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I can't read due to the paywall but based on this tweet I would take this study with a huge grain of salt. The false positive rate on these tests is atrocious (with respect to the prevalence), around 5%, which is the % of people who tested positive in this Los Angeles study.



Read this:


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can you dumb this down for me my friend?

What does this mean?
They randomly (well, not really randomly) tested volunteers in the general population. The idea is that you test 1000 people for antibodies. Antibodies are formed by your immune system against a virus and linger in the body, so they indicate that you have been exposed to the virus in the past. If 100 people have antibodies out of 1000, you can extrapolate and say that 10% of the population in general has been exposed to the virus.

That's in theory. In practice, it is not like that at all. One, the people tested are not random, so it's likely that people who had symptoms or contacts are more likely to volunteer, so the number is inflated.

Two, the antibody test is not specific for Covid-19. It could detect past infections with other coronaviruses, which are common and typically cause mild illness or no illness at all.

Three, the test isn't perfect. The best test we have now makes mistakes 5% of the time. So if you test 1000 people, 50 will test positive even though they actually have the antibody.

This LA study found ~4% tested positive, which is the false positive rate of the study. So I really take nothing valuable away from it.

I can't read the article but this is my understanding based on the comments and other antibody tests out there.
 
They randomly (well, not really randomly) tested volunteers in the general population. The idea is that you test 1000 people for antibodies. Antibodies are formed by your immune system against a virus and linger in the body, so they indicate that you have been exposed to the virus in the past. If 100 people have antibodies out of 1000, you can extrapolate and say that 10% of the population in general has been exposed to the virus.

That's in theory. In practice, it is not like that at all. One, the people tested are not random, so it's likely that people who had symptoms or contacts are more likely to volunteer, so the number is inflated.

Two, the antibody test is not specific for Covid-19. It could detect past infections with other coronaviruses, which are common and typically cause mild illness or no illness at all.

Three, the test isn't perfect. The best test we have now makes mistakes 5% of the time. So if you test 1000 people, 50 will test positive even though they actually have the antibody.

This LA study found ~4% tested positive, which is the false positive rate of the study. So I really take nothing valuable away from it.

I can't read the article but this is my understanding based on the comments and other antibody tests out there.
thank you sir. That was explained very well for a novice like myself.
 
Gov Kemp of Georgia is trippin!!!

My Dad, a Trump supporter who also lives in Georgia, even says he's lost his mind and its too soon.
they were one of the last to close too. He said something stupid on TV awhile back too. He said he didn't know asymptomatic people could spread the virus. You think there would be a higher power who could come in and fix GA. They're screwed.
 
They randomly (well, not really randomly) tested volunteers in the general population. The idea is that you test 1000 people for antibodies. Antibodies are formed by your immune system against a virus and linger in the body, so they indicate that you have been exposed to the virus in the past. If 100 people have antibodies out of 1000, you can extrapolate and say that 10% of the population in general has been exposed to the virus.

That's in theory. In practice, it is not like that at all. One, the people tested are not random, so it's likely that people who had symptoms or contacts are more likely to volunteer, so the number is inflated.

Two, the antibody test is not specific for Covid-19. It could detect past infections with other coronaviruses, which are common and typically cause mild illness or no illness at all.

Three, the test isn't perfect. The best test we have now makes mistakes 5% of the time. So if you test 1000 people, 50 will test positive even though they actually have the antibody.

This LA study found ~4% tested positive, which is the false positive rate of the study. So I really take nothing valuable away from it.

I can't read the article but this is my understanding based on the comments and other antibody tests out there.


the false positive rate being approximately equal to the percentage tested positive doesn't make sense to me. can someone elaborate on that? so if ~40 people people were found to be positive but it's estimated to have ~40 people to be falsely tested positive, doesn't that mean 0 people have it?
 

Interesting. I know my friends in NY and CT have gotten access then I’ve heard NTers in TX taking about going. It is definitely doable and safest solo or a twosome MAX. I’ve been hearing a lot of private clubs are going to go under as a result of this :smh:
 
look at this beyond racist dogwhistle

they got no problem hiring immigrant labor to do their dirty work, but think nothing of them

oqueso what you are saying, Smithfield Foods is that your multimillion dollar firm intentionally hired large quantities of immigrants for a job handling food, endorsed them for work in the country, and then did not compensate them adequately to improve their living conditions...do I have that right?

is that your explanation?

is it?

is?

IT?
 
the false positive rate being approximately equal to the percentage tested positive doesn't make sense to me. can someone elaborate on that? so if ~40 people people were found to be positive but it's estimated to have ~40 people to be falsely tested positive, doesn't that mean 0 people have it?
You're right, that's what the result would indicate. In practice, the numbers are all estimates, so if the false positive rate is supposed to be 40 people, it's really ballpark 40, so it could be 10, it could be 100.

I don't know if they tried to do any statistical correction in the study. It's possible that 10% tested positive and then, using a known false positive rate of 5% for their test, corrected it down to 5%. Either way, it's a lot of uncertainty.
 
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