UK Government COVID19 Fraud Now Growing Exponentially!
The UK Government is perpetratring a monumental lie during the COVID19 pandemic by declaring that official government policy is that contagions are exponential. No pandemic disease ever recorded has witnessed exponential contagion. This numbers fix is criminality perpetrated at the highest levels of power.
Principia Scientific International is proud to assist fellow citizens access the scientific evidence to expose the lies and misinformation spewed by corrupt government ministers and their scientific and medical ‘experts.’ In that regard, below we share the work of Peerless Reads and their latest video presentation exposes the scam.
Normal Vs Exponential
We are going to attempt to generate a series of presentations focusing on individual points to a level that is sufficiently clear and basic as to support court cases as required.
Our first topic will introduce and distinguish the exponential curve and the normal curve. A great deal has been made of the threat of the virus based on ‘exponential’ growth. It has now been made official by the UK government in the September 21st Vallance/Whitty presentation and by the September 25th Joint Statement both of which explicitly reference ‘exponential’ or ‘continues growing at the same rate’ which is the defining characteristic of exponential.
No contagion ever recorded has been exponential.
However first, let us become familiar with the two critical curves, the normal and the exponential.
Our presentations are targeted at the layman and will avoid math and numbers to the greatest extent possible. By the same token, the slightest familiarity with the curves by a school-leaver mathematician or degree level mathematician will suffice to recognise that we are not presenting difficult or contentious material.
Charts will be developed on Excel using simple formulae and images of such spreadsheets may be included occasionally. For the most part, the end result will suffice as the underlying mechanism will be clear to anyone familiar with Excel. The only formulae used will likely be the Norm.Dist function (normal distribution) and the Power function.
In this presentation we will discuss:
The Nature of Exponential (Mathematical Term)
We start with an example of an exponential curve for daily cases, using figures cited for covid. Doubling every five days” per Ferguson’s Imperial College Covid-19 Response Team Report 9.
We start with a single case.
Doubling every five days is equivalent to 1.15 times per day, or a 15% increase per day. A more exact figure is 1.148698355, which can be derived as =Power(2,1/5) in Excel. For the lay viewer, just ignore that and focus on the 1.15 or 15% per day.
Consider that you will be lucky to earn 1% per year in interest, and may be charged 15% per year on a personal loan, and then consider the power of 15% per day. In 90 days you would owe £250,000 on your £1 loan.
Given how absurd and extreme that would be gives us some indication of why scientists and the government had better have good grounds for using such an outrageously powerful escalation of threat.
They don’t.
Notice the C, G and F (the latter two are reversed vs our previous videos, as we feel it is more intuitive this way). C is the context we’re measuring, here cases, but it could be deaths, hospitalisations, any figure.
G is the growth rate.
Strictly it is an initial growth rate (G0 then, akin to R0 or R nought) but it doesn’t change. That is true of the exponential curve, and here we indicate it by a novel parameter F, the growth- decline factor.
Each day, the Growth rate of the curve is modified by the growth-decline factor.
This is a novel concept introduced by us, but it is simple and extremely relevant. For an exponential curve, the growth doesn’t change so F = 1
Thus on day 5 for example
G5 = G4 x F F = 1
So G5 = G4, the same rate Trivial and pointless right now, but it will be a critical concept in due course.
The curve is labelled as
C.N.Exp
This indicates that it is Cases, NEW (ie: daily figures not total figures) and for the exponential curve.
If we want the Total cases, we add each day’s cases (dotted line) to the previous total (solid line) to get the second curve (solid line, total or cumulative).
It is labelled C.T.Exp for TOTAL cases, exponential.
Notice that we’ve currently limited the chart to 250,000, so the total rises rapidly and reaches 250,000 well before the daily cases reaches 250,000 per day.
If we let the total do its thing all the way out to 90 days (and bear in mind we’re writing this 240 days after the first lockdown, so 90 days is ‘short’ in those terms) then the total reaches nearly 2 million cases, with 250,000 new cases every day.
Of course, that 250,000 cases is still growing. The very next day it’s at 290,000 and the total tops 2 million at 2.225 million (not shown here).
How soon before eg: the UK becomes overwhelmed at 66 million people?
That occurs on day 116, 24th June, if we start on 1st March, not even halfway to our current 25th November date, which would be day 269.
Four months for every human being in Britain to be a covid case.
That’s exponential.
On that day, covid is infecting people at the rate of 9.5 million per day.
Thank heavens for lockdown, the only thing that saved us.
Or did it?
What if the virus was never exponential in the first place?
Bear in mind the 1.15 growth rate (doubling every five days) is the REAL growth rate used by Ferguson in ICCRT Report 9.
1.104 (10% per day, doubling every seven days) was Vallance, 21st September.
No wonder scientists are so ardently tracking R-0. R0 is not identical to but related to our much simpler G, daily growth.
Except, the entire threat, the scare factor, hangs on exponential.
What if it never was exponential?
That’s it for now. I’m Andrew Mather, a 60 y/o Brit, mathematician, financier, technologist, husband, biker, pilot, healer, whatever.
Follow Peerless Reads at www.youtube.com
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Chris
| #
The acceleration, rate, and displacement graphs are the most useful thing taught in calculus. The exponential portion of a displacement graph is the round edge part. It occurs during a change in rate. It is brief. The leg will then be straight which is linear. Then it will round the other way when it stops. It cannot remain exponential for long.
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Charles Higley
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Perhaps an easy, possibly too simple, way to explain why epidemics are not exponential is to explain that the contagion might be increasing exponentially in a population but, at the same time, the number of uninfected individuals is going down exponentially. Thus, you have a relatively straight line upward, a peak, and a linear decline.
The fun part is that they are using the crappy PCR test to pretend that the virus is still around when, in fact, after low case numbers all summer, positive tests are skyrocketing. How can that be?
Well, they claim that one does not have immunity after beating the virus and can get infected over and over, which is completely the opposite of all that is know about infectious viruses.
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tom0mason
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Exponential growth of COVID-19 infections has never been a valid argument, for it willfully ignores the fact that by and large, people have functional immune systems — especially the healthy, well nourished Westerner (the majority of Westerners). Thus although everyone may eventually catch the virus — that is this virus may enter their body — not everyone will be infected by it. For many their immune systems will fight it off before it has a chance to become established or cause any symptoms.
Live long and stay healthy. 🙂
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