Covid 19 Lockdown as a Granfalloon – A Hypothesis

Introduction

On the day that I am writing this I was invited to watch a video of Matt Hancock the UK Health Minister make a statement in the House of Commons about the roll out of the coronavirus vaccine in the UK and the sequence in which people will be called in to get their vaccination. As I am now 72, that will not be so long in the future for me. When the time comes, said Hancock “step forward for your country”.

At that point I must admit that I shouted with rage at the computer screen….

In this essay I explain why. I do not do so with 100% conviction that I am right. I do so because of many doubts. I would probably be prepared to take the vaccine in a couple of years if this rush to try it has not had disastrous results. After all for the last few years I have taken the flu vaccine. But part of what I am going to write about is some scepticism about whether the pandemic is still really happening. I think there is a chance that it is nearly over anyway – though I am not sure.

In the House of Commons MP after MP stood up to make tribute to the vaccine manufacturers for the extraordinary speed with which they have developed and made available the vaccine. Might it not also be appropriate to point out that the reason why vaccines usually take longer to develop is to make sure that there are no long term unwanted health risks. Time is needed to see if these unwanted effects are felt by the people who trial them. Are the MPs celebrating taking short cuts on safety?

This is not “disinformation” and it reduces me to helpless rage to hear it implied that if I doubt the official narrative and express those doubts, I am peddling disinformation. People who raise doubt are asking others to retain their critical faculties, their ability to think for themselves rather than be stampeded into group think. In this essay therefore I am expressing an alternative analysis for consideration – including ways of thinking about the pandemic and responses to it that are hypotheses. I don’t say that I am convinced that these hypotheses are true – I say that they might be, that they seem plausible to me, and I ask them to be considered. I admit in advance that I might be wrong but I think that what I will write is more plausible than the official narrative and so I am writing it down to circulate.

To respond to crises such as covid 19 with new drugs and new vaccines, very large exercises in co-ordination, management and resource use are necessary. A variety of organisations and institutions, networked across the society, economy, political and media system, have co-ordinated together nationally and internationally. They require long time scales and large resources if they are to launch initiatives like an international vaccine. According to an article published in the Lancet in October 2018

The cost of developing a single epidemic infectious disease vaccine from preclinical trials through to end of phase 2a is US$31–68 million (US$14–159 million range), assuming no risk of failure. We found that previous licensure experience and indirect costs are upward drivers of research and development costs. Accounting for probability of success, the average cost of successfully advancing at least one epidemic infectious disease vaccine through to the end of phase 2a can vary from US$84–112 million ($23 million–$295 million range) starting from phase 2 to $319–469 million ($137 million–$1·1 billion range) starting from preclinical. This cost includes the cumulative cost of failed vaccine candidates through the research and development process. Assuming these candidates and funding were made available, progressing at least one vaccine through to the end of phase 2a for each of the 11 epidemic infectious diseases would cost a minimum of $2·8–3·7 billion ($1·2 billion–$8·4 billion range)….

…..In general, vaccine development from discovery to licensure can cost billions of dollars, can take over 10 years to complete, and has an average 94% chance of failure…

Note that 94% chance of failure. Does that chance apply to this vaccine too?

Under Operation Warp Speed, the federal government has pledged close to $9 billion to fund the development and production of the vaccines. Other countries are also putting in large amounts.

If they are not to lose or waste immense resources then such joint initiatives can take on a life of their own with far reaching consequences – for example it would be….or maybe is…. incredibly disruptive if the research and production of a vaccine were to be launched but then, before the vaccine is brought into use, the pandemic for which it is intended ends without intervention anyway. Or if rumour, true or not true, were to start circulating that the vaccine was not safe and, as a result, many people refused to use it. Or if it were found that there were alternative treatments which were as, or more, effective than a vaccine, what would then happen?

Even before I write it down I fear the attack on me as a conspiracy theorist – but here is a sample question: might steps be taken to undermine competitor drugs?

