@freemo Have you seen the USC antibody study results? Interesting, and somewhat expected https://news.usc.edu/168987/antibody-testing-results-covid-19-infections-los-angeles-county/
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@obi indeed, not surprising
@realcaseyrollins thats what it has always seemed to me, but what do i know @freemo
Nothing about this changes the fact that it was as serious as they said. We always knew, and accounted for, the fact that many more were infected than tested. We also always knew that a large portion were asymptomatic though this doesnt change the fact that a large portion still died, these facts arent at odds either.
@freemo @realcaseyrollins I know its a lot to base off just one study, and to scale it towards the entire population, but if it were to that scale in that range (2.8-5.6%) wouldn't that bring the mortality rate down to somewhere between .02 and .06%? That added with the fact that COVID19 attributed deaths dont require a positive test, I'm just saying its not as dire as the media makes it out to be. Of course a lot of people died. A lot of people are always dying. Never good, but we don't do shit about the rest.
No there are sooooo many things wrong with that assumption.. putting aside anything to do with scaling that figure to the whole population you are forgetting one very fundamental fallacy in your thinking.. its called the False Positive Paradox..
In any disease where the number of people who have the disease is a minority of the population, even if the test for the disease has a very low false-positive rate then when you randomly sample and test the population the **overwhelming** majority of positive results will be false-positives.
this is a more specific form of the Base Rate Fallacy logic: https://en.wikipedia.org/wiki/Base_rate_fallacy
@freemo That's interesting. Never knew false positives could go that high. Does this apply to this test tho? Because these people tested negitive to COVID19, but were had antibodies for it. Are antibody tests also susceptible to false positives? @realcaseyrollins
Every test has some degree of false-positive and false-negatives, yes.
@realcaseyrollins
@freemo So what do you do to account for that? Why are the studies even done if they don't mean anything? That's not meant to be snarky, honest question lol @realcaseyrollins
@freemo So more testing and larger scale testing and different region testing? Seems like that would help @realcaseyrollins
More tests, larger scale, specifically random testing, and case studies (identifying people actively infected and performing the tests on them even though we already know the results).. all of which should give us enough data to get a better idea of things
@obi
It isnt meaningless, you as the math on that link shows if you know the false positive rate, the size of the population, and a few other factors you can calculate the actual number of true-positive tests...
Right now we just dont have enough information to really caclulate that out is all. But this is one piece of the puzzle in getting there.
@realcaseyrollins