20th March 2021 — Dr. Malcolm Kendrick
What figures about COVID19 do you believe?
Indeed, what figures can you believe?
Do you simply take them all at face value, and work from there? That would certainly be nice, but it’s not really possible, and you would come to some pretty weird conclusions.
For example, I was running through the Worldometer site the other day. Yes, what an exciting life I now lead. Sitting right on top to each-other, on ‘deaths per million’ of the population were: Singapore, New Zealand and China. They are way down towards the very bottom of the list.
Deaths per million
- Singapore (188) = 5 deaths per million (total deaths 30)
- New Zealand (189) = 5 deaths per million (total deaths 26)
- China (190) = 3 deaths per million (total deaths 4,636)
Just to give you a quick comparison with countries rather closer to the top of that list, where the deaths per million are around four hundred times higher, on average:
Deaths per million
Czechia (3) = 2,206 deaths per million
UK (6) = 1,843 deaths per million
USA (12) = 1,649 deaths per million
Returning to Singapore, New Zealand and China. What do they have in common? From a COVID19 perspective they all locked down pretty hard. At least they say they did. They are all pretty wealthy countries. Apart from that… not much.
On the surface, there is nothing much to get excited, or confused about, yet. However, when you start looking a little more closely, you begin to notice stranger things. For example, if we look at total ‘cases.’
Total COVID19 cases
- Singapore = 60,121
- New Zealand = 2,432
- China = 90,062
So, China with a population of 1.4Bn (One billion, four hundred million) had ninety thousand cases. Singapore with population of just over five and a half million, had sixty thousand cases. Just in case you cannot do the mental arithmetic. Singapore’s population is two hundred and forty-six times smaller than China’s.
Which means that Singapore had two thirds the number of cases in China – resulting in almost the same rate of deaths per million but in a population two hundred and fifty times smaller.
Where does this then take us? It takes us to a place where the case fatality rates are widely different. Not just between China and Singapore, but in all three countries. In fact, these figures are not even in the same ballpark. Not even in the same city. By case fatality rate (CFR) I mean the percentage of people with a clear-cut infection, who then died [terms and conditions apply].
Here are the resultant case fatality rates from the three countries, in order.
Case fatality rates
China = 5%
New Zealand = 1%
Singapore = 0.05%
Which means that, using the figures provided, the case fatality rate from COVID19 is one hundred times higher in China than in Singapore. Or, to put it another way, you are one hundred times more likely to die if you get COVID19 in China than in Singapore.
On the other hand, you are only twenty times more likely to die in New Zealand than in Singapore. So, should we all rush to Singapore and find out what on earth they can be doing to cure so many people. Or….
Yes, you’re right. These figures simply do not add up. Not even remotely. Medical interventions, sadly, have made very little difference to mortality rates from COVID19. A few percentage points here or there. So that cannot even remotely explain such massive differences.
What is the other explanation? It is, and can only be, that we cannot possibly be comparing like with like. Which, in turn, means that the figures in one, or all of these countries, are so incomplete, biased or wrong, as to be utterly useless.
Are they missing cases, or not counting cases, or defining cases and deaths from COVID19 in completely different ways? Whichever of these is true it doesn’t really matter. The only thing that really matters is that at least two of these three countries are reporting figures that are of absolutely no use to man nor beast. Perhaps all three.
Equally, if you’re planning what do to next in this pandemic, you must have figures that you can trust, otherwise you are simply floundering about in a sea of confusion. What’s the other choice. Delete the statistics from the countries where you simply do not believe them. And where would you start with that?
There is a military strategy called OODA: Observe, Orientate, Decide Act. It was used in the Gulf War, and by Dominic Cummins to achieve victory in the Brexit referendum – so it is claimed. It sounds simple, but it actually becomes complex, quite quickly.
With COVID19 you can observe all you like, and I have done a lot of observing. However, if the data you are looking at are clearly nonsense, it becomes impossible to orientate. Then, in turn, it becomes impossible to decide how to act.
It is why, up to this point, I have mainly contented myself with pointing out that the data that we have been presented with thus far is almost perfectly meaningless. Let’s consider another example. Which is that the gold standard for diagnosis of COVID19 is to use a system known as PCR (polymerase chain reaction). We do not use symptoms, or clinical signs, as has been the case for all other diseases known to humanity over the ages. A major problem in itself.
