Author: Simon Sheridan

One of my all-time favourite books is Gregory Bateson’s Mind and Nature. In the first chapter, playfully titled Every Schoolboy Knows, Bateson lays out a list of things that he wished were taught in school. One of them is: science proves nothing.

What this means is that any theory, no matter how well established, can always be overturned by new data which contradicts it. It also means that prediction has limits. Though something worked a thousand times before there’s no guarantee it will always work.

I think of this quote often alongside a quote by Richard Feynman that “science is the belief in the ignorance of experts.” The scientific spirit is always about questioning and searching and probing. It is about admitting fallibility and welcoming correction. Even the greatest expert cannot have the whole picture. There may be something they missed or it may be that the next result simply overturns everything they thought they knew. In fact, what very often happens with experts is that they stop looking and, in fact, stop being able to see what is right in front of them.

That science proves nothing doesn’t mean we can’t trust in it. We can and do rely on scientific knowledge all the time and much of the modern world would be impossible without such knowledge. We can and do rely on everyday physics and chemistry but things get less reliable as we move into the life sciences.

This was a fact well known by the above-mentioned Bateson.  The cybernetics and systems thinking movements of the 20^th century, of which he was a part, set out to address this and try and put biology and the other life sciences on a more solid, scientific footing.

The trouble with biological systems (and by extension with medicine) is that they belong to what Gerald Weinberg called medium number systems. Medium number systems feature a large number of variables that can’t be easily simplified. Models of such systems are fragile and complex and small errors can magnify and render the whole thing useless. Worse than useless, in fact, because the models can seem to work for a time and this leads to over-confidence. That over-confidence creates blow-ups when the model eventually fails. Weinberg saw the systems thinking approach as being a way to avoid such large failures. It involves a scepticism of models. Such scepticism is, in fact, a natural part of science but our modern “scientific” society seems to lack it. In fact, the corona event represents the opposite of Feynman’s scientific spirit. We put absolute faith in the “experts”.

There is a famous thinker around today whose work touches on some of these ideas and who is especially relevant to the corona event because he took a strong pro-lockdown, pro-interventionist position: Nassim Taleb.

I’ll show later that Taleb violated his own position when it came to the corona event. For now, let me sketch out what I believe that position to be in the abstract. Let me call it: the risk approach.

The risk approach does not concern itself with scientific models of medium number systems because it knows they are subject to blow-ups. Instead, it concerns itself with risk and specifically with exposure. You don’t worry about trying to calculate how bad things will be, you worry about how you will be affected if things get bad. If the worst-case scenario happened, how would that impact you and what can you do to mitigate the risk?

I like the example of earthquakes in this respect. You know earthquakes are going to happen. They happen all the time. You know some are going to big and some are going to be really big but you have no idea when the really big one is coming. How do you orientate yourself around this situation? You implement building codes which require buildings to be earthquake-proof as much as possible. Maybe you prevent building in areas where the risk is highest. You educate the population on what to do in the event of an earthquake. You structure things so that when an earthquake comes you are prepared. This preparation need not involve prediction and science beyond the most basic observations i.e. that earthquakes happen. It can be purely risk-based.

Now here is a key question: as part of your risk-based preparations, do you put time and money into the science of seismology or geology or whatever other science might be useful to mitigate the risk posed by earthquakes? On the surface, this seems like a prudent investment. Why not spend a little money understanding the science better?

Let’s say you do this and the seismologists make what seems like great progress and they invent new technologies that seem to be able to identify earthquakes and predict when they are going to happen and what size they will be. Everybody gets excited and corporations are formed to take government money and turn it into early warning systems with advanced and complex testing run through government bureaucrats who specialise in earthquake management. 

As a hardened risk expert, you are duty bound to be sceptical of all this. In fact, you should dismiss it entirely. Models are for suckers. You know that all models of medium number systems are subject to blow-ups. You won’t get fooled by randomness. You’ll ignore the models and the early warning systems and concentrate on risk.

The pandemic preparedness programs and influenza surveillance programs that were set up in the last twenty years were the equivalent of the earthquake early warning system described above. When they sprung into action at the start of the corona event, my expectation was that Taleb and the other risk-based thinkers would be highly sceptical of them. But they weren’t. Quite the opposite.

What happened with Taleb and many, many others is that they believed the early warning system without question. They were told a “new” virus had arrived on the scene. Having taken that at face value, they then proceeded to take all the infection statistics and death statistics at face value. The lack of scepticism and questioning was incredible in a man who has made a name for himself for being the destroyer of intellectual idols.

In the last post in this series I made the claim that what has happened in the last couple of decades is that the virologists and public health bureaucrats ascended and the doctors and epidemiologists were confined to second rung status. Somehow, Taleb exemplified this development perfectly. During the corona event he singled out the epidemiologist, John Ionnadis, for his special brand of ridicule. He made the exact criticism of him described above: models are for suckers. Small errors lead to blow-ups. You’d have to be a fool to listen to the epidemiologists.

What apparently didn’t occur to Taleb was that the virologists themselves are using very complex models and opaque test techniques. If Taleb is going to be sceptical of the epidemiologists, he should also be sceptical of the virologists. There is plenty to be sceptical about.

Setting aside all the problems with even identifying and testing for a virus (see the references in post one of this series for more detail on this), even if you assume you’ve found a virus and have fixed its genetic identity, you still need to know that it’s “new” and herein lies some basic analytic issues.