Such things do happen. What other conclusions does one take after the scandals trying to undermine the research into hydroxychloroquine as a prophylactic and early treatment for Covid 19 in order to discredit that drug? (Both the Lancet and New England Journal of Medicine had to retract papers that they had published – see a great account of this scandal by Tim Watkins here.)

Actually as far as I know the vaccine manufacturers are not involved in a conspiracy – but I do think that they might be involved in a coalition of academics, officials, politicians and big pharma companies which would be more appropriately described as a granfalloon.

What’s a granfalloon? It is a powerful coalition that has formed around an idea that will enable the coalition members to improve or save the world – or so they believe – and maybe make a buck or two from a grateful world population when they have done their job. The other part of the definition of a granfalloon is that it is ultimately a futile endeavour. People and organisations associated with a granfalloon are pursuing an illusion. They are held together in the pursuit of this futile or vacuous goal by mechanisms of group-think and consensus trance.

This is the way that members of groups adjust their thinking to what others in the group believe is valid and plausible. The theorist of public relations, Edward Bernays, called it “the group mind”. I think I saw it today as I watched a video of the House of Commons when, one after another, the MPs all congratulated the scientists, but did not raise a peep about the risks.

Kurt Vonnegut, who originated the idea, described granfalloons like this: “If you wish to examine a granfalloon, just remove the skin of a toy balloon”. In my book Credo I explain how:

What often sustains the group trance is the fear of ostracism. There are taboo things that one cannot say or question – among business, government and most economists the very idea of questioning growth is not allowed otherwise one is banished to the group of tree huggers and eco-freaks who are not to be taken seriously….. desperate to be seen as a loyal member of the inner circle of power, the economists, politicians and mandarins develop a keen sense of what they can and cannot say to each other and in public. The desire to belong is a strong one, especially for ambitious people, so even while the official’s theory pictures all of us acting as independent minded individuals, the reality in the centres of power is often abject conformity and sycophancy to the ideas and opinions of those who are more powerful than oneself. ( p 89)

Nevertheless it is important to recognise that in the pursuit of a granfalloon, the true believers are probably not out to trick us as they would in a conspiracy – they are there to save us, from ourselves if necessary. In regards to a health crisis like covid 19 the background is a situation of widespread misunderstanding by a large variety of non experts. The media in particular are probably not deliberately setting out to misinform. There will be times when they have just taken in ideas superficially and misled without even trying. This two minute 19 second clip of a professor and former director of the Institute of Immunology at the University of Bern gives us an insight into the misleading role of media communication about the pandemic in respect of testing: https://twitter.com/robinmonotti/status/1326777941704007681?s=20

A few years ago I attended a conference in Ireland after the 2008 financial crisis by a lot of people most of whom had seen it coming. One speaker, Dmitry Orlov, asked rhetorically why the people in the conference were capable of understanding a lot of problems that other people simply could not see. “The answer that I came up with” said Orlov “is that most people like you do not have televisions”. His remark brought a laugh but was confirmed by asking around.

All of us are uninformed and misinformed in multiple aspects of this pandemic – including the medics who are rushing to understand it. The same applies to many who are experts. It applies to me. All of us have a spectrum, a spread of skills, knowledge and experience and form our viewpoint from what we think we know.

That’s why what I am writing here is a hypothesis – particularly as I am writing outside my normal field of expertise. But now politics, health policy and what happens in our everyday lives have all been mixed together whether we like it or not. So we are all entitled to try to figure out what is going on and pitch in – otherwise we might as well give up on the idea of democracy altogether and hand over our rights to committees of people claiming to know what is best for us because they have qualifications in public health. This is pretty close to what the Cabinet and Boris Johnson appeared to have done in their capitulation to their supposed expert advisory committee SAGE. Psychiatrists have a legal right to detain us under the Mental Health Acts. Are we now going to add a legal right to public health doctors to detain us when they claim that being out and about and going to the pub is a danger to our health and that of others? It seems so – except that giving public health doctors this right threatens our livelihoods which are also necessary to our health.

