mlsanityData to 7 Oct 2026

Group Testing for COVID-19: How to Stop Worrying and Test More

arXiv 2004.06306 ↗First posted 14 Apr 2020stat.ME q-bio.QMcited by 1

Not on the map. Why?

Abstract (arXiv)

The corona virus disease 2019 (COVID-19) caused by the novel corona virus has an exponential rate of infection. COVID-19 is particularly notorious as the onset of symptoms in infected patients are usually delayed and there exists a large number of asymptomatic carriers. In order to prevent overwhelming of medical facilities and large fatality rate, early stage testing and diagnosis are key requirements. In this article, we discuss the methodologies from the group testing literature and its relevance to COVID-19 diagnosis. Specifically, we investigate the efficiency of group testing using polymerase chain reaction (PCR) for COVID-19. Group testing is a method in which multiple samples are pooled together in groups and fewer tests are performed on these groups to discern all the infected samples. We study the effect of dilution due to pooling in group testing and show that group tests can perform well even in the presence of dilution effects. We present multiple group testing algorithms that could reduce the number of tests performed for COVID-19 diagnosis. We analyze the efficiency of these tests and provide insights on their practical relevance. With the use of algorithms described here, test plans can be developed that can enable testing centers to increase the number of diagnosis performed without increasing the number of PCR tests. The codes for generating test plans are available online at [1].

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 14 Apr 2020.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 1.

1 paper.