We are told sars-cov-2 was “novel” because its genetic signature was less than 90% identical to existing corona viruses? Why is 90% the cut off? What if it was 90.5%? Would it then not be “novel”? Given that RNA viruses are constantly mutating, how much genetic shift occurs simply by default? Will “sars-cov-2” still be the “same” in one year? In five years? In short, is it even valid to call a virus “new” based on a genetic analysis alone?

There are so many questions around the whole concept of “new” that I’m going to devote the whole of post 5 in this series to that issue.  

For now, it is enough to say that Taleb was fooled by virology. Where he should have been sceptical he unquestioning believed what he was told. Taleb of all people should have been suspicious of all what was happening but he went off with the virological fairies.

It has been joked by Michael Driver that the Taleb position was The Panic Principle (a play on Taleb’s beloved Precautionary Principle). Taleb lost the scepticism which forms the foundation of his risk-based approach. Like so many others, this led him into frankly quite ridiculous speculation with rampant cherry picking of anecdotal evidence. Here is a story about some child getting sick, here is a story about embolism or brain issues, here is a story about how antibody tests results are coming back very low and we won’t get herd immunity. These were neither proper science nor proper risk analysis. Embolism, for example, is also seen in a small number of influenza cases. Shouldn’t we therefore shut society down for every influenza pandemic? Would the risk-based approach tell us to do that?

Taleb might respond to this with his story about how it is better to mistake a rock for a bear than a bear for a rock. In other words, it’s better to overreact to a possible pandemic than not to. But this is quite a useless point. There are always pandemics. Using this criterion we could justify locking down society permanently. Besides which, in this case we didn’t just mistake the rock for a bear, we tripped over and broke our leg while trying to run away. You can only have so much self-inflicted damage like that before a real bear catches up with you.

Viral disease does not exist in the virus but in the relationship between the virus and the individual (medicine) and the virus and the population (epidemiology). To focus on the virus alone is simply a category error.

Our society has not taken a risk-based approach to pandemics. We have taken a scientific approach. That scientific approach has led to a blow-up. The corona event is a huge error due to over-confidence in models that we had no right to be confident about. More specifically, it was faith in one model: the virological one to the expense other ones that could have balanced our perspective such as the epidemiological one.

Given that Taleb did not follow his own principles in this case, is it nevertheless still valid to use the risk approach to deal with pandemics? Is there a way to address risk that doesn’t rely on opaque scientific modelling? There certainly is and it involves forgetting about early warning systems and focusing on exposure to risk.

There are things we could do to reduce our exposure to communicable disease. Among these would be reduced movement of people at all levels. Make population centres as self-sufficient as possible so that when movement is restricted during a pandemic life can continue as normal. Building codes should ensure every building has appropriate ventilation and buildings are constructed from materials known to reduce disease transmission (wood, copper). Never allow public transport to get overcrowded. Reduce population density in general. Reduce lifestyle disease and chronic illness. Other public health measures to improve immune system health among the population. Promote healthy lifestyles. Re-structure the entire health model to move to preventative medicine rather than the current system of pill popping and symptom mitigation.

I’m sure the reader can think of more. Note that every single item on this list is the opposite of the direction our society has been headed in over the last few decades. Is that just a coincidence?

But is this purely risk-based approach the correct approach? 

I don’t believe so.

Unlike with earthquakes, biological systems are adaptive. We are not defenceless against viruses. We have an immune system that knows exactly what to do with them. The system is not perfect. It doesn’t guarantee that you won’t get sick. But that’s life.

Over the past twenty years we have seen unprecedented movement of people around the world. In any of the major cities of the world you had people from all corners of the globe going through and bringing their microbiome with them. Has this led to an explosion in disease and illness? Not as far as I can tell. Ironically, people like Taleb flew all around the world without wearing masks or taking other precautions. They deliberately exposed themselves to ‘new’ viruses (viruses that their immune system had never seen before) and apparently never gave it a second thought. Now they are worried about a virus coming to them? That doesn’t sound like proper risk analysis to me.

The truth is, the number of variables at play when it comes to viral disease is enormous. There’s the viruses and their constant mutation. There’s the immune system and its response to viruses: antibodies, T-cells, other things we don’t even know about yet. There’s social and cultural factors around sanitation, body contact, hygiene. There’s issues of the general health of the population: diet, exercise, chronic illness. There’s environmental factors around climate, season, hours of sunlight, humidity etc.

Neither the risk approach nor the scientific approach is a silver bullet. They are tools in a toolkit and must be wisely applied. Simply dismissing one of them in the way that Taleb dismissed the epidemiological evidence is childish and dumb. It’s also incredibly dangerous. In the case of the corona event we relied exclusively on one tool in the toolkit – the PCR test – to the exclusion of everything else. We committed the grave sin about medium number systems that Gerald Weinberg warned about decades ago and put all our eggs in one basket. The result has been a disaster.

A mistake like the corona event is too large to be simply about one error. In my opinion, this is not really about science and it’s not really about risk. It’s about ethics. It’s about how you want to live your life. What you value in life. The corona event goes right to the heart of these matters because what is at stake ultimately is sickness and death.

Steve Jobs once said that he liked to focus on the question of his own death because it forced him to be clear about what was important in life. Maybe as a society we can’t deal with death because we have lost track of what is important to us. I’ll turn to this question in the final post in this series.

In the next post, I want to focus specifically on the question of death, why in modern western civilisation we are in denial of death and why this denial of death fueled the hysteria around the corona event.

