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Following on from my post of last week, below is a continued timeline about herd immunity and the coronavirus crisis in Britain.

Old news, perhaps, but it will be interesting to see how much of this, if any, is mentioned at the Government’s hearing, scheduled for 2022.

May 2020

On May 17, 2020, journalist Robert Peston tweeted about a conference in Edinburgh that could have been a super-spreader event:

One of Peston’s readers said that he was partly to blame, because, in March, he wrote an article for The Spectator‘”Herd immunity” will be vital to stopping coronavirus’.

It begins with this (emphases mine):

The key phrase we all need to understand is ‘herd immunity’ – which is what happens to a group of people or animals when they develop sufficient antibodies to be resistant to a disease.

The strategy of the British government in minimising the impact of Covid-19 is to allow the virus to pass through the entire population so that we acquire herd immunity, but at a much delayed speed so that those who suffer the most acute symptoms are able to receive the medical support they need, and such that the health service is not overwhelmed and crushed by the sheer number of cases it has to treat at any one time.

Infection figures were starting to recede in May. This could partly be explained by a month of glorious weather, apart from two days. It was one of the warmest and sunniest on record. I fantasised that I was in Cannes.

On May 18, Freddie Sayers of UnHerd interviewed Prof Karl Sikora, the Founding Dean and Professor of Medicine at the University of Buckingham Medical School and an ex-director of the WHO Cancer Programme:

Prof Sikora said:

The serology results around the world (and forthcoming in Britain) don’t necessarily reveal the percentage of people who have had the disease.

He estimates 25-30% of the UK population has had Covid-19, and higher in the group that is most susceptible.

Pockets of herd immunity help *already* explain the downturn.

Sweden’s end result will not be different to ours – lockdown versus no lockdown.

On May 10, Nic Lewis wrote a post about the UK and Sweden for Climate Etc.: ‘Why herd immunity to COVID-19 is reached much earlier than thought’.

It says, in part:

A study published in March by the COVID-19 Response Team from Imperial College (Ferguson20[1]) appears to have been largely responsible for driving government actions in the UK and, to a fair extent, in the US and some other countries. Until that report came out, the strategy of the UK government, at least, seems to have been to rely on the build up of ‘herd immunity’ to slow the growth of the epidemic and eventually cause it to peter out.

The ‘herd immunity threshold’ (HIT) can be estimated from the basic reproduction rate of the epidemic, R0 – a measure of how many people, on average, each infected individual infects. Standard simple compartmental models of epidemic growth imply that the HIT equals {1 – 1/R0}. Once the HIT is passed, the rate of new infections starts to decline, which should ensure that health systems will not thereafter be overwhelmed and makes it more practicable to take steps to eliminate the disease.

However, the Ferguson20 report estimated that relying on herd immunity would result in 81% of the UK and US populations becoming infected during the epidemic, mainly over a two-month period, based on an R0 estimate of 2.4. These figures imply that the HIT is between 50% and 60%.[2] Their report implied that health systems would be overwhelmed, resulting in far more deaths. It claimed that only draconian government interventions could prevent this occurring. Such interventions were rapidly implemented in the UK, in most states of the US, and in various other countries, via highly disruptive and restrictive enforced ‘lockdowns’.

A notable exception was Sweden, which has continued to pursue a herd immunity-based strategy, relying on relatively modest social distancing policies. The Imperial College team estimated that, after those policies were introduced in mid-March, R0 in Sweden was 2.5, with only a 2.5% probability that it was under 1.5.[3] The rapid spread of COVID-19 in the country in the second half of March suggests that R0 is unlikely to have been significantly under 2.0.[4]

Very sensibly, the Swedish public health authority has surveyed the prevalence of infections by the SARS-COV-2 virus in Stockholm County, the earliest in Sweden hit by COVID-19. They thereby estimated that 17% of the population would have been infected by 11 April, rising to 25% by 1 May 2020.[5] Yet recorded new cases had stopped increasing by 11 April (Figure 1), as had net hospital admissions,[6] and both measures have fallen significantly since. That pattern indicates that the HIT had been reached by 11 April, at which point only 17% of the population appear to have been infected.

How can it be true that the HIT has been reached in Stockholm County with only about 17% of the population having been infected, while an R0 of 2.0 is normally taken to imply a HIT of 50%?

