter space for the construction of pooling matrices compared to current methods.

Results

By arranging samples in a grid and using polynomials to construct pools, we develop direct formulas for an Algorithm (Polynomial Pools (PP))

SUBMITTER: Brust D 

PROVIDER: S-EPMC9872308 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature