# My Antibodies Test

In mid-February, after spending four days in New York City, I developed a respiratory viral infection that featured certain symptoms associated with Covid-19. Yesterday I had an antibodies test that is supposed to be 99% accurate. I expect to learn the results today. You can’t evaluate the results of these tests without some statistical analysis. If the test shows a false positive only 1% of the time, that doesn’t mean that, if you test positive, there’s only a 1% chance it’s a false positive. Your chance of a false positive is affected by how many people who take the test *are *positive, and how many are not. For example, if out of 1,000 people who take the test, only 10% *are* positive, out of the 900 people who aren’t positive, 1% –– 9 people –– will test false positive. So, if you are test taker #1001, you’re roughly nine times more likely to be a false positive than a true positive.

I think I have that right.

When I get my test results today, I’m going to try to find out what percent of the people who have taken the test in my cohort, if there is such a thing as my cohort, tested positive. I’ll be surprised if I get a straight answer to this question. Even if I do, I’m not sure it will help me figure out what the odds are that I really do have antibodies even if my test came out positive.