All posts in this series:-

The Coronapocalypse Part 0: Why you shouldn’t listen to a word I say (maybe)

The Coronapocalypse Part 1: The Madness of Crowds in the Age of the Internet

The Coronapocalypse Part 2: An Epidemic of Testing

The Coronapocalypse Part 3: The Panic Principle

The Coronapocalypse Part 4: The Denial of Death

The Coronapocalypse Part 5: Cargo Cult Science

The Coronapocalypse Part 6: The Economics of Pandemic

The Coronapocalypse Part 7: There’s Nothing Novel under the Sun

The Coronapocalypse Part 8: Germ Theory and Its Discontents

The Coronapocalypse Part 9: Heroism in the Time of Corona

The Coronapocalypse Part 10: The Story of Pandemic

The Coronapocalypse Part 11: Beyond Heroic Materialism

The Coronapocalypse Part 12: The End of the Story (or is it?)

The Coronapocalypse Part 13: The Book

The Coronapocalypse Part 14: Automation Ideology

The Coronapocalypse Part 15: The True Believers

The Coronapocalypse Part 16: Dude, where’s my economy?

The Coronapocalypse Part 17: Dropping the c-word (conspiracy)

The Coronapocalypse Part 18: Effects and Side Effects

The Coronapocalypse Part 19: Government and Mass Hysteria

The Coronapocalypse Part 20: The Neverending Story

The Coronapocalypse Part 21: Kafkaesque Much?

The Coronapocalypse Part 22: The Trauma of Bullshit Jobs

The Coronapocalypse Part 23: Acts of Nature

The Coronapocalypse Part 24: The Dangers of Prediction

The Coronapocalypse Part 25: It’s just semantics, mate

The Coronapocalypse Part 26: The Devouring Mother

The Coronapocalypse Part 27: Munchausen by Proxy

The Coronapocalypse Part 28: The Archetypal Mask

The Coronapocalypse Part 29: A Philosophical Interlude

The Coronapocalypse Part 30: The Rebellious Children

The Coronapocalypse Part 31: How Dare You!

The Coronapocalypse Part 32: Book Announcement

The Coronapocalypse Part 33: Everything free except freedom

The Coronapocalypse Part 34: Into the Twilight Zone

The Coronapocalypse Part 35: The Land of the Unfree and the Home of the Safe

The Coronapocalypse Part 36: The Devouring Mother Book Now Available

The Coronapocalypse Part 37: Finale

Most people might not realise it, but we had practice runs for the corona event several times in the past couple of decades. For SARS-1, bird flu, swine flu, ebola and others, an illness was apparently noticed in hospitals leading to a suspected pandemic. Doctors around the world were primed to look out for symptoms of a “mysterious respiratory infection”. Models were produced predicting enormous numbers of deaths.  Large amounts of government money were set aside. And then the problem went away all by itself.

So why was this time different?

There have been two big developments in the last two decades that changed the way we handle pandemics.

Firstly, a global bureaucratic structure was set up to monitor pandemics. Among these was the WHO’s influenza surveillance programs which had the effect of expanding the test infrastructure around the globe. Alongside this public health bureaucrats were being primed to respond to a serious pandemic at various conferences and committee meetings.

Secondly, and most importantly, the PCR test technology became the default for viral testing. Like any technology, it has its strengths and weaknesses but it was a step up from the old cellular testing in terms of speed and accuracy. I don’t think it’s an understatement to say that the corona event could never have happened without it.

Ironically, the man who invented the PCR technique and won the Nobel Prize for his efforts, Kary Mullis, said it should never be used for viral testing and Mullis himself was a strident critic of the biomedical industry.

As an aside: if there were patron saints of science, Kary Mullis would be one of them. I highly recommend his autobiography Dancing Naked in the Mind Field and there are some great interviews with him available online.

So, we had the test infrastructure, the test technology and the public health bureaucracy in place. For past pandemics like SARS-1, we had the early warning system, the apocalyptic models predicting enormous death, the public health bureaucrats ready to get to work. Why didn’t we have a corona event?

There is one very simple explanation: we didn’t have a specific test for a specific virus. Without a test we couldn’t track ‘infections’.

In order to test for a virus, you must first identify it. That is the job of the virologist. There have been some technological breakthroughs in virology in recent times that have made identifying viruses quicker and easier using a genome analysis approach. The amount of time to identify a virus has dropped rapidly. The one man who personifies these developments and who was front and centre for the corona event was the German virologist, Christian Drosten.

Let’s go back to SARS-1 in 2003. On the occasion, Drosten identified the virus five months after the first outbreak of disease was suspected to have happened. At the time, this was considered radically fast. So fast that Drosten won an award for his efforts where he was complimented thus: “the speed with which they succeeded in identifying the new virus…is remarkable.”

Despite that breakthrough in speed, the SARS pandemic was already pretty much over by the time the virus was identified. A few months later, SARS-1 was over entirely and a great deal of money that had been invested in vaccine research went up in smoke.

Fast forward to 2009 where it took six months to find the supposed virus for swine flu and create a test for it. Once again, this was too late in the game. Respiratory virus pandemics usually go up like a rocket and come down just as fast. Five or six months is too long if you want to make a difference.

That all changed with the corona event.