All of us live in a world full of unknown unknowns. Also, some of us don’t know things, but know we don’t know them. Unfortunately there are occasions when we misjudge and don’t bother to find out things when we know we don’t know them. We assume that the things that we know that we don’t know are not very important so we don’t bother to find out more when, on the contrary, they are very important indeed.

The people held up to be the experts – the so called SAGE group of scientists at Imperial College who advise the government as well as the chief medical officer and chief scientific adviser – regularly run models. During this crisis the models have shown that alarming rates of illness and death will occur unless something is done to prevent this happening

Then, when the alarming trends of deaths don’t happen, that’s presumed to be because the policy is working – not because of the counter factual that the original predicted trend was wrong in the first place. A lot of the rest of this article is about whether this is true or not. It is about what is called in the jargon – the counter factuals. Counter factuals are what would have happened if. For example, according to Neil Ferguson, a professor at Imperial College there would have been a half a million deaths had we not had the lock down.

This joke from Dr Malcolm Kendrick expresses it well:

A man sounds a horn every day and someone asks him:
Why are you sounding a horn?
To keep the lions away. Ever seen any lions around here?
No
Well, it’s working then isn’t it?

Now, if you offer to blow the horn next day, you just set up a granfalloon. If people get irritated by you blowing a horn then you run mathematical models which demonstrate how many lions you scared away….or even better, how many people they would have eaten.

Counterfactuals that show that lockdown worked

It is with that joke in mind we should consider a couple of studies which purport to show that the lockdown policies have saved many of us from covid 19.

One such study appeared in Nature and is by an academic team led by Seth Flackman and includes Neil Ferguson from Imperial College London – the mathematician whose modelling of the pandemic suggested that a half a million people would have died from the pandemic in the UK unless strong steps were taken through stringent policy measures. My counter hypothesis is that they are part of a granfalloon coalition, unwittingly sowing mayhem with their empty ideas.

In their study Flaxman et al provide justifications for lockdowns in Britain and elsewhere in Europe. Without the lockdowns they claim that there would have been 3.2 million more deaths. To quote from their study: “Our results show that major non-pharmaceutical interventions—and lockdowns in particular—have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.”

Another study by Hale et al is similar – though as far as I can see it has not been peer reviewed. Its conclusion “hypothesized that the overall stringency of a government’s interventions and the speed of implementation would affect the growth and level of deaths related to COVID-19 in that country.” It looked at evidence and concluded that a “lower degree of government stringency and slower response times were associated with more deaths from COVID-19.”

Other academics disagree with the study by Team Flaxman and with the study by Team Hale. So who is right and who is wrong? If Flaxman and Hale went wrong then in what way did they go wrong?

Other academics have accused Flaxman et al of methodological error. Have they modelled the effect of lockdowns accurately enough? Have they left out important considerations? The hypothesis is that if, because of lockdowns, people go out less to the places where they might pick up the virus, then they will be less likely to get infected. Hence where possible they/we must stay at home. But what if the most likely place where they pick up the virus is from people they live with and the policy means that they have to stay at home with them more? Are they not now more likely to pick up the virus where they live? Should that not be in the model?

Here is another example of omitted variables in the study by Hale et al. It is to be found in the description of their research methods: “Importantly, for all Non Pharmaceutical Interventions, we record only the official policies at the national level, not how well they are implemented or enforced.” Thus when government’s announce their regulations the restrictions are presumed to be working as intended and for as long as the regulations are there. But is this what happened in real life?

For someone who worked in the anti fracking movement that particular feature “shouted” at me because that was always the British government’s reason why no members of the public needed to fear fracking – because it would be well regulated, because companies would stick to the rules and best practice would prevail. It soon became clear that those assumptions were garbage – companies did not stick to the rules at all and things went wrong regularly.

So omitting how well policies were implemented or enforced is naive. It leaves big holes in data about the real world influences on the processes of infection and the extent that people really did stay at homes or in places where it was assumed that they would be less likely to get infected.

