Are we having a second wave? Of stupidity, yes.

Are we having a second wave of COVID-19? No! We haven’t even finished the first wave yet, and a second wave – if it happens, which it won’t* – wouldn’t start until winter.

So, why did Matt Hancock tell us we are?

Because the UK government and their advisors are scientifically illiterate.

* You’ll need to read the whole article to find out why, but I promise it’s worth it.

Science and literacy

Matt Hancock is a highly intelligent man, educated at one of the world’s leading universities, but his BA in Philosophy, Politics and Economics from Exeter College, Oxford, and his MPhil in Economics does not make him scientifically literate. How could it? This is quite clear from his bizarre interpretation about what is happening which is scientific nonsense. Blunt? Harsh? Yes, perhaps, but then again he is scientifically illiterate and making terrible, terrible mistakes. Only a science education in the appropriate sciences could make him literate. That’s how education and literacy works.

The Good, the Bad and the Ugly

Governments internationally continue to chase red herrings, reporting and reacting to “detected infections”, and in doing so, creating panic and hysteria, untold economic damage and inumerable deaths – almost ALL of which has been entirely unnecessary and avoidable – if only they had paid attention to good science.

Unfortunately, there seems to be an almost ubiquitous dis-ability to distinguish good science from bad science, and either from complete nonsense. No-one would expect the general public to have this ability, but it’s deeply troubling to see this at goverment level.

“Detected infections” is a meaningless metric.

I repeat: “Detected infections” is a MEANINGLESS metric.

EVERYONE, PLEASE STOP USING IT, READING ABOUT IT, AND SPREADING MISINFORMATION. It cannot be interpreted meaningfully and it should never be used to guide policy or strategy. That. Is. Insane.

It tells us nothing useful about actual infections, nor how dangerous a disease currently is. The fatality rate of COVID-19 is not a constant but varies over time and place enormously in response to changing conditions.

Deaths is a meaningful metric, despite some uncertainty around reporting, it is one of the most reliable metrics we have and usually comes from hospitals.

Recoveries is also meaningful, so long as it’s coming from the same source so we can compare like for like.

However, there are better metrics available.

Angels and Devils

Absolute (as opposed to relative) values for deaths and recoveries are useful within countries or states but since these depend on things like population, population density, economic factors, transmission rates (which can change enormously on a daily basis) etc. etc. we cannot compare these with other locations unless we make very complex adjustments.

There are lots of ways to adjust if you know all the various influencing factors, but we actually don’t know what all those factors are.

However, there’s also a neat trick which allows to sidestep this need completely.

Dimensionless entities

A dimensionless number is a concept from physics.

Roughly speaking, dimensions are units – things like metres, seconds, and so on and combinations like metres-per-second, virions per litre, deaths per million.

So, metrics like velocity and acceleration have dimensions, and so do deaths and recoveries (and detected infections). These dimensions are very important to know and help to make meaningful comparisons.

There is a higher form of metric which has no dimensions, existing in a kind of heaven of perfection. They’re so good they’re like the angels of the world of metrics, quite unlike “detected infections” which is an evil devil – misleading everyone and causing mayhem.

Why are dimensionless metrics so good?

Not having dimensions imbues them with a truly magical quality: we don’t need to make any adjustments to them when we want to make comparisons! Angelic!

Why is this so? And what’s an example?

Let’s look at total deaths for a country. This looks like a number without dimensions, but it isn’t. It actually has many complex-yet-unstated dimesions to do with local conditions – population, population density, socioeconomic and health care conditions, demographics and so on. These all vary by location and over time and it would confuse everyone if we figured out these dimensions and started referring to it using them. Imagine it: deaths per place, date, season, weather, wealth, population, density, weather, healthcare quality… etc. so we can see that deaths is actually highly dimensional.

Which country has had the highest deaths per capita? Do you know?

It’s Belgium. Surprising huh? But is this really meaningful? We’ve only adjusted for one of the dozens of possible dimensions we need to in order to compare. So, no, it isn’t.

Fortunately, there’s a trick to get rid of all dimensions – whether we know them or not!

We use ratios. Ratios are heavenly. Whenever we divide any two metrics with the same dimensions, the dimensions cancel out! This is analagous to multiplying fractions like:

  \frac{2}{4} \times \frac{4}{2}

the 4s cancel and the 2s cancel, so this is simply 1.

Recoveries and Deaths for a location have the same dimensions, so their ratio is dimensionless, ascending straight to number heaven. We can use this ratio to make meaningful comparisons across territories and over time. Magical!

Ratios can be tricky devils if we accidentally divide by zero. A convenient way to handle this with numbers like deaths and recoveries is to add 1 to the denominator since they can’t be negative this guarantees we never have a value of zero on the bottom.

