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Well, the type of information you're trying to gather is rather unique. Usually we just wait for a virus to run course then test lots of people to see the resul

Well, the type of information you're trying to gather is rather unique. Usually we just wait for a virus to run course then test lots of people to see the resulting case counts. But we can't do that here. Normally you just use a control and test group, but that doesn't work for figuring out underlying infection rates. There are some tests trying to sample everyone in a geographic area (SF Mission census block) but the data isn't out yet because they're conducting tests as we speak.

SpicyLemonZest 7y ago
I guarantee you that when the data comes out: * It will also show an undercount of at least an order of magnitude. * Commenters will still pop up to explain why the results can't be trusted and which further studies are absolutely required before we believe them.
- joshuamorton 7y ago
  I guess we'll see. I don't share your certainty. Although I'd love to be able to go outside sooner. Also elsewhere in this thread it's mentioned that the Florida and Santa Clara results could be entirely explained by high type II error in the test. The Florida test appeared to have a false positive rate of ~15% when independently validated, which is basically the infection rate they found. In other words, this is a specific form of base rate fallacy where the test accuracy is really low.
- suzzer99 7y ago
  Does anyone not think case count is an order of magnitude less than infected count?
- CydeWeys 7y ago
  > It will also show an undercount of at least an order of magnitude. It seems pretty likely that the data will come out showing at least 10%, so it's literally impossible for it to undercount by an order of magnitude. How do you think a random sample of inhabitants would be off by a whole order of magnitude, anyway? Can you explain the mechanism whereby that might happen? The only thing that comes to mind would be using a worthless test with a 90+% false negative rate.

SpicyLemonZest 7y ago

I guarantee you that when the data comes out: * It will also show an undercount of at least an order of magnitude. * Commenters will still pop up to explain why the results can't be trusted and which further studies are absolutely required before we believe them.

joshuamorton 7y ago
I guess we'll see. I don't share your certainty. Although I'd love to be able to go outside sooner. Also elsewhere in this thread it's mentioned that the Florida and Santa Clara results could be entirely explained by high type II error in the test. The Florida test appeared to have a false positive rate of ~15% when independently validated, which is basically the infection rate they found. In other words, this is a specific form of base rate fallacy where the test accuracy is really low.
suzzer99 7y ago
Does anyone not think case count is an order of magnitude less than infected count?
CydeWeys 7y ago
> It will also show an undercount of at least an order of magnitude. It seems pretty likely that the data will come out showing at least 10%, so it's literally impossible for it to undercount by an order of magnitude. How do you think a random sample of inhabitants would be off by a whole order of magnitude, anyway? Can you explain the mechanism whereby that might happen? The only thing that comes to mind would be using a worthless test with a 90+% false negative rate.