What’s more, researchers can check this because there is data available. Millions of people travel around with smart phones with their geo-location device left on.

When lockdowns are imposed, for example, in England, the first effects are striking falls in mobility and massive reductions of people being in the public places outside the home where they might be infected – in places of entertainment, transport hubs, restaurants and pubs, shops and work. This could be, and has been, tracked on google data of mobile phones. The big fall in mobility appeared to coincide with when the infections that led to deaths peaked and started to fall. Was this not a correlation between policy and infections? Was this the proof of what the Flaxman study and the Hale study claim?

The first thing to note is that the fall in infections probably pre-dated the lockdown, according to calculations by Simon N Wood’s paper “Did COVID-19 infections decline before UK lockdown?”.

Secondly, although in England the lockdown was associated with a 60% fall in mobility (a 60% reduction in phones that were not located in places deemed locations of potential infection), the fall began a week before the lockdown, kept falling for about two weeks and was not maintained after 29 March when people started to drift away from home again.

As this slippage happened there was not a matching uptick into more infections. Crowded beaches and demonstrations in support of Black Lives Matter which might have been considered superspreader events did not lead to an increase in infections. Infections continued to fall.

Nor did policy changes like the end of lockdown on 14th May, the opening of retail on 16th June, re-opening hospitality on 6th July make a noticeable difference….although ironically mandatory masking on 25th July was the low point after which infections started to rise again! If there was a connection then it was not a sign of the success of policy…

These developments are shown on these two graphs from a presentation by data scientist Joel Smalley below. Two graphs are presented – one above the other. The one on top is the curve of deaths backdated to when it is estimated the person who died was originally infected and the one underneath is the google geo-location data. As can be seen – school closure and lockdown in March coincide with a dramatic drop in being away from home and coincide in a peak of infections – however from 29th March through to 14th May, when the first lockdown ends. the fall in fatal infections is continuous. Yet it coincides with a continuous weakening of the compliance with the lockdown in this entire period. (Click to see an enlarged version.)

Source: Joel Smalley MBA presentation at https://www.youtube.com/watch?v=m121hAiREvc&feature=youtu.be

Only after the late summer bank holiday at the end of August does the trend to being more outside reverse. From September as people move into the autumn people start to stay at home more. So not only is people staying at home less mostly associated with falling rates of infection moving into summer, the opposite is the case in the autumn – as people stay at home more, the infection gets worse in what became known at the second wave.

Smalley’s data analysis also throws light over the so-called second wave. In the first surge the rate of growth of infections was falling before the lockdown was imposed. In the second case the lockdown was imposed 3 weeks after it had peaked and had already fallen a long way. Geo-location data shows the effect on people’s location falling for a couple of days the 7th November and then starting to drift up again – but there is no noticeable impact on a trend that has already started.

To return to the main point. Hale et al claim that stringent policies imposed quickly brought down the death rate but fail to model and take into account several points that do not fit their analysis at all.

As it happens, one Danish academic at Aarhus University reworked a lot of their data using an econometric approach. Over the last couple of decades econometricians have focused a lot on endogeneity and the spurious conclusions that endogeneity can lead to and have developed approaches to data to correct for these problems. This is what Christian Bjørnskov does in his article “Did Lockdown Work? An Economist’s Cross-Country Comparison” (August 2, 2020). After doing this Bjørnskov’s finds “…no clear association between lockdown policies and mortality development.”

Meanwhile two German academics, Christof Kuhbander and Stefan Homburg, tear into Seth Flaxman and colleagues in their brief “Commentary: Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe”. Kuhbander and Homburg particularly focus their critique of Flaxman et al on the rate at which the infection spreads. This is based on the average of how many other people each ill person infects – the so called R number. As Kuhbander and Homburg point out, this falls inevitably, for the simple reason that the larger the number of people infected the less are left who are still susceptible to be infected.