Dimensionless Fatality and Recovery Rates

We can see how fatal COVID-19 is by using the metric

  \frac{deaths}{(1 + recoveries)}

Let’s call this the Dimensionless Fatality Rate, or DFR. The most reliable source of deaths and recoveries is from hospitals and the hospital case fatality rate is the number of people admitted to hospital that die expressed as a rate. The DFR for hospitals in a state or country is a perfect, credible and comparable metric.

(I extended this concept significantly when I created the Epidemic Severity Index, the maths is more complex but DFR was the starting point for it).

We could flip this to think of recovery rates instead: the Dimensionless Recovery Rate or DRR is R/(1+D).

Dimensionless Fatality Rate and Dimensionless Recovery Rate

Let’s look at some examples to get a feel for how the DFR behaves: when there are no deaths and no recoveries its value is 0.

When there is 1 death, its value rises to 1.

If two people were admitted and the other recovers, then DFR goes down to 1/2.

For seasonal flu, about 1 in every 13 hospital admissions dies and the other 12 recover, so the DFR for seasonal flu is 1/13 or 0.077 (quite low, but still pretty scary). At the peak of the pandemic countries, experiencing bad outbreaks had a much higher DFR of around 0.5. However, countries that did not have bad outbreaks had much lower DFRs.

Small numbers are hard for our intuition, so let’s look at recovery rates, or DRRs, instead.

Seasonal Flu has a Dimensionless (hospital) Recovery Rate of 13. So, any value less than this means fewer people recover and the disease is more fatal. Anything higher than 13 means the disease is less fatal than seasonal flu and therefore we don’t need to be panic and enact stupid lockdown rules.

COVID-19 had a DRR of approximately 2.0 at the peak in Europe – that’s much more fatal than flu and a lockdown was well-justifed then. However, Japan’s DRR was 7.2 at the end of March so their C19 oubreak was only about twice as bad as seasonal flu! Two months later their DRR had risen to 16 and the disease was LESS SEVERE seasonal flu. By July 28th the daily DRR was an incredible 167 and the overall DRR had risen to 23. Japan’s COVID-19 outbreak was much less fatal than seasonal flu in the US. (I’ll explain why later).

Let’s see DRR calculated for some countries of interest on three key dates: 28 March, 28 May, and 28th July. We’ll look at the daily DRR and the overall DRR. Daily values can fluctuate and be unstable but it’s still illustrative to see what’s been going on.

Dimensionless Revovery Rates tell a very different story to the red-herring “detected infections” that Matt Hancock is chasing.

The UK’s current daily DDR is now almost as good as seasonal flu in the US. It’s rising all the time and we no longer need to be enacting lockdown.

This is why good science is so useful. It tells us what we should be doing. If governments were more scientifically literate and listened to me (and people like me) we would have gone into lockdown on the 10th March and we could have come out of it in May! We didn’t and could’t because they refused to look at vitamin D deficiency despite us proving that vitamin D deficiency is causing people to die of COVID-19. In fact, I had worked this out by March 19th and those who trusted the documented evidence for this that I circulated back then are still alive. Thankfully the documents went viral globally, so hopefully we saved millions of people from dying through our actions. If the goverment had listened, this would have all been over very quickly and with orders of magnitude fewer deaths.

Let’s look at DRR for more countries:

Why did countries have such different severities of COVID-19 outbreak? Vitamin D deficiency variation is the primary reason.

Finland is fascinating. Sadly, it was infected too late to include in either my paper explaining the Epidemic Severity Index and our proof that vitamin D deficiency causes poor COVID-19 outcomes, but I kept an eye on it because it’s the only country in Europe that has an effective vitamin D food fortification programme. It’s living proof this works: Finland has had 329 COVID-19 deaths and 6,950 recoveries at the time of writing.

Finland has an effective vitamin D food fortification because it’s so far north.
Just 329 deaths and 6,950 recoveries. That’s far less fatal than seasonal flu in the USA!
Source: https://covid19info.live/finland/

Everyone outside the tropics (30°S to 30°N) should be taking vitamin D supplements throughout winter and in fact, I believe all year round. I take 4,000IU per day and I had a very mild experience. In fact, if I hadn’t known the symptoms so well, I probably wouldn’t have even noticed I was ill. My 94 year neighbour, Alan, has been taking vitamin D since Christmas because he has dementia and I knew it would help, so I buy it for him. It does. It’s helped him recover from 5 hospitalisations due to UTIs over the last year including 1 hospitalisation and two care homes at the peak of the pandemic. He’s COVID-19 negative and recovering well at home now with a live in carer.

My neighbour Alan, 94 years young, at home again and vitamin D sufficient! He’s on the left, I’m on the right. 😉

If everyone is vitamin D sufficient, we will not have a second wave.

 

Published by Gruff Davies

Gruff is a British scientist, tech entrepreneur, and author. He was named one of the World's Top 50 Innovators by Codex in 2019 at the Royal Society, London.

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