The sars-cov-2 virus had apparently been isolated and a test for it produced by early January, only weeks after the supposed initial outbreak. The China CDC put its own PCR test into use early on. Christian Drosten also came onto the scene and created a test at his lab in Germany. It was available on January 16. For the first time ever, we had a test for a virus at the start of a suspected pandemic.

Let’s review a timeline of what happened at the very start of the corona event:-

• Mid-late December 2020: Doctors in Wuhan think they notice an unusual pattern of respiratory illness. These cases are recorded under the influenza surveillance program using the category “pneumonia of unknown origin”.
  • Note: in accordance with the rules of the influenza surveillance program, the China CDC is notified and they arrive to investigate and collect specimens etc.
  • Note: all that “pneumonia of unknown origin” really means as far as I can tell, is that they had some people with pneumonia and when they tested for known viruses the tests came back negative. Was this really unusual? It seems that many pneumonia cases are not tied back to specific viruses. The key point in this case seems to have been that there were a lot of unknown cases in a short period of time in the same location. But there are all kinds of questions here. How many cases of pneumonia every year are of unknown cause? If there are many, are all these cases investigated to find a virus? If not, why were these particular patient samples studied? What counts as a ‘lot’ of cases? What scientific criteria are used to determine when such an investigation should occur?
  • Note: at this point in proceedings there was no test for a virus and so a ‘case’ was defined by clinical symptoms alone. Specifically: “fever (≥38°C), radiographic evidence of pneumonia, low or normal white-cell count or low lymphocyte count, and no symptomatic improvement after antimicrobial treatment for 3 to 5 days following standard clinical guidelines.” Again, there are questions here. These criteria seem very vague and generic. Surely many pneumonia cases would fulfil these criteria. Surely cases like this would come up all the time so why was the alarm raised in this instance?
• January 3 2020: Samples are taken from a patient and genetically analysed. A “novel” virus is apparently discovered.
  • Note: there are all kinds of problems with the use of the word “novel” here and I will deal with this in more detail in a future post. All it actually means is that we human beings had never found it before. Just because we never found it before doesn’t mean it actually is “new”. At this point its newness is just a hypothesis. How could we actually prove that it is “new”? Even if it was “new”, that doesn’t mean it’s necessarily going to cause illness. Nothing has been proven at this point and yet even the article referenced above refers to an “emerging” pathogen. It already assumes the “newness” is a fact. That is at best sloppy science.
• Three more samples are genetically studied and tests created to match the genetic pattern. 
  • NOTE: the authors here claim to have “isolated” the virus although they admit that Koch’s postulates or some variation thereof were not fulfilled. This means no causal relation has been proven between the virus and an illness at this point.
• January 5, 2020: the WHO releases a statement saying the cause of the illness is still unknown. It states: “The symptoms reported among the patients are common to several respiratory diseases, and pneumonia is common in the winter season; however, the occurrence of 44 cases of pneumonia requiring hospitalization clustered in space and time should be handled prudently.” Sounds like very sensible advice but things were about to take off because…
• January 11, 2020: the first PCR test kits arrive in Wuhan. These were developed by the China CDC.
• January 16, 2020: Christian Drosten and his team in Berlin, Germany develop their own PCR test which is accepted by the WHO.
• January 18, 2020: the “case” definition is now updated to include two positive results on the PCR test. This is a crucial change whose importance cannot be overstated. It represents the shift from clinical symptoms to genetic identification of ‘cases’.
• January 20, 2020: 201 cases of ‘pneumonia of unknown origin’ reported.
  • Note: at this point we are still talking about an actual illness.
• January 26, 2020: 2000 cases of infection are reported.
  • Note: this is no longer about illness necessarily. Already at this early period “asymptomatic cases” were known and clinical symptoms seemed to vary widely. We are now talking about ‘infection’. The focus is now on the virus and not on the illness.

To summarise what appears to have happened in the early stages of the corona event:-

Some doctors noticed an apparently high number of pneumonia cases in Wuhan. The Chinese CDC came in to investigate. Based on what appears to be a very low number of samples, they identified a common genetic pattern among patients that apparently mapped to a previously unknown coronavirus. Within about two weeks, a genetic test (PCR) is developed and starts to be used to identify ‘cases’. This test was then put into widespread use and large numbers of ‘cases’ were found.

After about two weeks of such testing, on January 23, 2020 at 2am in the morning, the Chinese government announced it would lock down the city of Wuhan at 10am that day. 300,000 people are said to have left Wuhan in that eight-hour window (are people in Wuhan nocturnal?) and others got out before the highways were closed later that afternoon.

What stands out to me in this story is the speed in which everything happened. When I think of science, I think of slow, methodical, careful investigation. I think of peer review, control testing, blind testing. Normally in science there are disagreements and counter theories that need to be worked through over time. In this case we went from a hypothesised novel virus to shutting down cities in the space of a few weeks.

The truth is something had changed in the way we dealt with pandemics in the last two decades and that change represents the ascendancy of virology at the expense of epidemiology.

That slow and methodical approach is true for the discipline of epidemiology. But it is not true of modern virology. On the contrary, modern virology has been all about speed. Christian Drosten and his ilk have literally made it their life work to find viruses as fast as possible. In this quest they have been in league with the public health bureaucrats who have it in their heads that we must be able to find and respond to viral pandemics as quickly as possible. The problem is that just because you find a virus, even if it is ‘new’, doesn’t mean you have a problem. To know you have a problem requires epidemiology and that takes time. It’s not a coincidence that the epidemiologists were sidelined in the corona event. Other interests were being served.