A recent paper (Gomes et al.[7]) provides the answer. It shows that variation between individuals in their susceptibility to infection and their propensity to infect others can cause the HIT to be much lower than it is in a homogeneous population. Standard simple compartmental epidemic models take no account of such variability. And the model used in the Ferguson20 study, while much more complex, appears only to take into account inhomogeneity arising from a very limited set of factors – notably geographic separation from other individuals and household size – with only a modest resulting impact on the growth of the epidemic.[8] Using a compartmental model modified to take such variability into account, with co-variability between susceptibility and infectivity arguably handled in a more realistic way than by Gomes et al., I confirm their finding that the HIT is indeed reached at a much lower level than when the population is homogeneous. That would explain why the HIT appears to have been passed in Stockholm by mid April. The same seems likely to be the case in other major cities and regions that have been badly affected by COVID-19.

On that topic, Prof Sunetra Gupta, one of the signatories to The Barrington Declaration which came out that summer, entered the picture. Prof Gupta is the Professor of Theoretical Epidemiology at the University of Oxford. Freddie Sayers of UnHerd interviewed her on May 21:

The accompanying article says:

Her group at Oxford produced a rival model to Ferguson’s back in March which speculated that as much as 50% of the population may already have been infected and the true Infection Fatality Rate may be as low as 0.1%.

Since then, we have seen various antibody studies around the world indicating a disappointingly small percentage of seroprevalence — the percentage of the population has the anti-Covid-19 antibody. It was starting to seem like Ferguson’s view was the one closer to the truth.

But, in her first major interview since the Oxford study was published in March, Professor Gupta is only more convinced that her original opinion was correct.

As she sees it, the antibody studies, although useful, do not indicate the true level of exposure or level of immunity. First, many of the antibody tests are “extremely unreliable” and rely on hard-to-achieve representative groups. But more important, many people who have been exposed to the virus will have other kinds of immunity that don’t show up on antibody tests — either for genetic reasons or the result of pre-existing immunities to related coronaviruses such as the common cold.

The implications of this are profound – it means that when we hear results from antibody tests (such as a forthcoming official UK Government study) the percentage who test positive for antibodies is not necessarily equal to the percentage who have immunity or resistance to the virus. The true number could be much higher.

Observing the very similar patterns of the epidemic across countries around the world has convinced Professor Gupta that it is this hidden immunity, more than lockdowns or government interventions, that offers the best explanation of the Covid-19 progression:

“In almost every context we’ve seen the epidemic grow, turn around and die away — almost like clockwork. Different countries have had different lockdown policies, and yet what we’ve observed is almost a uniform pattern of behaviour which is highly consistent with the SIR model. To me that suggests that much of the driving force here was due to the build-up of immunity. I think that’s a more parsimonious explanation than one which requires in every country for lockdown (or various degrees of lockdown, including no lockdown) to have had the same effect.”

June 2020

On June 4, Freddie Sayers interviewed Prof Karl Friston, a computer modelling expert, world-renowned for his contributions to neuroscience. He had been applying his ‘dynamic causal modelling’ approach to the Covid-19 pandemic:

The accompanying article says that his Bayesian models were showing that up to 80% of the population might be naturally immune to coronavirus:

His models suggest that the stark difference between outcomes in the UK and Germany, for example, is not primarily an effect of different government actions (such as better testing and earlier lockdowns) but is better explained by intrinsic differences between the populations that make the “susceptible population” in Germany — the group that is vulnerable to Covid-19 — much smaller than in the UK.

As he told me in our interview, even within the UK, the numbers point to the same thing: that the “effective susceptible population” was never 100%, and was at most 50% and probably more like only 20% of the population. He emphasises that the analysis is not yet complete, but “I suspect, once this has been done, it will look like the effective non-susceptible portion of the population will be about 80%. I think that’s what’s going to happen.”

Theories abound as to which factors best explain the huge disparities between countries in the portion of the population that seems resistant or immune — everything from levels of vitamin D to ethnic-genetic and social and geographical differences may come into play — but Professor Friston makes clear that it does not primarily seem to be a function of government coronavirus policy. “Solving that — understanding that source of variation in terms of this non-susceptibility — is going to be the key to understanding the enormous variation between countries,” he said …

His explanation for the remarkably similar mortality outcomes in Sweden (no lockdown) and the UK (lockdown) is that “they weren’t actually any different. Because at the end of the day the actual processes that get into the epidemiological dynamics — the actual behaviours, the distancing, was evolutionarily specified by the way we behave when we have an infection.”

Most significantly, it would mean that the principal underlying assumption behind the global shutdowns, typified by the famous Imperial College forecasts — namely, that left unchecked this disease would rapidly pass through the entire population of every country and kill around 1% of those infected, leading to untold millions of deaths worldwide without draconian action — was wrong, out by a large factor. The largest co-ordinated government action in history, forcibly closing down most of the world’s societies with consequences that may last for generations, would have been based on faulty science.

