Use of compressed sensing to expedite high-throughput diagnostic testing for COVID-19 and beyond.

ABSTRACT: The rapid spread of SARS-CoV-2 has placed a significant burden on public health systems to provide swift and accurate diagnostic testing highlighting the critical need for innovative testing approaches for future pandemics. In this study, we present a novel sample pooling procedure based on compressed sensing theory to accurately identify virally infected patients at high prevalence rates utilizing an innovative viral RNA extraction process to minimize sample dilution. At prevalence rates ranging from 0-14.3%, the number of tests required to identify the infection status of all patients was reduced by 69.26% as compared to conventional testing in primary human SARS-CoV-2 nasopharyngeal swabs and a coronavirus model system. Our method provided quantification of individual sample viral load

SUBMITTER: Waldstein KA 

PROVIDER: S-EPMC9632879 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature