This is of course not true, but we are still being hypothetical. Let’s say all of us Indians are getting ourselves tested. After all, it was a pretty deadly pandemic.īut suppose we take a closer, maybe deeper, look at my friend’s case? Consider these numbers: Isn’t that what the numbers tell us? And if so, and even if covid is on the wane, that is still a pretty unsettling number. So, given the accuracy of this test, what is the chance that my friend, who tested positive, actually does have the virus? At first glance, we might think the answer is 99% or more, simple. In fact, with the numbers above, you’d most likely call it better than 99% accurate and that’s a good way to describe it. No doubt you’d agree that this is a very accurate test. Let’s say the converse is even better: the test produces a negative result for 99.5% of those who are not infected. Now, let’s say that an RT-PCR test administered in India produces a positive result for 99% of those who already have the virus. They want to be sure one way or another, and that’s why they get tested. They have suspicious symptoms, that’s all. Of course, some who have the virus, like my friend before he took the test, don’t know they are infected. We can divide the population of the country into two camps: those who are actually infected with the virus, and those who are not. Let me try explaining that here with some hypothetical numbers. Here’s a question worth asking: what do we mean by a “very accurate" test?
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