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Saved by @Mollyycolllinss

https://t.co/xvP6tVlIaE
Quite a surprise. Ferguson isn’t qualified to comment on such things. He lacks understanding of basic biological concepts, partly explaining why his predictions are often so extreme.

 That said, I’ll take him as an ally. It’s clear we’re already at herd immunity. How can I be sure? London had a huge peak of excess deaths in spring. The timing of peak deaths showed clearly that the pandemic was self-limiting. Recall much debate about whether the interval...
...between lockdown & peak deaths was long enough for lockdown to have been the cause of reducing deaths? The answer was “no”. But it was close & I can understand people thinking “well, it’s close, so perhaps it was lockdown that did it?”, thereby establishing a foundational...
...myth favoured by those who genuinely believe lockdown saves lives (it clearly doesn’t).
I’ll get to London & here immunity. But those wavering about the evidence about lockdown in spring really will benefit from cogitating on this graph.
In blue are the 30 trusts with the earliest date of peak deaths in spring. In red, the 30 with the latest peak deaths. For me, this is proof that national lockdown, which began Mar 23, played no role whatsoever in turning the pandemic. You’ll see some areas had peak daily...
...deaths numbers occur before lockdown. Others so close to lockdown that obviously the intervention was far too close to peak daily deaths that lockdown can’t even have contributed to turning the pandemic. Even harder for pro-lockdown folk is the marked range in dates of peak...
...daily deaths across the country. The lockdown thesis is that this intervention sufficiently reduced social contacts that the spread of the virus was abruptly slowed & that pushed Rt below 1. That’s what saved us. But if that was even close to what happened, the dates of peak..
...daily deaths would be close together in time, perhaps a few days variation. That’s not what we see. Looking at the trusts with earliest to latest peak daily deaths we see variation of a whole month. Furthermore, the trusts with earliest turning points are mostly London and...
...those with latest turning points furthest from London. I can conceive of no crisper evidence that (1) lockdown was not responsible for turning the spring pandemic & therefore (2) something else was responsible for the abrupt turning of the pandemic. As yet, no one, not SAGE...
...nor anyone else has come up with an explanation for this data that doesn’t involve a rapidly reducing proportion of the population who remain susceptible to the virus, aka herd immunity.
What this means is that almost all of U.K. experienced what’s called unmitigated...
...spreading of the virus. Just like Sweden. It’s not surprising then that we’ve ended up with identical population fatality (0.08%).
Back to London. Three months ago, I wrote a detailed article which contained several predictions.
https://t.co/b0rT5Lq9HI
At the heart of things, I laid out why SAGE’s advice to Govt was seriously in error. If SAGE was correct, we’d expect the pandemic to resume in a similar pattern to spring, the deaths to increase in the typical respiratory virus pattern of a clear spike & importantly for excess..
...deaths in London to be marked (it was the epicentre in spring). For this next part, I recommend we set to one side for a moment the label “covid19 deaths”, because there’s some controversy about the reliability of PCR mass testing. Prof Whitty himself guided us to look at...
...excess deaths as the best indication of progress of the virus. So let’s do that. London has not had excess deaths at all this autumn & winter. That means SAGE was flatly wrong & without crowing it turns out I was closer in my prediction. Here’s the official data. Note that...
...the data is sufficiently sensitive a record to pick out the deaths associated with the August heatwave. But the daily deaths are not greater than the five year average all the way through autumn & winter. I agree with Prof Ferguson. But he’s months off the pace. The data...
...was unequivocal that SAGE’s narrative has been demonstrably wrong by early summer last year. Once it’s realised that lockdown 1 wasn’t the force that turned the pandemic in spring, lots of other things we’ve been told cannot be true. I’m willing to ascribe their errors to...
...ignorance. They didn’t have an immunologist on their team in spring. So what is obvious to me might not even have crossed their minds or entered into their mathematical models.
SAGE’s errors unfortunately have been compounded & their mistaken narrative is gradually destroying
...the country in every way. Remember the other predictions I made & how they contrast with reasonable inferences from SAGE’s position? I predicted what I termed a #SecondaryRipple which was characterised by regional outbreaks which would be self-limiting & overall excess...
...deaths rather modest compared with spring. Again, let’s follow Whitty’s advice to be guided by excess deaths & not labelling of cause of deaths (because total deaths is agreed to be objective). What we’ve seen in autumn & winter is a slow ramp of excess deaths. This is...
...because each mini outbreak is uncoordinated in time across the country. And the total excess deaths has been small compared with spring. In fact, recent PHE weekly reports have shown low to no excess deaths.
This is completely consistent with national herd immunity, with local self limiting outbreaks possible but impossible to see a widespread & growing epidemic. Note that official data shows there is no public health emergency due to the virus. I’m not going to get into the whole...
...business of misattribution of cause of death due to untrustworthy PCR mass testing again (yesterday’s thread covered that). Please follow Whitty’s advice & be guided by excess deaths. Once you do that, the whole position is seen for what it is: a reality in complete contrast..
...with the narrative of fear. I’ll close by again encouraging those at elevated risk of severe outcomes from the virus to consider getting vaccinated. It isn’t wise to do so if you’re not at elevated risk. I also repeat my demand that mass testing of the population ceases. It...
...is simply not necessary & because of unknown unreliability, I believe it’s main product is false positives, fear & superfluous ‘control measures’ which don’t work, while hurting everyone.
If anyone on SAGE reads this, please look to your conscience & alter course.

