Multi-Level Group Testing with Application to One-Shot Pooled COVID-19 Tests

TL;DR

This paper introduces a multi-level group testing scheme for COVID-19 that efficiently detects infection levels in a one-shot manner, outperforming existing pooled testing methods in accuracy and resource use.

Contribution

The paper proposes a novel multi-level group testing approach that enables accurate infection level detection in a single test, addressing limitations of traditional methods.

Findings

The scheme accurately detects infection levels with fewer tests.

Theoretical analysis shows reliable operation under certain conditions.

Numerical results demonstrate improved performance over existing methods.

Abstract

A key requirement in containing contagious diseases, such as the Coronavirus disease 2019 (COVID-19) pandemic, is the ability to efficiently carry out mass diagnosis over large populations. Some of the leading testing procedures, such as those utilizing qualitative polymerase chain reaction, involve using dedicated machinery which can simultaneously process a limited amount of samples. A candidate method to increase the test throughput is to examine pooled samples comprised of a mixture of samples from different patients. In this work we study pooling based tests which operate in a one-shot fashion, while providing an indication not solely on the presence of infection, but also on its level, without additional pool tests, as often required in COVID-19 testing. As these requirements limit the application of traditional group-testing (GT) methods, we propose a multi-level GT scheme, which builds upon GT principles to enable accurate recovery using much fewer tests than patients, while operating in a one-shot manner and providing multi-level indications. We provide a theoretical analysis of the proposed scheme and characterize conditions under which the algorithm operates reliably and at affordable computational complexity. Our numerical results demonstrate that multi level GT accurately and efficiently detects infection levels, while achieving improved performance over previously proposed one-shot COVID-19 pooled-testing methods.