“The model of Flaxman et al. (3) contradicts this elementary insight. They estimate R(t) from daily deaths associated with SARS-CoV-2 using as an a priori restriction that R(t) may only change at those dates where interventions become effective. Such an approach does not prove that NPIs were effective but rather begs the result, i.e., involves circular logic. The true effective reproduction number declines continuously, and when its estimates are allowed to change only at intervention points, it is clear that profound discontinuities, which attribute strong effects to the interventions, will emerge. Flaxman et al. (p. 2) conclude that while most NPIs had unidentifiable effects, lockdowns reduced the reproduction numbers instantaneously by 82%….”

Showing a graph of the growth of infections falling between 14th March and 4 May, they write

“Considering a total delay of 23 days between infection and death, possible effects of the 23 March lockdown should only become visible in the data around April 15. However, the series does not show the slightest break in mid-April. Hitherto, the growth factor had already declined from 1.54 to 0.97, and thereafter it continued its slowdown. Quite contrary to the findings of Flaxman et al, Figure 1B (the graph) strongly suggests that the UK lockdown was both superfluous (it did not prevent an otherwise explosive behavior of the spread of the coronavirus) and ineffective (it did not slow down the death growth rate visibly)…

“We have checked that the growth factors in the remaining 10 countries considered by Flaxman et al. show a similar pattern. Our analysis does not answer the question whether the decrease of R(t) was due to a decreasing number of susceptible persons or to voluntary behavioral changes, but it rules out the possibility that the decrease was caused by the general lockdown.”

More omitted variables – variations in susceptibility and connectivity in transmission

Another study draws attention to other omitted variables in the Flaxman paper – the variation in susceptibility and connectivity in the population study. Flaxman et al assumed that all the population in the countries that they studied were equally susceptible to infection and equally connected to others (hence equally likely to pass on the infection). However 4 academics at Edinburgh and Strathclyde Universities used the same data as Flaxman et al but dropped that assumption. The abstract for their study (not peer reviewed), titled “Trajectory of Covid 19 Epidemic in Europe” reads as follows:

The classic Susceptible-Infected-Recovered model formulated by Kermack and McKendrick assumes that all individuals in the population are equally susceptible to infection. From fitting such a model to the trajectory of mortality from COVID-19 in 11 European countries up to 4 May 2020 Flaxman et al. concluded that “major non-pharmaceutical interventions – and lockdowns in particular – have had a large effect on reducing transmission” . We show that relaxing the assumption of homogeneity to allow for individual variation in susceptibility or connectivity gives a model that has better fit to the data and more accurate 14-day forward prediction of mortality. Allowing for heterogeneity reduces the estimate of “counterfactual” deaths that would have occurred if there had been no interventions from 3.2 million to 262,000, implying that most of the slowing and reversal of COVID-19 mortality is explained by the build-up of herd immunity. The estimate of the herd immunity threshold depends on the value specified for the infection fatality ratio (IFR): a value of 0.3% for the IFR gives 15% for the average herd immunity threshold.

Prior immunity?

This idea that populations were not all equally susceptible and equally likely to pass on the infection makes better sense of why the pandemic peaked so early when it had still only infected a minority of the population. The contrary idea, that the bulk of the population are still susceptible, still vulnerable to infection, is the underpinning assumption used to justify continuing the lockdown and restrictive policies as well as the need for a vaccine too.

On this matter a growing alternative view has been that a large part of the population may have have a prior immunity and it was not true that the whole population was susceptible. According to an article in the British Medical Journal there is a growing degree of scientific interest by doctors focusing in on T cell based immunity. The author, Peter Doshi , associate editor of the British Medical Journal, concludes this article with the question “ Could pre-existing immunity be more protective than future vaccines? Without studying the question, we won’t know.”

This prior immunity is usually explained by the idea that most people had been infected with other coronaviruses and this has perhaps been remembered by their immune systems in their T cells. Perhaps this gave them “cross reactive” immunity. An article in the BMJ covers this possibility and the need for further research in this direction.