More from Yardley Yeadon

Yardley Yeadon
Yardley Yeadon
@MichaelYeadon3
In a number of Sunday papers:
Scientific advisers said it was “hard to see” when the restrictions would end as new variants continued to emerge, delivering a potentially devastating blow to the travel industry. The prime minister said that after progress with vaccinations...

...”what we don’t want to see is all that work undone by the arrival of a new variant that is vaccine-busting”.
The idea is planted in people’s mind that this virus is mutating in such a way as to evade prior immunity. This is completely unfounded, certainly as regards immunity..

...gained naturally, after repelling the virus (which well around 99.9% of the population do, fewer, obviously in the very elderly & already ill, more in those younger & well). It’s important to appreciate that upon infection, the human immune system cuts up an infectious...

...agent into short pieces. Each of these short pieces of protein are presented to other cells in the immune system, like an identity parade. Our cells have a truly astonishing range of abilities to recognise different protein structures, and there will be some which recognise...

...each of the pieces of the invader. The cells which recognise a piece are instructed to multiply selectively so that, after a few days to a couple of weeks, our bodies contain large numbers of virus piece specific cells. These have a range of functions. Some make antibodies...
SCIENCE
Yardley Yeadon
Yardley Yeadon
@MichaelYeadon3
@ukiswitheu I invite people to run the thought experiment: “what if the ‘cases’ data is inaccurate?”
Ignore ‘cases’, look instead only at excess deaths (per M Levitt’s tweet). Does that look characteristic of an epidemic? It’s completely diff from spring or any winter flu outbreak.
London:


Can anyone explain why there is no ‘2nd wave’ of excess deaths in London, without invoking herd immunity?
It’s not lockdown. See NW England:
This is the largest #SecondaryRipple (which I predicted).


https://t.co/b0rT5Lq9HI
Now check the 3 predictions I made months ago. They’ve all happened. Compare predictions from SAGE’s statements: they’re all wrong.
Even neutrals at this point might ask themselves “if he’s been right on all predictions, maybe he’s correct now?”


I’ve been saying since the Lighthouse Labs got up & running that I’m deeply sceptical about the trustworthiness of their ‘cases’ data. I showed how, at low virus prevalence, the PCR mass testing data was throwing out potentially 90% positives being

https://t.co/t4qQN4rH0u
I got ‘fact checked’ a LOT over that statement. This paper just published, about precisely that time period I speculated about. Turns out that high-80s% of Dr Healy’s positives by PCR were FALSE. This alone is sufficient in my view to throw severe doubt...
FOR LATER READ
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Yardley Yeadon
Yardley Yeadon
@MichaelYeadon3
@scottorandojin What if the false diagnosis rate was 90%?
Don’t misunderstand me. I’m a thorough believer in the existence of this virus.

