  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].
