What SAGE Has Got Wrong

From Lockdownsceptics.org

16 October 2020

by Mike Yeadon

“It’s Easier to Fool People Than It Is to Convince Them That They Have Been Fooled.” – Mark Twain

Dr Mike Yeadon has a degree in biochemistry and toxicology and a research-based PhD in respiratory pharmacology. He has spent over 30 years leading new medicines research in some of the world’s largest pharmaceutical companies, leaving Pfizer in 2011 as Vice President & Chief Scientist for Allergy & Respiratory. That was the most senior research position in this field in Pfizer. Since leaving Pfizer, Dr Yeadon has founded his own biotech company, Ziarco, which was sold to the worlds biggest drug company, Novartis, in 2017.

Abstract

SAGE made – and continues to make – two fatal errors in its assessment of the SAR-CoV-2 pandemic, rendering its predictions wildly inaccurate, with disastrous results. These errors led SAGE to conclude that the pandemic is still in its early stages, with the vast majority (93%) of the UK population remaining susceptible to infection and that, in the absence of more action, a very high number of deaths will occur.

Error 1: Assuming that 100% of the population was susceptible to the virus and that no pre-existing immunity existed.

Error 2: The belief that the percentage of the population that has been infected can be determined by surveying what fraction of the population has antibodies.

Both of these points run entirely counter to known science regarding viruses and to a significant amount of evidence, as I will demonstrate. The more likely situation is that the susceptible population is now sufficiently depleted (now 28%) and the immune population sufficiently large that there will not be another large, national scale outbreak of COVID-19. Limited, regional outbreaks will be self-limiting and the pandemic is effectively over. This matches current evidence, with COVID-19 deaths remaining a fraction of what they were in spring, despite numerous questionable practices, all designed to artificially increase the number of apparent COVID-19 deaths.

Introduction

The ‘scientific method’ is what separates us from pre-renaissance peoples, who might tackle plagues with prayer. We can do better, but only if we’re rigorous. If an important theory isn’t consistent with the findings it purports to oversee, then we’ve got it wrong. Honest scientists occasionally are forced to accept they’ve gone astray and the best scientists then go back and distinguish what they’ve assumed from what can be shown beyond reasonable doubt.

After nearly 35 years of work leading teams in new drug discovery, and trained in several biological disciplines, I like to think I’ve a good nose for spotting inconsistencies. I was once told by a very senior person who, at the time, was responsible for an R&D budget similar to the GDP of a small country that they’d noticed I did have an outstanding talent for “spotting faint patterns in sparse data, long before the competition did”. I’ll take that. Sometimes I spot inconsistencies in my own thinking (more commonly, it must be admitted, others do that for me); on other occasions it can be about others’ scientific work. This is an example of the latter – specifically, SAGE.

It is my contention that SAGE made – and tragically, continues to make to this very day – two absolutely central and incorrect assumptions about the behaviour of the SARS-CoV-2 virus and how it interacts with the human immune system, at an individual as well as a population level.

I will show why, if you’re on SAGE and have accepted these two assumptions, you’d believe that the pandemic has hardly begun and that hundreds of thousands of people will probably die in addition to those who’ve died already. I can empathise with anyone in that position. It must cause despair that politicians aren’t doing what you’ve told them they must do.

If, like me, you’re sure that the pandemic, as a ghastly public health event, is nearly over in UK, you will probably be with me in sheer astonishment and frustration that SAGE, the Government and 99% of the media maintain the fiction that this continues to be the biggest public health emergency in decades. I have written about the whole event in detail before (Yeadon et al, 2020). Mortality in the UK in 2020 to date, adjusted for population, lies in 8th place out of the last 27 years. It’s not been that exceptional a year from a mortality point of view.

It’s my view that SAGE has been appallingly negligent and should be dissolved and reconstituted properly.

Crucially, I will show that because the proportion of the population remaining susceptible to the virus is now too low to sustain a growing outbreak at national scale, the pandemic is effectively over and can easily be handled by a properly functioning NHS. Accordingly, the country should immediately be permitted to get back to normal life.

…..

Flaws in Imperial College’s Modelling

I will now show you the two, absolutely fatal flaws in the infamous model of Imperial College. There may be other weaknesses, but these two alone are sufficient to explain why SAGE thinks the roof is about to fall in, whereas the wet science, the empirical data, says something entirely different. I believe we could, and should, lift every measure that’s in place, certainly everywhere south of the Midlands. It would probably be fine everywhere, but that’s to step into a firefight that is not needed and would detract from the force of my argument.

What are these two assumptions? They are so basic and alluring that you might need to read this twice.

If you don’t have the stomach to wade through all this, have a look at the two pie charts below.

First, the Imperial group decided to assume that, since SARS-CoV-2 was a new virus, “the level of prior immunity in the population was essentially zero”. In other words, “100% of the population was initially susceptible to the virus”.

You will be forgiven for thinking this surely doesn’t matter much and is a scientific debating point, rather than something core and crucial. And isn’t it a reasonable thing to think? I’m afraid it does matter, very much. Its not a reasonable thing to assume, either. I will come back to this first assumption in a moment.

But before that, the second fatal assumption, which was that, over time, the modellers would be able to determine what percentage of the population had so far been infected by surveying what fraction of the population had antibodies in the blood. That number is about 7%.

Surely, this too cannot be so terribly important? And isn’t it true, anyway? Again, I regret to inform the reader that yes, its absolutely central. And no, its not true.

Read the full article here

HT/Photios