The influenza surveillance programs, global lab networks, pandemic response conferences were all predicated on fast intervention. An entire system was set up for the purpose of intervening. In the past, it had never been able to justify an intervention because it didn’t have the test data. That was the crucial difference between this pandemic and past pandemics. With the PCR test in their hot little hands, the public health bureaucrats could start to identify ‘cases’, the number of cases seemed to explode and the panic button was hit.

That would have been bad enough but then the media got involved and through them, the public.

Respiratory viral pandemics are literally a yearly event, but they take place invisibly. They come and go without anybody paying them the slightest bit of attention. Remember that influenza pandemic in 2017 that killed 1.25 million people globally? Nah? Neither do I. Might have got a few reports on page ten of the newspaper if it was lucky.

Just as the first Gulf war was the first war to be broadcast live on television, the corona event was the first pandemic to get twenty-four hours a day news coverage and the centrepiece of that coverage has always been the ‘infection’ statistics. All anybody has been talking about is the number of people infected. You get up in the morning and check the ‘case’ count and wring your hands. Nobody thought ask whether any of the people who were ‘infected’ were sick or how sick they were.

Even the early epidemiological evidence for covid indicated that the corona event would be in the range of a severe flu. Symptoms varied widely, there were lots of asymptomatic cases, there were presumably lots of people who never got sick enough to go to hospital. An early case fatality rate of about 1-2% was expected to diminish by an order of magnitude over time as this is what always happens with such pandemics. These predictions by the epidemiologists turned out to be very accurate and covid is on track for a case fatality rate of about 0.1% when all is said and done.

As far as I have seen, there was never any epidemiological evidence that the corona event was something special or unusual. But the epidemiological evidence simply never made it into the public discussion. The epidemiologists were sidelined. One, Knut Wittkowski, was even censored by youtube for daring to suggest a number of sensible, fairly obvious reasons why the lockdown might be a bad idea and might actually be counter-productive to its stated intentions. Why is youtube censoring scientists talking about science now? Is calm, rational, objective disagreement now against the rules?

At various times throughout the corona event I have thought that it represents a failure of science, even a disgrace for science. But that’s too broad a brush to paint with. What happened specifically here is that the virologists and mathematicians (mathematical epidemiology) alongside the public health bureaucrats with their testing infrastructure created a perfect storm. For the first time in history we tracked an apparent viral pandemic in real time. Where they were listened to at all, the epidemiologists pointed out that there was no actual evidence that what was happening was particularly unusual or required radical measures. But they weren’t listened to. The slow, careful, methodical approach of epidemiology could never compete the speed and excitement of the ‘infection’ statistics and the doomsday models.

The corona event represents a watershed in how we react to pandemics. Public health bureaucrats had been just itching to intervene in a pandemic and they finally got their chance. The doctors and epidemiologists were elbowed aside and the virologists and public health bureaucrats ran the show. Whether we continue down this route or correct our course is going to play a massive role in what society looks like going forward. All of sudden, dystopian depictions of authoritarian societies are no longer the realm of science fiction. Will it turn out that Kafka wasn’t really a fiction writer but a Nostradamus in waiting?

To reiterate: the epidemiologists got it right in relation the corona event. Even the early predictions turned out to be accurate. We would have done well to listen to them.

However, there is arguably a weakness in the epidemiological approach and this is highlighted by people who say we should ignore the science and consider a pandemic from a risk mindset.

All epidemiology and medicine can do is look at the early pattern in a pandemic and say that it looks just like this other pattern that we have seen in other historical cases. Most of the time that’s going to be right. But what about when it isn’t? In that case, lots of people might die. That is a risk that comes from the fact that science never proves anything.

In the next post in this series, I’ll examine this statement and look deeper into the claim that pandemic response is not about science but about risk.

All posts in this series:-

The Coronapocalypse Part 0: Why you shouldn’t listen to a word I say (maybe)

The Coronapocalypse Part 1: The Madness of Crowds in the Age of the Internet

The Coronapocalypse Part 2: An Epidemic of Testing

The Coronapocalypse Part 3: The Panic Principle

The Coronapocalypse Part 4: The Denial of Death

The Coronapocalypse Part 5: Cargo Cult Science

The Coronapocalypse Part 6: The Economics of Pandemic

The Coronapocalypse Part 7: There’s Nothing Novel under the Sun

The Coronapocalypse Part 8: Germ Theory and Its Discontents

The Coronapocalypse Part 9: Heroism in the Time of Corona

The Coronapocalypse Part 10: The Story of Pandemic

The Coronapocalypse Part 11: Beyond Heroic Materialism

The Coronapocalypse Part 12: The End of the Story (or is it?)

The Coronapocalypse Part 13: The Book

The Coronapocalypse Part 14: Automation Ideology

The Coronapocalypse Part 15: The True Believers

The Coronapocalypse Part 16: Dude, where’s my economy?

The Coronapocalypse Part 17: Dropping the c-word (conspiracy)

The Coronapocalypse Part 18: Effects and Side Effects

The Coronapocalypse Part 19: Government and Mass Hysteria

The Coronapocalypse Part 20: The Neverending Story

The Coronapocalypse Part 21: Kafkaesque Much?

The Coronapocalypse Part 22: The Trauma of Bullshit Jobs

The Coronapocalypse Part 23: Acts of Nature

The Coronapocalypse Part 24: The Dangers of Prediction

The Coronapocalypse Part 25: It’s just semantics, mate

The Coronapocalypse Part 26: The Devouring Mother

The Coronapocalypse Part 27: Munchausen by Proxy

The Coronapocalypse Part 28: The Archetypal Mask

The Coronapocalypse Part 29: A Philosophical Interlude

The Coronapocalypse Part 30: The Rebellious Children

The Coronapocalypse Part 31: How Dare You!

The Coronapocalypse Part 32: Book Announcement

The Coronapocalypse Part 33: Everything free except freedom

The Coronapocalypse Part 34: Into the Twilight Zone

The Coronapocalypse Part 35: The Land of the Unfree and the Home of the Safe

The Coronapocalypse Part 36: The Devouring Mother Book Now Available

The Coronapocalypse Part 37: Finale

Humans have a cognitive bias for linear functions. One of the ways in which this manifests is that we expect the magnitude of the cause and the magnitude of the effect to be equal. This expectation works well in everyday situations.  If you throw a rock, the more effort you put into the throw, the further the rock will travel. The larger the rock, the heavier you expect it to weigh etc.  Linear functions, or at least what we perceive us as linear functions, form the basis for everyday life. Much of science education involves teaching the student to overcome this bias and understand alternative functions.

As the corona event unfolded earlier this year, various experts, and even the Chancellor of Germany, who is, after all, a scientist by training, took to the media to remind us that pandemics need to be understood as exponential functions. We heard all about the R0, the doubling time of cases and the possibly explosive growth of infections.

Nevertheless, most of the media presented the corona statistics as cumulative graphs rather than as log graphs. The cumulative graph, of course, looks linear thus satisfying our non-scientific preferences. It also looks scarier. A feature that appeals to the modern media.

So, we like linear functions. We expect the punishment to fit the crime. We demand an eye for an eye. We want a fair day’s pay for a fair day’s work. And when the government takes an extreme measure like locking down civil society, we expect that this must be in response to a genuine, highly dangerous threat. Only the most dire situation could justify such an unprecedented measure, we think to ourselves.

It was this expectation that formed my initial confusion about the corona event back when it was still mostly taking place in China. China had shut down an entire city on hours’ notice. We heard stories about people being welded in their apartments and other extreme measures. The assumption would be that this new virus must be super deadly.

But even in the early days of the pandemic, this didn’t make sense. The statistics didn’t look that bad. The case fatality rate seemed to be between 1-2% and the deaths were mostly among the elderly. It looked like a bad flu virus.

I started to look for other explanations. I started to wonder whether there wasn’t some political crisis going on in China. Perhaps it was a political thing. Maybe a civil war was breaking out in Wuhan. Maybe it was the latest move in the US-China trade war. Or maybe the Chinese government was trying to cover up what was really a health emergency and the official statistics were wrong.

Slowly, like green slime dripping down a wall, the virus leaked into our lives in the West.

By mid-March, it still didn’t look that bad. Epidemiological reports based on the evidence available at that time were estimating around a 1% case fatality rate that would likely fall by an order of magnitude because that’s what always happens with respiratory viral pandemics. It was going to be bad but not astronomically bad. Probably a little worse than the influenza pandemic in 2017 that was estimated to have killed 1.25 million people worldwide.

Western governments at the time seemed to agree with this diagnosis of the situation. Our leaders pushed back against a rising tide of fear that was being fed by an increasingly voracious media. They tried to reassure the public that the situation could be handled without the extreme measures seen in China.

The PR battle lasted about two weeks. Then, seemingly in unison, western governments rolled over and we went into preparations for the lockdown. Neil Ferguson’s doomsday model was splattered all over the media and other models were found that predicted all kinds of awful outcomes. From that point right up until now there was nothing but wall-to-wall fear mongering in the media. The cool, calm, objective voices of the epidemiologists were drowned out by a growing tide of hysteria.

Around that time I decided to spend what I thought was going to be ten minutes investigating how we test for the corona virus. I am a trained linguist and worked briefly in that capacity before switching to a job testing software. So, I was professionally curious to see how the medical profession does its testing for something that was becoming a potentially world-changing event.

That ten minutes turned into several hours. I couldn’t believe what I was reading. The tests used to detect corona virus were much much weaker than I had expected. As I delved deeper, I learned that much of the testing around viruses in general was weak and flimsy. This eventually led me all the way back to the germ theory of disease. To Louis Pasteur and Antoine Bechamp. It seemed to me that the victory of the germ theory of disease, something I had learned in school and forgotten about since, was nowhere near conclusive. At best, viruses were an edge case in that theory. But more to the point for the current crisis, the test techniques just didn’t seem strong enough to justify shutting down society.

To get from the virus to the thing we actually care about – illness – requires a chain of inference and at each step in the chain there is ambiguity and doubt. The PCR test that we use to determine an ‘infection’ (like seemingly all of the testing around viruses, it doesn’t conclusively prove an infection) matches your sample against a somewhat arbitrary genetic sequence that a virologist thinks identifies a virus. The evidence that that genetic sequence actually identifies the virus is not conclusive and the evidence that the virus actually causes an illness is also not conclusive. Because of this, there is a chance that the whole chain is invalid.

In the next post in this series, I will go into more detail about the PCR test and how it has been the decisive feature of the corona event. This test became ubiquitous in the last two decades. The shift to it as the main method of viral detection coincided with the setting up of a worldwide influenza surveillance program run out of the WHO. It is this infrastructure and this bureaucratic system that sprang into life at the very beginning of the corona event to produce the ‘infection’ statistics that have become an everyday part of our lives.