When I put this to Professor Friston, he was the model of collegiate discretion. He said that the presumptions of Neil Ferguson’s models were all correct, “under the qualification that the population they were talking about is much smaller than you might imagine”. In other words, Ferguson was right that around 80% of susceptible people would rapidly become infected, and was right that of those between 0.5% and 1% would die — he just missed the fact that the relevant “susceptible population” was only ever a small portion of people in the UK, and an even smaller portion in countries like Germany and elsewhere. Which rather changes everything.

With such elegant formulations are scientific reputations saved. Practically, it makes not much difference whether, as per Sunetra Gupta, the 40,000 officially-counted coronavirus deaths in the UK are 0.1% of 40 million people infected, or, as per Karl Friston’s theory implies, they are more like 0.5% of 8 million people infected with the remaining 32 million shielded from infection by mysterious “immunological dark material”. If you are exposed to the virus and it is destroyed in your body by mucosal antibodies or T-cells or clever genes so that you never become fully infected and don’t even notice it, should that count as an infection? The effect is the same: 40,000 deaths, not 400,000.

However, on Sunday, June 7, SAGE member Prof John Edmunds was still backtracking on his earlier claims about herd immunity from March. He was all about lockdown and told the BBC’s Andrew Marr that the UK should have locked down sooner to prevent deaths:

Speaking of lockdown, Britons were increasingly angry about being told not to leave the house, especially when people were protesting with no social distancing:

June in the UK — Part 1: the angry, yet law abiding, silent majority (June 3)

June in the UK — Part 2: angry silent majority questions lockdown (June 5; masks; no arrests for destructive protestors, two for eccentric Piers Corbyn)

June in the UK — Part 3: the angry silent majority on lockdown (June 5)

June in the UK — Part 4: coronavirus and the public’s anger about health during lockdown (June 5)

June in the UK — Part 5: the hypocrisy surrounding coronavirus and social distancing (June 6, protests)

—————————————————————-

Writing a year later, I do wonder whether getting vaccinated is really worth it for most of us.

Unfortunately, we have to do it to have any semblance of normality.

I’m a big believer in natural herd immunity, less so the artificially engineered type.

More to follow on herd immunity next week.

Before reading this, here are Parts 1, 2 and 3 of a series on coronavirus and lockdown.

It seems that the British silent majority were largely fine with obeying the rules that Boris Johnson’s government set until the end of May.

By then, they began asking questions about the duration.

During the first two months of lockdown, they understood that the reasons were not to put too much pressure on the NHS.

However, as Boris and his ministers are taking only ‘baby steps’ (Boris’s words) to release us, many wonder what the real plan is.

Rightly or wrongly, suspicion is rife:

There is also the question about the NHS and the need for treatment outside of COVID-19.

Those of us who watch the daily coronavirus briefings from the government can’t help but notice the messaging, especially from Health Secretary Matt Hancock:

I missed this little titbit from the coronavirus briefing on Friday, June 5. Hancock said, ‘As the NHS reopens’. Hmm:

Yet, Britons are still missing out on non-coronavirus NHS treatments that are urgent:

I couldn’t agree more with this next observation from Prof Karol Sikora:

Then we have the unknown consequences of Big Data intrusions into our lives:

This is now climbing up the chain to stain Prime Minister Boris Johnson, the champion of his soi-disant ‘Government of the People’:

The goalposts have clearly shifted since Boris’s stonking victory in December 2019:

Lockdown has now gone on too long:

Despite what the government and scientists say on the weekday coronavirus briefings, other statistics find their way through the established narrative:

Yet, part of the blame also lies with the proportion of the British public who are afraid of re-engaging with society the way they did before lockdown:

Those who are afraid can stay at home. Let the rest of us get back to real life.

This London Assembly member from the Brexit Party is spot on. Lockdown must end:

Social distancing will end up being a killer, too:

One hopes it doesn’t come to this:

One wonders whether there is such a thing as conservatism any more:

Or is the WHO driving this? They must think we are stupid. Perhaps we are:

We will never be in a risk-free, virus-free world.

Ending on Boris, for now, this is something I missed. Then again, I don’t listen to BBC Radio 4. Even if I had, I would have thought that Boris’s father Stanley was voicing his own views, not his son’s:

Boris is still better than his Labour counterparts — Jeremy Corbyn (then) and Keir Starmer (now).

However, his polling will take a dive unless he restores what he called the People’s Government.

More tomorrow: coronavirus and the June riots.

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