*Government Innumeracy*
<https://lockdownsceptics.org/radical-uncertainty-and-government-innumeracy/>

by James Ferguson

https://lockdownsceptics.org/?s=government+innumeracy
Matt Hancock and his closest advisors receive the latest modelling update
from Prof Neil FergusonAre you positive you are ‘positive’?
<https://lockdownsceptics.org/?s=government+innumeracy#are-you-positive-you-are-positive>

*“When the facts change, I change my mind. What do you do sir?” – John
Maynard Keynes*

*The UK has a big problem with the false positive rate (FPR) of its
COVID-19 tests. The authorities acknowledge no FPR, so positive test
results are not corrected for false positives and that is a big problem.*

*The standard COVID-19 RT-PCR test results have a consistent positive rate
of ≤ 2% which also appears to be the likely false positive rate (FPR),
rendering the number of official ‘cases’ virtually meaningless. The likely
low virus prevalence (~0.02%) is consistent with as few as 1% of the 6,100+
Brits now testing positive each week in the wider community (pillar 2)
tests actually having the disease.*

*We are now asked to believe that a random, probably asymptomatic member of
the public is 5x more likely to test ‘positive’ than someone tested in
hospital, which seems preposterous given that ~40% of diagnosed infections
originated in hospitals.*

*The high amplification of PCR tests requires them to be subject to black
box software algorithms, which the numbers suggest are preset at a 2%
positive rate. If so, we will never get ‘cases’ down until and unless we
reduce, or better yet cease altogether, randomized testing. Instead the
government plans to ramp them up to 10m a day at a cost of £100bn,
equivalent to the entire NHS budget.*

*Government interventions have seriously negative political, economic and
health implications yet are entirely predicated on test results that are
almost entirely false. Despite the prevalence of virus in the UK having
fallen to about 2-in-10,000, the chances of testing ‘positive’ stubbornly
remain ~100x higher than that.*
First do no harm
<https://lockdownsceptics.org/?s=government+innumeracy#first-do-no-harm>

*It may surprise you to know that in medicine, a positive test result does
not often, or even usually, mean that an asymptomatic patient has the
disease. The lower the prevalence of a disease compared to the false
positive rate (FPR) of the test, the more inaccurate the results of the
test will be. Consequently, it is often advisable that random testing in
the absence of corroborating symptoms, for certain types of cancer for
example, is avoided and doubly so if the treatment has non-trivial negative
side-effects. In Probabilistic Reasoning in Clinical Medicine (1982),
edited by Nobel laureate Daniel Kahneman and his long-time collaborator
Amos Tversky, David Eddy
<https://www.cambridge.org/core/books/judgment-under-uncertainty/probabilistic-reasoning-in-clinical-medicine-problems-and-opportunities/661E12D1ECD669EDB5B410407A4BB570>
provided
physicians with the following diagnostic puzzle. Women age 40, participate
in routine screening for breast cancer which has a prevalence of 1%. The
mammogram test has a false negative rate of 20% and a false positive rate
of 10%. What is the probability that a woman with a positive test actually
has breast cancer? The correct answer in this case is 7.5% but 95/100
doctors in the study gave answers in the range 70-80%, i.e. their estimates
were out by an order of magnitude. [The solution: in each batch of 100,000
tests, 800 (80% of the 1,000 women with breast cancer) will be picked up;
but so too will 9,920 (10% FPR) of the 99,200 healthy women. Therefore, the
chance of actually being positive (800) if tested positive (800 + 9,920 =
10,720) is only 7.46% (800/10,720).]*
*Click on the link for the rest.*
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