Imagine installing a fire alarm in a theatre when you knew it would go off sometimes even if there was no fire. Is that a smart thing to do? No, it’s not. It might cause a panic and people would be injured or killed as a result. But that’s what happened in the last couple of decades. We constructed an alarm system of questionable reliability and accuracy. It has been waiting to go off for twenty years and this year it finally went off.

I have been in a state of denial about all this. Surely, I couldn’t be right. Surely, somewhere there were people doing proper testing that conclusively proved these things. I’m still hoping somebody can show me the light and restore my faith in the system.

However, as the corona event has panned out, I have realised that what I learned was true. I’ve seen experts on television admit they have no gold standard test for the corona virus. Leading health bureaucrats have openly admitted in the media that they don’t have any firm data on the proportion of false positives or false negatives (because they don’t have a gold standard test by which they could establish those rates).

The truly strange thing to my mind that is that nobody seems to be trying to hide these facts. In the minds of these public health officials, shutting down entire societies is apparently not a problem and the fact that the accuracy of the tests is unknown doesn’t even matter. It’s better to be safe than sorry. (Really? Does anybody feel safe at the moment? And I have a feeling we are going to be sorry about what we’ve done).

Even by the sketchy veracity of all this test data, the corona pandemic has not proven to be anywhere near the doomsday predictions given to us in March. In fact, it has panned out exactly as the epidemiologists said it would. The case fatality rate looks like it will end up about 0.1%. It looks like global fatalities will be less than influenza in 2017. Despite this now overwhelming evidence base, as of the start of July we are still in hysteria-mode. Particularly here in Australia (and especially where I live in Melbourne) where efforts to eliminate the virus are starting to fray.

Because I came to understand how the testing works very early on, my perspective on the pandemic has been very different to most people. For that reason, it might be that things I have noticed will be of interest. Or maybe the reader will think I am a crank. Either way, better to be interesting than boring.

I start from the proposition that the corona event is a kind of mass hysteria. It’s the kind of thing you see in groups of people quite regularly and the internet has made us all one big group now and allowed the hysteria to spread around the globe instantaneously. I assume the testing is weak and that the test data has never shown any evidence that corona was something to be overly worried about. Where evidence was shown, it was cherry picked edge cases that were never a threat to the general public but which were published time and again in the media and on social media with the effect of spreading fear and panic.

Starting from these assumptions, I draw some very different conclusions about what has happened this year. I’ll expand on these ideas in subsequent posts but here is an overview of what I see as the main points.

•  Cargo-Cult Science: As a society, we are now in an era of cargo-cult science. The level of scientific and mathematical understanding among the general public appears to be woefully inadequate to make sense of a viral pandemic and the institutions of science, in particular in the biomedical sciences, have been corrupted by money and power. Even otherwise intelligent people failed to question the statistics they were being fed. It turns out that not a single statistic about the corona event can be taken on face value. “Infection rates”, “death rates”, “excess mortality”. All of them need quotation marks around them because they do not mean what they might mean at first glance. You have to take the time to understand how they are being measured. Then you have to put them into a historical context so that you can properly interpret what they signify about the health risk in question. The great Richard Feynman once said “science is the belief in the ignorance of experts.” As a society, we have swallowed whatever the experts told us and convinced ourselves it was science. That is not science. (Note: there were, of course, experts who got it right but we didn’t listen to them).
• The decline of traditional media: most people don’t have the time to spend understanding complex scientific concepts. That is where the media might have been able to help. But the traditional media has completely failed in what should be its main role of helping the public to make sense of what was happening. When we needed cool, calm, trusted voices we got hysterical fear mongering. The traditional media, now nothing more than a clickbait generator, completely failed in its ostensible job. Or, maybe it never was that way. Maybe the media was always just an extension of government. Maybe the media’s primary job here was simply to justify the government’s position. If so, they did a fantastic job. Scary good.
• The rise of social media: social media, which has been a big driver behind the demise of traditional media, allowed the lightning dissemination of fear and panic around the globe. I don’t believe politicians wanted to go to lockdown. I think they were forced into it by the growing hysteria.  They knew they would be held politically accountable for each and every death which would spread via social media posts. Imagine being a politician and suddenly the public was blaming you for every death from influenza or rhinovirus? It would be absurd, but there wouldn’t be much you could do about it. The lockdown was politically necessary because it shifted the politics away from people blaming politicians to politicians being able to take all the credit for “preventing deaths”. In actual fact, there is prima facie evidence that the lockdowns caused more deaths than they saved.
• Economic decline: the pandemic represents a natural consequence of decades of economic decline. This is most obvious in the US where that decline has had significant political ramifications. In Australia, our economy has been running on real estate, immigration and higher education bubbles for a long time now. We deluded ourselves into thinking we had avoided the fate of other countries in the west. There is a story to be told about how that economic decline made us more susceptible to illness.
• Folk language vs the language of science: the question of whether the virus and the illness are “new” is of personal interest to me because it is a classic example of the Sapir-Whorf hypothesis that I studied in my linguistics degree. That hypothesis is that language influences thought. In the case of the “novel” corona virus it certainly did that. It turns out that the whole idea of a new virus or a new illness is scientifically questionable but was extremely important in shaping the public discourse and the subsequent hysteria. 
• The denial of death: our response to the corona event has been massively out of proportion to the actual risk. In that sense, it is a mass hysteria. Like all hysteria, it is driven by deep seated cultural and emotional issues. One of most important of those I believe to be a fear of death and actually a denial of death in Western culture. I’ll discuss this in more detail.
• Germaphobia, biophobia and divorce from nature: somehow humans survived for hundreds of thousands of years without even knowing that viruses existed. Ever since the discovery of viruses, it was noted that people projected onto them deep seated and irrational fears. Germaphobia is tied in with the denial of death (and therefore the denial of life).
• A Kafkaesque nightmare: if the corona event was a work of fiction, the author would be Kafka. It is in large part a bureaucratic nightmare driven by the influenza surveillance programs instituted by the WHO and the public health bureaucrats in various countries. Those programs set up the testing infrastructure and it is that testing infrastructure which has driven the hysteria. The corona event represents the ascendancy of virologists and public health bureaucrats at the expense of doctors and epidemiologists. I will explain this further.
• An epidemic of testing: In past pandemic alerts (SARS 1, swine flu etc), all the infrastructure was in place but the missing ingredient was the test. For the corona event we had a test far earlier than in past pandemics and that test drove the whole shebang. I’ll talk about that in the next post of the series.
• The age of abstraction: we all have an innate aversion to visible, tangible illness that is biologically hardwired. But the corona test and other statistics are all abstractions.  The corona event was an abstraction layer on top of our biological aversion to disease. This is part of a broader tendency in modern society where abstractions rule. We care about GDP and inflation instead of actual wealth. We trade futures and ‘financial instruments’ instead of actual products. Now we worry about “infections” instead of actual illness.