As I wrote at the beginning of this articlem I am writing hypotheses…..but also insisting that the mainstream analysis that government seems to accept as fact – that it was its policy actions that brought down the infections – is also a hypothesis.

Seasonality

Another part of the story appears to be that SARS Cov 2 has proved to be seasonal in its infectiousness in a similar way to influenza. Influenza is a winter disease. So there are other “hidden variables” – one of which is that people live outside more in the summer. Contagion is not so easy outside as viruses are dissipated in fresh air whereas inside, viruses can accumulate in aerosols in unventilated spaces and then infect people.

Perhaps too, sunlight in summer enables people to manufacture and accumulate vitamin D in their skin and better modulate their immune systems and protect themselves from infection. See “The link between vitamin D deficiency and Covid-19 in a large population” (not yet peer reviewed ). Also this study (peer reviewed) and this one (peer reviewed)

The bottom line on lockdowns – they don’t seem to work to prevent infections and deaths

There are other studies. They also conclude that the stringency of government measures did not significantly influence the course of the disease. For example a peer reviewed study published in the Lancet in August concludes, among other things, that “Rapid border closures, full lockdowns, and wide-spread testing were not associated with COVID-19 mortality per million people.”

The bottom line is that there are two narratives about how the virus and pandemic has developed. One is that the decline in infections and deaths early in 2020 going into the summer was not because of the lockdown. The other is that the disease peaked and then fell largely because of the lockdown. In my view the former hypothesis is more plausible and better fits the evidence, but I admit I could still be wrong. I rely myself on the studies of others.

The “Second Wave”

If the epidemic reached a peak, declined and appeared to end due to natural processes rather than the lockdown, then why has it re-emerged? At first sight, the resurgence of the virus, the so called second wave, better fits the idea that the virus was held at bay by policy measures which, when they were relaxed allowed the virus to re-emerge. It seems to confirm the analysis of Flaxman et al. Hale et al and of Ferguson, Whitty, Vallance and SAGE. Unless we are put under lockdown, or locally tailored “tiers” of restriction, the virus comes back.

But is this true? What has actually happened this autumn and why? Again I stress that the narrative expressed here is an alternative understanding that appears to me to be suggested by the data as collected and presented by Joel Smalley. It is an alternative hypothesis that seems to me to be very plausible. It appears congruent with the analysis presented earlier that the pandemic spread through a population with varying degrees of susceptibility and connectivity.

One would expect a contagion to pass first through the areas with the most intensive levels of connectivity and susceptibility. Thus, for example, because political and economic power is reflected in a high level of “well connectedness” among the elite, it is no accident that many global and national political leaders became infected. Through chains of people who know people the political and economic leaders know and are connected directly and then through indirect chains of connection into the population. These channels of interconnection are how political power, and also commerce, work – and these connections follow geographical settlement patterns too. So it is not at all surprising that although infection might originate in peripheral locations they would tend to flow towards centres and then between connected centres and from thence outwards back into more peripheral locations. That is how supply chains, money flows and social, business and political networks work – and illness contagions follow the same connections.

So in the first wave, it is not surprising that first of all and most intensively in the UK it impacted on cities like London and the West Midlands.

Thus the spread of the disease has involved growing in intensity and saturation at each individual place while at the same time flowing outwards from the most highly connected centres to less connected peripheral settlements in an uneven way over time. This dual process of local growth of intensity and outwards flow was interrupted by the summer and continued in the autumn.

In the spring, London, followed by West Midlands, had a conspicuously higher mortality peak but in autumn it is Manchester and West Yorkshire – whereas now (late November/Early December) in London and West Midlands the problem is much less.

This is suggestive that what is involved is a natural process whereby London, because of the higher rate earlier, was infection saturated but is now closer to herd immunity – whereas Manchester and West Yorkshire that were spared earlier were, as a result, left with a greater part of the population still susceptible to the virus.

