re: Antibodies ...why are they not getting any love?

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I've seen it.

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I doubt it

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Depends on combination of sensitivity, specificity, and true prevalence. Do you know what these words mean?

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You're yet another TD poster with a Bayesian fetish?

Because Orange Man Bad.

Notice a correlation?

HCQ+ has been successful treating COVID-19 patients in multiple studies on 4 continents. If the treatment is started early.

Media and libtards dismiss those and lock on to one study that gave HCQ to patients on vents and close to death. That study had poor results, shocker!

Now we have antibodies testing from 2 of the top universities in America, plus several from abroad, all showing that the true infection rate is 10-80 times higher. Meaning WuFlu has been here since November-December and that the real mortality rate is significantly less than 1%

These people have a mental disease or they truly hate America. Or both.

They can't stop what is coming. Freedom. MAGA rallies. A November slaughter. 4 more years of OMB.

Deal with it. There is not going to be a 2nd shutdown.

Decent read from a couple weeks ago (which is a year or more in COVID time):

NY Times

I accidentally closed the tab on my phone. I'll add an excerpt. Discusses previous coronaviruses and acquired immunity studies.

ETA:

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In the first study, researchers selected 18 volunteers who developed colds after they were inoculated — or “challenged,” as the term goes — with one strain of coronavirus in 1977 or 1978. Six of the subjects were re-challenged a year later with the same strain, and none was infected, presumably thanks to protection acquired with their immune response to the first infection. The other 12 volunteers were exposed to a slightly different strain of coronavirus a year later, and their protection to that was only partial.

In another study published in 1990, 15 volunteers were inoculated with a coronavirus; 10 were infected. Fourteen returned for another inoculation with the same strain a year later: They displayed less severe symptoms and their bodies produced less of the virus than after the initial challenge, especially those who had shown a strong immune response the first time around.

No such human-challenge experiments have been conducted to study immunity to SARS and MERS. But measurements of antibodies in the blood of people who have survived those infections suggest that these defenses persist for some time: two years for SARS, according to one study, and almost three years for MERS, according to another one. However, the neutralizing ability of these antibodies — a measure of how well they inhibit virus replication — was already declining during the study periods.

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What is you background in science? Do you have any formal training in microbiology and clinical laboratory?

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Seems unlikely

If the test isn't 100% accurate certainly there is some possibility of a false negative

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If the antibody that the test is looking for is present, the test will show positive. It is what the test does.

The errors show when a different/similar strain is present but the test recognizes it as antibodies for sarscov2 and reports the false positive.

The only false negative would be testing for antibodies too soon after infection before the antibodies are built up and present. Since the antibodies aren't present, by definition it isn't a true false negative despite incorrectly pointing the individual as a prior infection.

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I was incorrect in the percentage. Thanks for pointing that out. Right now .35% of americans have tested positive.

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You weren't off by a little. You were off by a factor of 100. Remember, this was "basic math" by your own words.

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How so?

Right now, .0035% of Americans have tested positive. Let's say that the real number is 100 times greater than that.

Let's give the test to 102 people.
Out if 102 people, by percentages only .36 people have covid. Let's round that up to 1 with covid. And there would be 1 false positive at 99% accuracy.

You have netted a 50% accuracy with me making some very generous presumptions in favor of the testing.

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How about you repost this without your "accidental" mistake.

The point of the post is how a 1% error in testing results makes the results untenable to policy decisionmaking.

The positive test results on the molecular and serologic testing aren't even a part of the equation.

The relevant factors are the true infection rate and the percentage of error in the antibody testing.

You are barking up the wrong tree. I can admit a mistake. Especially in a factor irrelevant to the discussion.

Can you admit that 1% error is not satisfactory for these purposes?

Wow. Here you go.

We presume the actual infection rate is 2.5% (per the study). The accuracy is 99% (per the study).

If you test 1,035 people, then you have 25 true positives and 10 false positives. The false positives are as much as 40% of the true positives. Just like the last time I did the figures 2 hours ago.

As I said, the positive serology and molecular tests (.35% of the US population) are irrelevant to why the 1% error is too big to make policy decisions. And that assumes that the test accuracy isn't between 90-95% accurate which is exponentially worse (exponential... you know?).

So I ask again, is a 99% accuracy on the antibody testing good enough for policy decisionmaking?

Your example uses an awfully small sample of 1035 people.

Ramp that up to 1 million. 2.5% sick would give 25,000 sick. From that if 99% accurate, you would get 24,750 true positives and 250 false positives. This would seem reasonable to base decisions from.

This is what I was trying to tell texrider, but he failed to grasp the concept.