In early February 2006, the Centers for Disease Control estimated that out of the 300,000,000 Americans out there, a million or so are HIV-positive. That's 1 in 300, or 0.3%.
How they came up with this figure, I have no idea. What I'm going to show you in the next 3 minutes is that if you test positive for HIV in America, you still probably don't have it. It's all in the numbers, and it's all very well known to the medical community.
Initial HIV tests are done using the Enzyme-Linked Immunosorbent Assay (ELISA) test. If a person tests positive, another more accurate test known as the Western blot is performed. Together these tests are claimed to have an accuracy of 99.5% - which is astoundingly precise for medical testing. But let's not count our chickens before they hatch. What this really means is that among people who do not have HIV, the test will yield 0.05% false positive.
Now I know this might scare you, but take a look at the diagram below.
In spite of what you're now thinking, this diagram is intended to clarify the statistics behind the shocking conclusion I'm going to reveal in just a few sentences. Let me explain. The first set of divergent arrows represent the population, and the numbers along these arrows are percentages. We know that 99.7% of Americans are HIV-negative and 0.3% are HIV-positive. The second set of arrows orginating at HIV negative represent the test with its corresponding percentages. Now remember, every single one of these people is HIV-free, so any positives represent a mistake on the part of the test and someone who is told he has HIV and in reality is perfectly healthy aside from any number of other terrifying diseases, conditions, mutations, and disabilities not mentioned here.
This means that 0.5% of those healthy people will falesly test positive. So the total number of positives will be the false-positives and the actual positives. The important thing to remember is that there are far more people in the healthy group, which means that even though only a tiny percentage of healthy people test positive, it's still going to be quite a large number. How large?
Let's say we test 10,000 people. We know that 30 people have HIV and 9,970 do not, but the important question is how many will test positive? Calculator time, folks, and don't hate me for saying that. Multiplying the number of healthy people - 9,970 - by the probability they will test positive - 0.005 (0.5%) gives us just about 50.
If you're not shocked and amazed by this number, you probably zoned out right about the time I said the word "multiplying." What this means is that while only 30 people had HIV, there were a total of 80 who tested positive! So even with 99.5% accuracy, if you test positive for HIV there is a 62.5% chance you don't have it at all - that's almost 2 out of 3! Better hope your doctor knows this or you could end up paying for a lot more highly-active anti-retroviral therapy than you really need.
But wait a second, if you're not American you better look again. These conclusions are very dependent on the actual percentage of the population that has the disease. Thanks to 16 years of political isolationism under dictator Robert Mugabe, which has led to ignorance about the spread and severity of HIV/AIDS in its population of 12.5 million, the country of Zimbabwe has an estimated adult HIV infection rate of to have a 30% or more. With the same accuracy, out of 10,000 Zimbabweans tested 35 will be false-positive but 3000 will actually have HIV. The likelihood, then, that you don't have HIV if you test positive in Zimbabwe drops to a staggeringly low 1.2%.
So now it must be fairly evident that when you get the results of a medical test back, it's very important to know as much as possible because if for some odd reason your doctor doesn't, things can get out of hand. This analysis did not even include the much more frightening possibility of a false-negative; that is, someone who has the disease but tests negative.