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..
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...
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..
To mutations & variants. Many viruses are error-prone when they replicate in your cells. They make “typos” so the virus which results is...
Why these incorrect stories are being spun, I’ve no idea, that not being a scientific matter. But spin & completely inappropriate & severe restrictions...
More from Yardley Yeadon
I urge all followers who have read my criticisms of PCR mass testing in U.K. to carefully read Mr Fordham’s carefully worded letter. Note that the innovation minister in the Lords, Lord Bethel, already admitted that the PCR system doesn’t have the equivalent of an MOT. https://t.co/zXzeDMKCBb
Without this information it’s impossible to interpret any result. If the oFPR is 4%, for example, and if the true prevalence is 0.3% (it’s probably less), then for every 10,000 tests, 400 positives would be false & 30 positives would be genuine. So 93% of positives are false.
As Mr Fordham points out, almost all policies pivot on PCR mass testing. Hancock previously admitted on talkRADIO to Julia Hartley-Brewer in late summer that the FPR was “just under 1%”. That was a flat lie (possibly inadvertent but he’s never corrected the record). The reason...
...we are sure Hancock told a lie is that they have never known the FPR. Those including Hancock who believe that the oFPR can be estimated by inspection of the lowest positivity ever recorded, while logical, is completely wrong. Changes in personnel, throughout, testing...
...architecture & the like can radically alter the oFPR. Since Hancock’s remark in late summer, PCR mass testing has moved into the Lighthouse Labs & this creates a new & urgent need to continually assess oFPR. I’ve good reason to believe it’s now VERY much higher now that the...
So I wrote back to @lucyfrazermp for another go. Here\u2019s my letter.
— Edmund Fordham (@EdmundFordham) November 28, 2020
They don\u2019t understand how serious this is.
If they can\u2019t tell us the oFPR, our PCR testing is worthless. (thread) pic.twitter.com/zHJ8SJCzf1
Without this information it’s impossible to interpret any result. If the oFPR is 4%, for example, and if the true prevalence is 0.3% (it’s probably less), then for every 10,000 tests, 400 positives would be false & 30 positives would be genuine. So 93% of positives are false.
As Mr Fordham points out, almost all policies pivot on PCR mass testing. Hancock previously admitted on talkRADIO to Julia Hartley-Brewer in late summer that the FPR was “just under 1%”. That was a flat lie (possibly inadvertent but he’s never corrected the record). The reason...
...we are sure Hancock told a lie is that they have never known the FPR. Those including Hancock who believe that the oFPR can be estimated by inspection of the lowest positivity ever recorded, while logical, is completely wrong. Changes in personnel, throughout, testing...
...architecture & the like can radically alter the oFPR. Since Hancock’s remark in late summer, PCR mass testing has moved into the Lighthouse Labs & this creates a new & urgent need to continually assess oFPR. I’ve good reason to believe it’s now VERY much higher now that the...
@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...
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...
More from Science
Hugh Everett's birthday! Pioneer of the Many-Worlds Interpretation of quantum mechanics. Let us celebrate by thinking about ontological extravagance. I will do so by way of analogy, because I have found that everyone loves analogies and nobody ever willfully misconstrues them.
We look at the night sky and see photons arriving to us, emitted by distant stars. Let's contrast two different theories about how stars emit photons.
One theory says, we know how stars shine, and our equations predict that they emit photons roughly uniformly in all directions. Call this the "Many-Photons Interpretation" (MPI).
But! Others object. That is *so many photons*. Most of which we don't observe, and can't observe, since they're moving away at the speed of light. It's too ontologically extravagant to posit a huge number of unobservable things!
So they suggest a "Photon Collapse Interpretation." According to this theory, the photons emitted toward us actually exist. But photons that would be emitted in directions we will never observe simply collapse into utter non-existence.
The physicist Hugh Everett III was born #OTD in 1930. His \u201crelative state\u201d formulation of quantum mechanics, which we now call the \u201cMany Worlds Interpretation,\u201d was published in 1957. pic.twitter.com/ZqMsZcPJDG
— Robert McNees, the bastegod (@mcnees) November 11, 2020
We look at the night sky and see photons arriving to us, emitted by distant stars. Let's contrast two different theories about how stars emit photons.
One theory says, we know how stars shine, and our equations predict that they emit photons roughly uniformly in all directions. Call this the "Many-Photons Interpretation" (MPI).
But! Others object. That is *so many photons*. Most of which we don't observe, and can't observe, since they're moving away at the speed of light. It's too ontologically extravagant to posit a huge number of unobservable things!
So they suggest a "Photon Collapse Interpretation." According to this theory, the photons emitted toward us actually exist. But photons that would be emitted in directions we will never observe simply collapse into utter non-existence.
@mugecevik is an excellent scientist and a responsible professional. She likely read the paper more carefully than most. She grasped some of its strengths and weaknesses that are not apparent from a cursory glance. Below, I will mention a few points some may have missed.
1/
The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
2/
The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/
The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
4/
The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
5/
1/
I've recently come across a disinformation around evidence relating to school closures and community transmission that's been platformed prominently. This arises from flawed understanding of the data that underlies this evidence, and the methodologies used in these studies. pic.twitter.com/VM7cVKghgj
— Deepti Gurdasani (@dgurdasani1) February 1, 2021
The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
2/
The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/
The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
4/
The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
5/