To exemplify: the NHS is under severe winter pressure. Many staff are unavailable, largely due to forced isolation from testing. Also, I’m told the adaptations to the conditions make normal work almost impossible. Trying to keep apart patients in different categories must be...

...incredibly stressful. I doubt I could ever have coped. Add to this the real stream of sick people & it’s a complete nightmare. My sympathies won’t be accepted but I offer them anyway. As to “the deaths”, do you mean the reported count of “covid19 deaths”? Everyone is doing...

...their very best. But as to that count: it’s nothing to do with clinical judgement. A covid19 death is a death from any cause within 28d of a positive test. So once a person is labelled by a positive test, if they then die, they’re a covid19 death. Back to my substantive...

...question: how reliable is that labelling? It’s not a clinical diagnosis. We’re not used to this idea. Never before in medical history has someone had a disease (let alone cause of death) been defined by the result of a single year alone. Yet that’s where we are. I think that..
HEALTH
Yardley Yeadon
Yardley Yeadon
@MichaelYeadon3
Postcard From Luxembourg: normality is restored prior to vaccination.
I’ve repeatedly said that “test, test, test” is madness, if the tests are unregulated. Why?
‘Because pandemic’, NO PCR mass testing has a declared operational false positive rate.

So we don’t know the oFPR of PCR mass testing in U.K. This is conducted in a small number of private labs, set up at pace in summer, anticipating a ‘2nd wave’ (itself a dubious prediction from the Imperial team who’ve been wrong every time before). You’d assume these “Lighthouse

...Labs are surely regulated, inspected, accredited etc. They’re doing the most impactful medical diagnostic testing which has ever happened in history. But no. None of these are true. ‘Because pandemic’. Now, I don’t know the oFPR either. But we’re paying for it. It is NOT ZERO.

However, the authorities take every positive result as a “confirmed case” (though there’s nothing confirmed). There is no open protocol you can examine & debate. None of the results are available for understanding, thinking & interpretation. Wouldn’t it be important to learn...

...how the distribution of cycle threshold for positives varies through a run of tens of thousands of samples? Or through time? Or across geography? There is no routine evaluation of the characteristics of the test, even though we know the oFPR of complex systems is subject to...
SOCIETY
Yardley Yeadon
Yardley Yeadon
@MichaelYeadon3
@DesmondSwayne Sir Desmond is right. SAGE makes mathematical predictions based on flawed models.
I chose to stick my neck out almost 4mo ago here:
https://t.co/b0rT5Lq9HI
I experienced much anxiety doing this, aware that, if I was badly wrong here, I would be destroyed as a contributor.

That said, I thought the immunology so clear that I made three, specific & testable predictions which should apply if I was right.
Please examine them, on the right, under the pie chart:


In particular, I predicted that the epidemic would not reignite in London. Obviously, we have many “cases” but I urge people to disregard these & instead to look at excess deaths, on the principle that a severe (occasionally lethal) respiratory virus would show itself this way.

Here is a chart showing the trend of deaths in London alone over recent years. A prominent peak of deaths is evident as the virus swept through in spring. Also visible the August heatwave. But there are no excess deaths now.
I submit this is a striking example of herd immunity.


I’m still waiting for SAGE or indeed anyone to provide an alternative explanation for the sharp nature of the spring excess deaths peak which doesn’t involve herd immunity or otherwise removing from the pool those vulnerable to lethal outcomes (same result). Given this sharp...
MATHS

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Warren C.\U0001f1fa\U0001f1f8 45th POTUS = G.O.A.T. \U0001f1fa\U0001f1f8 \u271d\ufe0f
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💥💥 Situation Update, Dec. 7th – DNI John Ratcliffe, the bogus science of PCR testing and China’s GMO super soldiers

✅ I cover the bogus science behind PCR testing, explaining from a lab science point of view why no PCR instrument can “quantify” anything,
[M. Adams]