Indeed, if we look more closely at the sub regional level we can see the same picture of uneven and patchy spread of the disease within the sub region of Mancher that we saw before at the national level – within the sub region there are higher levels of infection in patches like Wigan, Rochdale and Oldham in the autumn – areas that escaped the worst of the spring epidemic because they are more peripheral and so were left with a higher proportion of still susceptible people while Manchester proper, and Bolton, were not.

Conversely, although London was saturated in the Spring, particularly in Brent, Croydon and Barnett, there were few patches that escaped and now have a greater problem in the autumn – in fact the one left vulnerable was Havering.

In the spring there was no tiered differentiation in behavioural or regulatory driven human responses so that would not explain Havering being differently vulnerable. To repeat: the autumn surge was because of different levels of susceptibility and immunity resulting from the first wave – NOT different behavioural responses in Havering from other places in London.

Note: See update comment about the situation in London at the end of the text.

Pseudo-epidemics caused by false positive testing

This might be part of the reason why the contagion came back in the autumn in some of the places remaining where it had earlier taken hold less intensively. The other reason why it might have appeared to come back intensively in the autumn was that the ramp up in testing created a pseudo epidemic of false positives. We may have a small real epidemic running alongside a pseudo epidemic.

Once again we have contested interpretations and the only way to finally clear up what the true situation is in regard to false positive tests ought to be to test the tests – at least to re-test anyone who gets a positive test. This is because if and when the prevalence of infection in a population is non existent or very low then a number of false positive tests is not only inconvenient to the individuals who have been tested (they may be quarantined unnecessarily). In addition their “positive” test results may be added up and wrongly seen as evidence of an epidemic which does not exist. Or perhaps false positives happen AND real positives in a mixed way, so that a real epidemic occurs but appears to be more serious than it really is.

In this regard there are enough reasons to believe that there might be a problem and to consider that checking is important. Firstly it is known that somewhere between 1 and 4 % of PCR tests may be false positives. False positives from a PCR test can arise for a variety of reasons, including contamination and poor procedures when taking tests and at laboratories. Under pressure to ramp up the number of tests taken and processed, procedures can degenerate so that the number of errors increases more than proportionately with the test. This report is by someone with a PhD in virology who worked in a laboratory in Milton Keynes and ended up working as an undercover agent for the Health and Safety Executive.

PCR tests work by “magnifying” tiny fragments of viruses in cycles. The number of cycles required to identify viral genetic material – the cycle threshold (Ct) – correlates inversely with the amount of viral genetic material actually present in the original specimen. At very high cycle thresholds one can find fragments of a dead virus which, if counted as positive, really says nothing about a current infection or infectiousness – and may be the result of an infection from some time past.

A “White Paper” on the future management of covid by a number of Irish doctors comments (giving copious academic references that can be found in the original text but not here):

Problems and inconsistencies with PCR testing have been documented extensively : non standardised specimen collection techniques; no gold standard test yet identified; different tests used in different labs; no standardised acceptable Ct values; inconsistent quality assurance programs; false positives; identification of irrelevant dead viral genetic material which can persist for months after infection; potential contamination of specimens, to name a few. Poorly designed PCR testing regimes can drive cases in infectious disease outbreaks and several reports exist of “pseudo” epidemics caused by over sensitive or poorly regulated PCR testing regimes. Patients with Ct values of >35 are extremely unlikely to be infectious unless they have been tested in the early stages of infection. Repeat testing of such cases (with PCR or antigen techniques) should be standard, is consistent with existing HPSC policy, and would give clarity on their true status while use of techniques causing enzymatic degradation of dead viral genetic material, before PCR testing, could be explored as a way to distinguish previous from current infections.

Notwithstanding that the problems are well known, little is being done to nail down the true extent of false positives. Why then has there been so little interest in double checking the testing?

Why the political indifference?

My answer would be because it would undermine the granfalloon belief system and the granfalloon project. Most people are uninformed and take on trust that experts and government know what they are doing. They are part of the “consensus trance”.