Another major problem is we know that if you run PCR test processing for forty-five amplification cycles, the results become entirely meaningless. No-one will officially provide the data on how many cycles are being done. But it does seem that, in the UK at least, many labs were using forty-five cycles.
Now, the numbers of cases are falling, they have reduced PCR processing to thirty cycles. But, who knows? Perhaps it is because they have reduced PCR to thirty cycles, that the cases have gone down. Or maybe it is the fact that we are using millions of lateral flow tests which has led to the number of positive tests falling. Because you get far fewer positive results with lateral flow kits than PCR.
In addition to that area of confusion and conflict, recorded deaths from COVID19 in the UK are based on having a positive test within twenty-eight days of dying. Yet we know that COVID19 tests can remain positive for months after someone has recovered. So, you can have had a positive test in November, go into hospital in January – for whatever reason – where you will have another test, that has remained positive. You then die of something completely unrelated. You become a COVID19 death statistic. What nonsense.
Even if you truly have COVID19, then die, how do we know if the main cause of death was COVID19, or something else? I have seen terminally ill patients close to death from cancer, or suchlike, who have had a positive swab. They then died, and they became another ‘COVID19 death.’ Really? Is that what killed them?
We do know that at least ninety-five per-cent of people who are recorded as dying of COVID19 had other serious medical conditions. Claiming that COVID19 was the primary/recordable cause of death in all of these cases is just ridiculous. Beyond ridiculous.
Frankly, anyone who asks me to trust in any data about COVID19 is going to have a pretty tough sell. Right now, I feel that there is almost no statistic which has not been wildly bent out of shape to suit the narrative.
At this point, I shall change direction slightly, and point you at the most incomprehensible statistic of all.
It comes from the UK. In this data set, the UK has been split into four countries. England, Northern Ireland, Scotland and Wales. Here, we are looking at the figures on overall mortality – that is deaths from all causes – during the period January 1st, 2017 up until the present day. These data cover the age group of forty-five to sixty-four (I set the graphs to specifically show this age group).
What you would expect to see, I think, is that all four countries that make up the UK should show almost exactly the same pattern of deaths. All four countries are virtually identical in their demographics, life expectancy, and suchlike. All four countries ‘locked down’ in almost exactly the same way, at almost exactly the same times.
Below, are the figures (z-scores/deviation from the mean) on overall mortality. https://www.euromomo.eu/graphs-and-maps#z-scores-by-country
We can see an enormous spike in England in the forty-five to sixty-four age group in Spring 2020, and Autumn/Winter 2021. We observe nothing, or virtually nothing, in the other three countries.
Just in case you are wondering. I do believe in these overall mortality data. If someone is dead, they are dead. It is difficult to misdiagnose or diagnose in any other way. So, these figures represent the real deal.
Observe, orientate, decide, act.
I observe that overall mortality rates went up sharply in England in the spring of 2020 and again in the autumn/winter of 2020/21 in the age group 45-64. I observe that the rates barely moved in Northern Ireland, Scotland or Wales.
Something of great significance happened in England, that did not happen in the other three countries. I cannot orientate, because I have absolutely no idea what these figures are telling me.
These data, unremarked open by anyone else – as far as I am aware – are trying to tell us something. Something that may well be of absolutely critical importance. These are the figures that we should be using to base our decisions and actions upon. If we could only understand what they were telling us.
There is one other country which has a pattern similar to England’s, and that is Spain.
Nowhere else looks remotely similar. For example, here is Sweden.
What have England and Spain got in common? Or, at least, somewhat in common?
Do not decide anything until you are orientated. In turn, do not act until your decision is made on a good understanding of the environment you are operating in.
Do not decide what to do until you can explain why, for example, China has a case fatality rate that is one hundred times higher than in Singapore.
Equally, you cannot possibly claim to be orientated until you can explain why England, alone of all the countries in the UK, suffered such massive spikes in overall mortality in the forty-five to sixty-four year age groups.
In super-short summary, until you can rely on the figures that are provided from around the world, you cannot claim to be orientated.
Our glorious political leaders have decided that they are, indeed, oriented. Because of this false orientation, they have made decisions and acted. Based upon foundations of, precisely, nothing.
So, what are the odds that they acted in the right way?