  Since the beginning of 2020, the coronavirus disease 2019 (COVID-19) has
spread rapidly in the city of Wuhan, P.R. China, and subsequently, across the
world. The swift spread of the virus is largely attributed to its stealth
transmissions in which infected patients may be asymptomatic. Undetected
transmissions present a remarkable challenge for the containment of the virus
and pose an appalling threat to the public. An urgent question that has been
asked by the public is "Should I be tested for COVID-19 if I am sick?". While
different regions established their own criteria for screening infected cases,
the screening criteria have been modified based on new evidence and
understanding of the virus as well as the availability of resources. The
shortage of test kits and medical personnel has considerably limited our
ability to do as many tests as possible. Public health officials and clinicians
are facing a dilemma of balancing the limited resources and unlimited demands.
On one hand, they are striving to achieve the best outcome by optimizing the
usage of the scant resources. On the other hand, they are challenged by the
patients' frustrations and anxieties, stemming from the concerns of not being
tested for COVID-19 for not meeting the definition of PUI (person under
investigation). In this paper, we evaluate the situation from the statistical
viewpoint by factoring into the considerations of the uncertainty and
inaccuracy of the test, an issue that is often overlooked by the general
public. We aim to shed light on the tough situation by providing evidence-based
reasoning from the statistical angle, and we expect this examination will help
the general public understand and assess the situation rationally. Most
importantly, the development offers recommendations for physicians to make
sensible evaluations to optimally use the limited resources for the best
medical outcome.
