David Craig, on September 19th, 2020(Sunday/Monday blog by David Craig�- proudly banned from commenting by the Times and Sunday Times for insufficient political correctness such as supporting Donald Trump, supporting Brexit, ridiculing free-speech-hating trans-nazis, calling BLM rioters ‘fascists’, worrying about the uncontrolled Third-World migrant invasion and calling Man-Made Climate Change/Extinction a ‘scam’)
I ain’t no epidemiologist, but….
In fact I hardly know how to spell ‘epedimiologist’. But as the experts howl and scream about the disastrous ‘second wave’ that’s going to kill us all if we don’t immediately shut the economy down completely and all commit suicide, I was starting to do some number-crunching around the issue of ‘false positives’.
Very few medical tests are always 100% accurate. And with a new hastily-developed and hastily-introduced test, like the one for the Wuhan plague, being administered by hastily-trained staff at hastily-constructed test centres and analysed by often hastily-trained staff in many different labs each with their own methods and quality control systems, there’s no way current tests are going to be 100% accurate. From the little I understand, the ‘false positive’ rate is at least somewhere between 1% and 1.5%.
This does NOT mean that if there are 4,000 positives, then 1% to 1.5% (40 to 60) will be ‘false positives’.
Let me explain:
Here comes the complicated bit. I ain’t no statistician but I think the calculation goes as follows (readers are welcome to click on the headline and correct me if I’ve got this wrong):
- Let’s imagine 200,000 tests are done in one day and there are 4,000 positives. That would give 196,000 negatives.
- If there is a ‘false positive rate’ of 1%, then that would give 1,960 ‘false positives’ – 1% of the 196,000 negatives. Thus almost half the 4,000 supposed positives would actually be ‘false positives’
- If there is a ‘false positive’ rate of say 1.5%, then there would be 2,940 ‘false positives’. Thus 73.5% of the 4,000 supposed positives would actually be ‘false positives’
I have a feeling that most people (like Matt ‘Hapless’ Hancock) think the number of ‘false positives’ is derived by applying the ‘false positive’ rate (1% to 1.5%) to the total number of positives – which gives a tiny number of ‘false positives’. But I believe that the correct calculation is to apply the ‘false positive’ rate to the total number of negatives – which gives a massive number of ‘false positives’. I hope that makes sense.
So, if I am right with my calculations and if the ‘false positive rate’ is between 1% and 1.5%, then maybe there is only a slight rise in real infections. But the large increase in tests is giving a large increase in ‘false positives’ making the apparent rise in infections appear much larger than the actual real rise.
Even worse than this is the fact that, as the number of ‘false positives’ is a function of the number of negative test results, then the fewer people who test positive (real positive and false positive) then the greater the number of ‘false positives’ will be as a percentage of all the positive results.
This all means that our statistically-challenged government may be about to trash our economy and impose massive hardship on hundreds of thousands of businesses and millions of families for absolutely no reason at all.
Moreover, if I am right, then the situation may even be more absurd than described above. Let’s assume that general testing reveals an apparent rise in infections in say Bolton. To help quantify and control the apparent rise, our geniuses running the testing system would rush loads of extra testing capacity to Bolton. But if the ‘false positive’ rate is actually 1% to 1.5%, the more people that are tested in Bolton, the more it will appear that infections are shooting up due to the increase in ‘false positives’ when, in fact, the real rise in infections may actually be quite limited.
And then you have questions around whether the tests only pick up the Chinese Covid-19 Coronavirus or whether some people being tested might actually have other Coronaviruses that have been around for years. I don’t know if tests picking up other Coronaviruses are currently included in the official ‘false positives’ infection estimates.
Why do no journalists mention the issue of ‘false positives’ when hyperventilating about how we’re all going to die?
Is the maths too complicated for journalists to report on? (That’s a rhetorical question, by the way).
Of course, I might be completely wrong in the way I have calculated the ‘false positive’ numbers.
But if my maths are correct, and I’m pretty sure they are, then we really are running around chasing our own tails by not separating out the ‘false positives’ from the real infections.
(since I wrote the above, a reader sent me the link below to a report about ‘false positives’. From what little I understand from glancing through the report, this proves my method of calculation of the number of ‘false positives’ is correct. Thus increased testing will give a massive increase in ‘false positives’ as just 1% or even a lower percentage of a huge number of negatives will give a ginormous increase in ‘false positives’ and probably lead to loads more totally unnecessary lockdowns.
Aaaaarrrrggggghhh!
(Here’s the link)
OMG!!!! I’ve just listened to the first 2 minutes of the Julia Hartley-Brewer interview with Health Secretary Matt Hancock that a reader mentioned (link below). Hancock thinks the rate of ‘false positives’ is less than 1% and that the number of ‘false positives’ is calculated by taking that percentage of the total number of positives. Whereas (as I have explained above) he should be calculating the number of ‘false positives’ by applying the percentage ‘false positives’ to the total number of negatives.
By using the wrong way of calculating the number of ‘false positives’ Hancock claims the actual number of ‘false positives’ is tiny. If he had used the correct method of calculation (as I have done above) he’d know that anywhere between 50% to 75% of supposed positives are probably ‘false positives’.
