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9,662 Views· 08 Jun 2020
Truth Warrior

Dr Birx - HALF (or more!) of #Covid tests that test positive are likely to be #FalsePositives.

US ADVISOR Dr Deborah Birx warned you can not assume the Covid test positive result is correct - it is likely to be wrong most of the time - a "false positive".

She says:
"If you have 1% of the population infected and you have a test that is only 99% specific, then if you find a positive, then 50% of time it will be a real positive and 50% of time it won't be! [ie, it will be a false positive]".

See full 1.5 hr video for context. Segment starts at 52m37s:


Update: CDC FINALLY admits it too (regarding antibody tests but same problem for PCR).
#CDC competent??

CDC know this well but did not admit it for months:

All these false positives are not obvious but here's why:

Specificity: probability that a test will be negative when the disease is absent.
Sensitivity: probability that a test result will be positive when the disease is present.

The key factor is PREVALENCE, eg, "If you have 1% of the population infected ".

Birx: “None of our tests are 100 percent sensitive and specific."
Video: https://lnkd.in/gHhCPwd

And Birx says so here:

A test with specificity of 99% is unrealistic, as in Birx example. But let's assume her numbers are realistic...

Check Dr Birx's numbers for yourself here with a test calculator that does the complicated probabilities math for you (Bayesian stats).


Here's a calculator and follow steps below.

Enter data:
Disease present (Sensitivity 99%): 1, 99 (although a more typical value as used in another version, the NPR calculator below, would be 90%, or 10, 90);
Disease absent (Specificity 99%): 1, 99 (Dr Birx's unrealistic/optimistic value for an almost perfect test);
Prevalence: 1% (Dr Birx'x example for the population prevalence).

Results (Birx example):
True positives: 50% (ie, 50% of those with a result of "positive" will be truly positive for virus markers - they "have" the virus)
False positives: 100 - 50% = 50% (ie, 50% will be FALSE positives - their positive result is false! They likely do NOT truly have the virus).

Tests are more likely to have only 80 - 85% specificity.

Reduce to a more realistic test specificity of 85% (15, 85), and sensitivity 90%, prevalence 1%...

Then you get:
True positives: 5.71 = 6%
False positives: 100 - 6 = 94%
Over 90% are wrong results!

Because the test was developed using a test-tube with 100% virus prevalence as the standard, then as prevalence INCREASES (more true cases in population), the test becomes MORE reliable (but not by much):
If California has, say, 5% prevalence, then above calc (85% specificity) becomes:
True positives: 24%
False positives: 100 - 24 = 76%
76% of positive tests would be FALSE and wrong - about three quarters are wrong.
Another calculator here (from NPR) - cross-check:
"If you used a test with 90% specificity in a population in which only 1% of the people have it...more than 90% of the positive results would be false positives."
Article + calc: https://lnkd.in/gVyKtUb
It says "antibody test" but it applies to any test including PCR swab.

A very easy read and example explanation:
Today’s riddle: A 99% accurate medical test is wrong half the time. Why?
More good videos explaining false positives, and antibody testing:

The Covid test is reliable for true negatives (eg, 99.5%) so if you don't have the (signature of) the virus, the test will reliably tell you that. But it extremely unreliable for positive tests if prevalence is low (eg, 1-5% of popn actually have it). The poor reliability and imperfect sensitivity and specificity of the PCR test (or any test) is a serious issue that undermines their entire narrative of "test test test!" and uses misleading results to justify questionable policy. This is astounding and is not understood or even discussed enough.

#Birx #Covid #FalsePositives #Coronavirus #Pandemic

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PanAdmin 7 months ago

"highly infectious" utter bulls*it

2    0 Reply
Truth Warrior
Truth Warrior 12 months ago

Of course. Endless lies what do you expect? It’s all lies. One big hoax and yet still people cannot see this? We went from 50% false positives back in May to 93% false positives now but the same test. Notice the pattern of lies? Lol

2    0 Reply
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