1. whether it’s a coronavirus viral load or the percentage of a food that’s GMO. In fact, literally all the tests currently conducted with PCR equipment are scientifically invalid when it comes to diagnosing illness or determining infectiousness. The sample acquisition used for

2. PCR tests — nasal swabs — aren’t even standardized! (100% bogus junk science).
After covering PCR tests, today’s update then goes into detail about Director of National Intelligence (DNI) John Ratcliffe, pointing out that he will be issuing a report on foreign interference

3. in U.S. elections on or before Dec. 18th. If this report confirms the existence of foreign interference that was capable of altering the outcome of the election, it gives President Trump full justification to declare the election null and void and dispatch military troops

4. to seize all ballots and hold a new count under military authority.

👉 Podcast notes and sources:
The office of military commissions has cleared its calendar for December:
https://t.co/u4nFRiUj8m

US military STOCKPILED Pfizer’s mRNA vaccineBEFORE it was approved by theFDA
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10-K Diver
10-K Diver
@10kdiver
1/

Get a cup of coffee.

In this thread, I'll help you understand the basics of Binomial Thinking.

The future is always uncertain. There are many different ways it can unfold -- some more likely than others. Binomial thinking helps us embrace this view.


2/

The S&P 500 index is at ~3768 today.

Suppose we want to predict where it will be 10 years from now.

Historically, we know that this index has returned ~10% per year.

If we simply extrapolate this, we get an estimate of ~9773 for the index 10 years from now:


3/

What we just did is called a "point estimate" -- a prediction about the future that's a single number (9773).

But of course, we know the future is uncertain. It's impossible to predict it so precisely.

So, there's a sense of *false precision* in point estimates like this.

4/

To emphasize the uncertainty inherent in such predictions, a better approach is to predict a *range* of values rather than a single number.

For example, we may say the index will return somewhere in the *range* of 8% to 12% (instead of a fixed 10%) per year.

5/

10 years from now, this implies an index value in the *range* [8135, 11703]:
SCIENCE
James Hay
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@jameshay218
Ct values can be used to estimate epidemic dynamics UPDATE! Ct values are expected to change depending on whether the epidemic is growing or declining, and we harness this to estimate the epidemic trajectory. Lots of cool new analyses and methods!

Highlights:
- Cts from symptom-based surveillance change over time, but the effect is weaker
- Methods to infer incidence using single cross-sections of Cts
- Unbiased by changing testing coverage
- Gaussian process (wiggly line) model for incidence tracking using Ct values
2/12

This work is *JOINTLY led* with @LeekShaffer and PI’d by @michaelmina_lab. Thank you also to the ever insightful @mlipsitch and to coauthors @SanjatKanjilal @gabriel_stacey and @nialljlennon. 3/12

Premise: times since infection depend on the epidemic trajectory. Distributions of randomly sampled viral loads proxy times since infection. With calibration, Ct values can estimate growth rate. We focus on qPCR in SARS-CoV-2, but the principle applies to any outbreak. 4/12

Result 1: viral loads are shifted higher (Cts lower) during epidemic growth and lower (Cts higher) during decline when individuals are sampled *based on the onset of symptoms*. We simulated linelist data under symptom-based surveillance and looked at TSI and Cts over time. 5/12
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Carlos E. Perez
Carlos E. Perez
@IntuitMachine
It is astonishing that most of cognitive science ignores an obvious reality. That there are two kinds of humans.

Tomasello has a very credible hypothesis that what distinguishes humans from the great apes is the inclination towards shared intentional behavior. What is innate is the disposition and like personalities, it is what defines our cognition as we grow.

If cognitive preference is so critical in cognitive development then why is it that we seem to have completely ignored the difference in cognitive preferences between men and women?

Humans are that species of primates that wandered out into the savannah. The savannah is different enough from a dense jungle to exert the evolutionary pressures that encourage the development of planning and forecasting skills.

Furthermore, human infants required a disproportional amount of effort to rear. This meant the specialization of roles between women who were responsible for rearing offspring and men who were responsible for bringing home the bacon. Failure in either implied death.
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