OMG!!! OMG!!! OMG!!!
Category: 
Julia Hartley Brewer has progressed from bedwetter to sceptic and this morning she asked hancock about the false positive rate which he said was less than 1%. You tube video here:
https://t.co/rH0O9RFXSi?amp=1
But according to the gov document, below, they don�t know, but it�s estimated to be between 0.8-4.0% with a median of 2.3%. So 0.8% is the ‘best case’.
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/895843/S0519_Impact_of_false_positives_and_negatives.pdf
Today they processed 233k tests and the cases are moving up almost exactly with the increase in tests.
The plan is to test millions so effectively pushing up the false positive cases into the tens of thousands.
This all with a test that is not designed for this and they are using amplification at a level way beyond the norm.
Julia Hartley Brewer has progressed from bedwetter to sceptic and this morning she asked hancock about the false positive rate which he said was less than 1%.
But according to previous releases they don�t know, but it�s estimated to be between 0.8-4.0% with a median of 2.3%. So 0.8% is the ‘best case’.
Today they processed 233k tests and the cases are moving up almost exactly with the increase in tests.
The plan is to test millions so effectively pushing up the false positive cases into the tens of thousands.
This all with a test that is not designed for this and they are using amplification at a level way beyond the norm.
You are far too intelligent to be allowed to comment on ‘The Times’. Why is it that none of our polies recognise that increased testing produces more cases (real or not), especially when the tests are so non-specific. They have lost the opportunity to build up ‘herd immunity’ during the summer, when there is little danger to most people, and now are trying to open schools/encourage return to work, but have utterly failed to provide an accurate, honest testing programme
Prof Heneghan is my expert of choice and he is worried about basing policy on the increasing number of those testing positive because the test does not say how infectious they are, and apparently they are not being asked about symptoms. It is hospital admissions and deaths that really matter according to him and they have been going down. We are at the start of the flu season to add to the confusion. As the cartoon I mentioned elsewhere says, the latest slogan is – Stay Confused.
Obviously subtracting the ‘false positives’ from the real infections would have to be done to provide an accurate measure of the increases in infections. Dave got the calculation correct. Well done Dave. Moreover, the vast majority of of the positives don’t result in hospitalisations. And most of those hospitalised recover. Therefore, there is no justification for using Covid to shut the economy down.
Any statistician would be able to see that immediately because to become one you need to have a degree in advanced mathematics. There is an increase in positive tests because the statisticians are not adjusting for the false positives correctly. Therefore, whoever is concerned must be pulling the wool over our eyes – wilfully.
I say that all of the constant fear-mongering and false information is designed to herd us into taking the vaccines en masse that were probably already ready before the so-called pandemic hit the world almost at once. – How was that achieved? – By Wi-Fi?
I work in a care home and thanks to our spineless government now have mandatory weekly tests for the Wuhan Pestilence, an indignity I for one resent. We administer the tests to ourselves. BTW the alledged shortage of testing kits – an oversized q-tip in a plastic bag – has not affected us. As we are at the bottom of the health-sector food chain I’m unconvinced by those allegations. Also, all through the ‘shortage of PPE’ media nonsense we had no shortage of any barrier equipment of any kind at any time. All through the lockdown we were plagued by phone calls from companies offering us deals on PPE – so much for the shortages. If only the media actually gathered news instead of inventing it.
This article has just appeared on the same issues
https://principia-scientific.com/tests-positives-up-but-fewer-dead-end-the-lockdowns/?utm_source=feedburner&utm_medium=email&utm_campaign=Feed%3A+psintl+%28Principia+Scientific+Intl+-+Latest+News%29
Your opening paragraph sums up my own opinions completely which is why I read your blogs.
When you look at the graphs of Covid infections and deaths of all countries/cities that imposed lockdowns they are all the same. They start with a rapidly increasing infection and death rate to a peak and then a steady decline to a very low infection and death rate. This is the epidemic period. After this period there is a second rise in detected infections but basically no increase in hospital admissions or deaths. This is the casedemic. If you mark any or all of these graphs with the start of lockdowns and mandatory mask dates you can see that there are no beneficial effects at all.
These graphs were also the same for SARS and MERS. Locking down people and businesses now is a total act of economic vandalism and NOT based on any scientific or historic data.
This is obvious,or should be,to anyone with a brain,willingness to read widely,have a healthy sense of pessimism with regard to politicians and some life experience.This has nothing to do with a relatively mild virus and everything to do with an economic and political reset,world wide.It will take serious resistance to counter the elites who must feel confident that they can pull it off.I am not that confident that the population of the UK is sufficiently aware or has the will to resist.However there are a serious number of ex military with the expertise who could,just could ,influence events.Interesting times,but dangerous ones.More so than the last world war in many respects,as we have many 5th collumnists in positions of power and influence.
David, here is a link to an article that confirms your analysis:
https://lockdownsceptics.org/2020/09/20/latest-news-140/
It concludes: “This test is fatally flawed and MUST immediately be withdrawn and never used again in this setting unless shown to be fixed.”