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Comment by obastani | Hacker News Reader

The result in the Stanford paper is very likely biased due to the false positive rate of the test they used:

https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw...

I've found that the false postive rate of the normal test to be 10% and chest CT to 6%. https://abc7news.com/coronavirus-test-free-testing-update-ac....

Shouldn't we use this simply because the false positive of 2%-1% is lower than those tests we are using for making policies right now.

But thats a better percentage than a lot of the normal covid tests. I haven't done the math entirely but a 98.3% to 99.9% accurate test doesn't seem to correlate with a 50x-85x jump. If anyone can write out the proof that would be great.

Also this article has one weird thing I picked up on and maybe I someone can verify it but they've said 100 people died in Santa Clara country but I could find 73 possible covid-19 deaths. All of those haven't been verified. This is based on April 17th numbers

I don't know the specific numbers but this jump is definitely possible.

Let's say the false-negative rate is 0% and the false-positive rate is 2%. For sake of argument, let's say that 0.05% actually have Covid. If you tested 10000, 5 people have it in reality but your testing would show that 205 people tested positive.

That doesn't seem right if it says 5 people had it then a false positive would only say that there's a 2% that likelihood that that test is wrong. Its not saying there is a 2% likelihood that 10000 people are sick. Its saying there's a 98% chance that this test diagnosis them right and 2% chance it does it wrong.

This is better than the false positive of other tests like the normal tests with a 10-15% false positive rate. https://abc7news.com/coronavirus-test-free-testing-update-ac...

Also this

and the FB data is likely underestimated too, because many persons don't feel comfortable about answering honestly with their real name to a company/university that could be coerced by government to share their identity (and that could mean fines, jail, or quarantine)

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