One thing I will not cover in these posts, although I think it is arguably the most important thing anybody can do to educate themselves about the corona event, is the test techniques themselves. The best resource I have found on this is David Crowe’s website – https://theinfectiousmyth.com/

David passed away recently from cancer so I am not sure how long his site will stay up but the articles and the podcasts give a comprehensive look at all elements of testing for viruses including the establishment (or lack thereof) of an actual cause between a virus and an illness. His paper on the corona event is a great place to get an overview of his position – https://theinfectiousmyth.com/book/CoronavirusPanic.pdf

Another person who has done an excellent job explaining the testing is Andrew Kaufmann who has some great material up on youtube. This one in particular is a great starting point on the PCR tests – https://www.youtube.com/watch?v=8XST-nOgX-0

Note that both David and Andrew have some very alternative views on the subject of viruses. If you can’t get past that you’re probably not going to enjoy this series of posts. Having multiple explanatory frameworks is the norm in science. The fact that the germ theory exponents have out muscled the terrain theorists has less to do with science and more to do with politics as far as I can tell.

If you want to place eternal faith in the germ theory of disease that is fine by me but please don’t tell me that your position is “scientific” while mine is not. Science is about questioning assumptions, asking questions and challenging explanations. I hope you will challenge the explanations I give here and I welcome and encourage all constructive discussion in the comments.

All posts in this series:-

The Coronapocalypse Part 0: Why you shouldn’t listen to a word I say (maybe)

The Coronapocalypse Part 1: The Madness of Crowds in the Age of the Internet

The Coronapocalypse Part 2: An Epidemic of Testing

The Coronapocalypse Part 3: The Panic Principle

The Coronapocalypse Part 4: The Denial of Death

The Coronapocalypse Part 5: Cargo Cult Science

The Coronapocalypse Part 6: The Economics of Pandemic

The Coronapocalypse Part 7: There’s Nothing Novel under the Sun

The Coronapocalypse Part 8: Germ Theory and Its Discontents

The Coronapocalypse Part 9: Heroism in the Time of Corona

The Coronapocalypse Part 10: The Story of Pandemic

The Coronapocalypse Part 11: Beyond Heroic Materialism

The Coronapocalypse Part 12: The End of the Story (or is it?)

The Coronapocalypse Part 13: The Book

The Coronapocalypse Part 14: Automation Ideology

The Coronapocalypse Part 15: The True Believers

The Coronapocalypse Part 16: Dude, where’s my economy?

The Coronapocalypse Part 17: Dropping the c-word (conspiracy)

The Coronapocalypse Part 18: Effects and Side Effects

The Coronapocalypse Part 19: Government and Mass Hysteria

The Coronapocalypse Part 20: The Neverending Story

The Coronapocalypse Part 21: Kafkaesque Much?

The Coronapocalypse Part 22: The Trauma of Bullshit Jobs

The Coronapocalypse Part 23: Acts of Nature

The Coronapocalypse Part 24: The Dangers of Prediction

The Coronapocalypse Part 25: It’s just semantics, mate

The Coronapocalypse Part 26: The Devouring Mother

The Coronapocalypse Part 27: Munchausen by Proxy

The Coronapocalypse Part 28: The Archetypal Mask

The Coronapocalypse Part 29: A Philosophical Interlude

The Coronapocalypse Part 30: The Rebellious Children

The Coronapocalypse Part 31: How Dare You!

The Coronapocalypse Part 32: Book Announcement

The Coronapocalypse Part 33: Everything free except freedom

The Coronapocalypse Part 34: Into the Twilight Zone

The Coronapocalypse Part 35: The Land of the Unfree and the Home of the Safe

The Coronapocalypse Part 36: The Devouring Mother Book Now Available

The Coronapocalypse Part 37: Finale