Tag Archives: Epidemiology

Testing for COVID-19: Test Performance of a Rapid Antigen Detection Test

One of the things everyone wants to know (especially during the ongoing pandemic is- if I test positive for a disease (COVID-19), does it mean I actually have the disease (and vice-versa)?

I will try to shed some light on what test results actually mean, and how to determine if you can accept test results at face value.

For the purpose of this article, I will discuss the ‘Standard Q COVID-19 Ag detection kit’ which is the only stand-alone antigen detection assay approved for use by the Indian Council for Medical Research (ICMR) in India. Although some of the values I discuss will be specific to the above mentioned test, the principles can be applied to any other test.

In previous articles, I have described sensitivity, positive predictive value and negative predictive value. In this article, I will illustrate some principles pertaining to testing that may not have been covered previously.

From the advisory for rapid antigen test issued by ICMR, the following are determined:

  1. The test was evaluated in two centres.
  2. The performance of the test was as under:

Given the above, how do we interpret a positive (or negative) test result?

You may recall that both sensitivity and specificity of a test are fixed attributes of a test (with respect to the gold standard test [the best available test]). In addition, one needs results of both the new test and the gold standard test to calculate sensitivity and specificity.

In reality, one only has access to the test result- which is either positive or negative. How does one know if the positive test result is accurate (if the test result is positive, what is the chance that the person actually has the disease)? To determine this, we need to calculate the Positive Predictive Value (or predictive accuracy of a positive test). There is one issue, though. We need to know the disease prevalence- since the positive predictive value is directly proportional to the prevalence. In the case of COVID-19, we don’t know the prevalence for sure.

One recent report from Delhi suggests that about one in four residents had antibodies against COVID-19. This yields a prevalence of 25%. Of course, this value is likely to be contested (and revised over time), but for now, we will assume the prevalence to be 25%. This means that out of 100 people, 25 will have the disease.