As already argued, a granfalloon is not the same as an attempt to trick people for malign motives – rather it is grounded in the complacent belief of a coalition that everyone in their network is acting with the best of intentions in the interests of everyone else – so complicated trivial details can be ignored. A granfalloon can operate on the basis of surface appearances which are not true. As long as people believe they are true, the coalition holds together and its main leaders are trusted.

On superficial impressions everything confirms the world view of the elite actors networked in governments, health service management systems, pharmaceutical companies, academics and media personalities who simplify and popularise the story of what is supposed to have happened, is now happening and the anticipated future.

Inside the grandfalloon coalition the group-think takes the form of a basic consensus. A “second wave” has happened and it shows that the lockdown was and is still necessary because when it was relaxed the disease eventually sprang back into existence and started growing again – as it would because 96% of the population were not infected after the first wave according to Flaxman et al and SAGE et al.

Because what has happened appears to be congruent with the granfalloon belief system, there is no compelling reason to check the tests. If a few results are false positives these can be thought of as just “noise”, not a signal of another reality. It is not really an issue because a growth of infections happened, as was expected, when the restrictions were relaxed.

Another way of describing this might be complacency which tends to be more likely among powerful people – although when independently minded people get together, and start arguing for, an alternative narrative which is sensed to be plausible, things may change. When that happens you might then get a vitriolic attack. As the saying goes:

First they ignore you. Then they attack you. Then they claim to have said the same thing all along.

On the other hand the people who can actually think for themselves are the ones that are prepared to revise their point of view. Those who can acknowledge that they might be wrong and are not at all sure of how things are can keep changing their mind. I have done that several times over this pandemic. I am retired so I have the luxury to do so.

In management and politics, leaders who keep on changing their mind are regarded as indecisive. To doubt, to U-turn, conveys uncertainty and is the very last thing that is expected of decisive leaders. As the poet Yeats understood….

The best lack all conviction, while the worst   
Are full of passionate intensity.

Political leaders don’t think of the possibility that they have been wrong because to be a decisive leader they have to be sure that they are right….. If a ‘wrong idea’ gains currency, the common project, the granfalloon beliefs like a belief about the efficacy of lockdowns, will be in danger, and that makes leaders like this angrily indignant at the subversion that doubts represent.

People might not want to take the vaccines, and that would never do. To remain a leader when they call on you to step forward, they cannot find that hundreds of thousands or millions would prefer to wait without losing power.

Unless this doubt can be spread, the theatre of the absurd is now moving into a new act with the vaccine and will continue until the economy implodes…

…but that is a hypothesis. Nothing is certain except that we all die eventually anyway.

Brian Davey
9th December 2020

Dec 16: Update on London situation

At the time of writing there is an upsurge in apparent cases (i.e. positive tests) in London and Kent. This has been linked to a new mutation of the virus and has then fed the rumour mill of speculations about policy. All viruses mutate and this ought not to be regarded as anything remarkable or threatening. This Nature article is about how there is “No evidence for increased transmissibility from recurrent mutations in SARS-CoV-2”.

The deeper problem is, however, that the greatest danger is from the confirmation bias in government and the health service where there is a vicious circle. The fear of the virus leads to more testing. More testing leads to more false positives and more false positives magnifies the appearance, though not the reality, of an epidemic. This then leads to more lockdown and more restrictions that damage the economy.

What we are therefore getting is a strange kind of policy-driven degrowth process – but unlike the degrowth called for by ecological activists and the degrowth movement, this kind of degrowth is characterised by (a) the close down, rather than the encouragement, of any kind of conviviality and the destruction of life quality along with obstruction to people coming together to respond to the underlying economic situation and (b) the loss of civil liberties of the most fundamental kind.

The thing that is needed to get us out of this trap and downward spiral is a serious examination of the tests – preferably through the courts taking a judgement on the tests. If, as I think most likely, we are suffering a “pseudo epidemic” and this is the judgement of the courts we can at last escape – although it will most likely then create a massive crisis of governance… But that would be the next episode…