The Vaunted “R Number” the UK Is Destroying Itself Over Is Shamanic Mumbo Jumbo

Not only is the data going in weak and uncertain, but even the core assumptions of the model are educated guesses subject to bias

Treating complicated mathematics (on rotten assumptions) with reverence once reserved for magic

In the words of former Supreme Court Judge Lord Sumption, lockdown is without doubt the greatest interference with personal liberty in our history. 

Since the end of March we have had our freedoms curtailed, our economy has been in freefall and our children have had their education stopped. As it stands, there is no clear end in sight.

At first we were told this was all about protecting the NHS from a surge of cases. 

But now that the NHS has been protected, the Government and its advisers have come up with another reason for stopping us living our lives.

This is the R value – the number of people who are expected to catch the virus from an infected person.

A value above one, and cases of the virus increase exponentially; below one, they decrease and the virus fades out.

Time and again, we are told that keeping R below one is the only way to map a route out of lockdown.

The truth, however, is entirely different. Why? Because R is an artificial construct and not even a number we know with any certainty.

R is calculated using mathematical modelling – and the models used have repeatedly been found to reach untenable and frankly wrong-headed conclusions.

As a former professor of pathology, and someone who has had a long research career, I am very familiar with critical assessment of data.

And in the case of R, I can tell you that this is not a strong enough number to bear the burden of any Government policy, let alone a policy with the magnitude of lockdown.

In fact, the epidemiological models that generate R are probably less reliable than long-range weather forecasts. Let me explain.

There is a tendency to give models too much respect because they rely on mathematics that few can follow. 

But any model, no matter how complex, is only as good as its data and assumptions.

How do weather forecasting and epidemiology compare? Well, for a start they both suffer from weak data. 

Meteorologists study things such as pressure, temperature, wind speed, and humidity, to try to predict what is going to happen.

These are known as variables because they can take many different values. And changes in the variables can produce totally different results in the forecast.

So meteorologists are generally unable to predict accurately further than a few days ahead because there are many more variables out there than they are able to measure. 

But at least the assumptions of the model – the physics at its core – are very well established.

Epidemiology models share the same serious problem of weak data. Lack of testing means we don’t know how many people have been infected, or have recovered.

Changes to death certification during this epidemic mean that, contrary to what has repeatedly been said, we genuinely don’t even know how many people have died as a direct result of the disease.

This means that it is very difficult to know how nasty the disease is compared to, say, the effects of lockdown.

Many analysts suggest that lockdown is directly causing more deaths than the virus.

Even worse, it is becoming increasingly clear that assumptions central to the models that generate R are flawed. 

One, for example, is that everyone is susceptible to the virus because it is new. But this is clearly not true.

Some of us, perhaps as many as six or seven million, have already had the virus, and immunity means that we are highly unlikely to get it twice.

Indeed, new work just published in the prestigious journal Cell shows that coronaviruses causing the common cold give rise to immune cells [T cells] that also react to Sars-Cov-2, the virus responsible for Covid-19.

These cells were present in 40 to 60 per cent of people who had not been exposed to the new virus. If they confer a degree of immunity to it, as seems likely, they would blow calculations of R out of the water.

This would also explain another incorrect assumption, that the virus would ‘rip through’ the population, infecting 80 per cent of us, when in fact it seems to be levelling out at about 20 per cent.

Then there’s the assumption that we are all equally vulnerable. This is not true either.

Children are very unlikely to catch the virus, to become very ill with it, or to pass it on. So quoting a single value of R for different segments of the population is highly misleading.

R is also very different in different parts of the country, and in different locations within those parts.

This combination of weak data and flawed assumptions means that R is clearly not a number that can be applied universally, or even one that we really know.

Weather forecasters often refer to themselves as being in the business of making educated guesses about the weather.

But you can see that their guesses, wrong as they often turn out to be, are actually more educated than the models causing the Government to mess up our lives.

Another important finding, unappreciated at the start of the epidemic, is that many people, perhaps as many as 80 per cent, have an asymptomatic infection. That is, they have the disease so mildly that they are not even aware of it.

In this case, it doesn’t matter if the apparent R (assuming we could measure it) is higher than one for healthy people.

The best way to deal with the virus is not lockdown, but to encourage R above one for the fit and healthy.

If they go out and catch the virus it builds herd immunity, bringing forward the time when R heads back below one and the virus largely peters out.

Risks for the fit and healthy are very small, again contrary to initial impressions.

Worries on Friday that R was apparently heading back towards one were missing the point. For some segments of society, including most people of working age, that would be a good thing.

We need to restart the economy, allowing the fit and healthy not only to get their lives back, but also to generate the resources needed for protecting those elements of society most at risk.

Another implication of seeing R this way, which is quite a relief, is that social distancing can be consigned to the dustbin of bizarre historical episodes.

We can’t realistically do it for many things that make life worth living, and thank goodness most people don’t actually need to.

Self-isolation for people with symptoms, while shielding the vulnerable, would be just as effective with massively smaller costs.

WORRIES about a second wave of infections are also misplaced when so many have such mild symptoms. In any case, the NHS is supposed to be there to look after us, not the other way around.

We now know more about treating this disease and are better placed to deal with any new cases that do occur. It is not the existential threat that was first feared.

The Government and their scientific advisors are heading up a blind alley with their emphasis on R.

They seem to be grasping for spurious certainty from a modelling output that cannot supply it.

Or perhaps that is part of the attraction. R is a mysterious number, calculated in ways we are not privy to, that the Government can produce at will to justify a policy that is no longer tenable.

But a single R for the country is at best misleading, at worst a meaningless abstraction.

And R isn’t necessary to understand that evidence has changed over the past two months.

The worst-case scenario didn’t happen, and in any case serious flaws in the models show that it was greatly exaggerated.

We need to get beyond panic and stop moving the goalposts.

It takes courage and leadership to strike out in a new direction. Boris Johnson showed that once, in opting for lockdown.

But now that we know more about this virus and the consequences of that decision, it’s time he showed it again.

He should release lockdown and minimise social distancing for most, while continuing to bolster systems that provide protection for those most in need.

We need our liberties back − and to return to all the things that make life worth living.

Source: The Daily Mail

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