offguardian--2020-04-19--Thinking Errors and the Coronavirus

Thinking Errors and the Coronavirus

The coronavirus doesn ’ t just make individual people ill – it threatens the whole of society too .
Measures used to control the virus destroy people ’ s livelihoods , trample basic freedoms and , if prolonged , could eventually bring about wholesale societal collapse .
However , thus far , talk about the virus has been focused on the medical and epidemiological facts – about which there seems to be an astonishing lack of agreement .
We still have no real idea of how dangerous the virus is , nor how easily it spreads , nor how many @ @ @ @ @ @ @ Yet , the absence of real information hasn ’ t caused governments to move extra cautiously .
On the contrary , it has encouraged them to take ever more radical steps .
To understand why , requires an appreciation of how all knowledge , most definitely including scientific facts too , is socially constructed , and how human beings , for all the philosophers ’ assurances to the contrary , are at heart , irrational animals .
We are fearful and gullible creatures whose response to crises is governed by deeply entrenched cognitive @ @ @ @ @ @ @ China announced its first death from the virus , a 61-year-old man who had purchased goods in a seafood market .
For the following two months the world followed the story essentially as spectators .
But then , on March 7 , an American public looking forward to the weekend instead woke to the grim news from Dr. James Lawler , a University of Nebraska Medical Center professor , that about 96 million Americans could become infected with coronavirus .
Of these , Lawler calculated 4.8 million would be hospitalized and nearly half @ @ @ @ @ @ @ !
For the Western world , watching the virus was no longer a spectator sport .
Worse news followed only days later when British experts in London published their research .
This seemed to show that without drastic action , not half a million but two and half million Americans faced an imminent and nasty end at the hands of the mystery virus .
The detailed and apparently authoritative assessment by Professor Neil Ferguson and his team at Imperial College in London predicted at least half a million deaths in the UK alone @ @ @ @ @ @ @ the usually jocular Boris Johnson , the politician who had hung from a zip wire waving a union jack to the delight of the media , took unsmilingly to the airwaves to address the nation .
“ I must level with the British public , ” the Prime Minister said .
“ Many more families are going to lose loved ones before their time.
” The broadcast was followed hours later by emergency regulations shutting down many aspects of normal life and announcing plans to quarantine all elderly people for a period – @ @ @ @ @ @ @ months .
At the same time , even as President Donald Trump ‘ hesitated ’ , over in the US , state legislatures began to rush out their own emergency plans .
A bill in Alabama called on individuals to ‘ fist bump ’ rather than shake hands ; New York suspended some mortgage payments for small businesses and Rhode Island formally requested that Trump ‘ declare a National Emergency for the coronavirus Pandemic ’ .
The TV and newspapers lapped it up .
Years of exaggeration plus a new internet-fueled appetite for @ @ @ @ @ @ @ had left the press no longer minded to separate fact from fiction .
Instead , all over the world , media , politicians – and health experts too – combined forces to convince the world that it was facing imminent doom .
The result was what social scientists call ‘ an information cascade ’ .
A radical shift in ideas and beliefs driven not by carefully assessed and evaluated data but rather by uncritically embraced observation and reinforcement of the views of others .
In an information cascade , the actions and decisions @ @ @ @ @ @ @ evidence you are directly acquainted with let alone your own judgement .
In this way , a particular view ‘ cascades ’ down the side of an ‘ informational pyramid ’ – like a waterfall .
How many waterfalls really cascade down pyramids ?
Not many .
But that is not the point .
Rather , the insight is that it is often easier for people , if they do not have either the ability or the interest to find out for themselves , to adopt the views of others .
This is @ @ @ @ @ @ @ As the economist Pierre Lemieux has put it , cascade theory reconciles ‘ herd behavior ’ with rational-choice because it is often perfectly rational for an individual to rely on information passed on to them by others .
Often… but not always !
And in the grim spring of 2020 , the news and media coverage , academic research and computer models and , above all , actual policy announcements all became a swirl of self-reinforcing misinformation .
A Reuters summary March 18 , 2020 headed : ‘ Factbox : Latest on the @ @ @ @ @ @ @ [ 1 ] accidentally hinted at a kind of herd panic .
Under the heading : DEATHS , INFECTIONS , it announced : • All 50 states in the United States have reported cases , with the total number of known infections surging past 6,400 .
The Senate is expected on Wednesday to vote on a multibillion-dollar coronavirus bill that passed the House of Representatives over the weekend .
• Ukraine , where a lawmaker tested positive , has imposed a state of emergency in the region around the capital Kiev .
• @ @ @ @ @ @ @ Wednesday from five to 19 and Malaysia warned of “ a tsunami ” of cases if people did not follow new restrictions as infections surged across Southeast Asia .
In a highly mediatized age , there is a bias towards seeing normal amounts of illness and death as exceptional .
Perspective is lost .
The seasonal toll of flu ( or “ flu like illness ” ) , the virus everyone agrees is much less serious than the new corona one , is between 290,000 and 650,000 people .
Worldwide , every year @ @ @ @ @ @ @ cases in Europe alone , with a death toll there estimated at between 15,000 and 70,000 each winter .
By comparison , as of March 16 , 2020 , a date at which a good proportion of Western Europe had entered ‘ lockdown ’ , there had been 2,337 deaths in Europe overall from the coronavirus with the first recorded European death , in France , on February 15 .
Put another way , by mid-March , amid peak political concern , the coronavirus had not killed exceptionally high numbers of people .
@ @ @ @ @ @ @ China , Taiwan and Hong Kong ) the numbers of deaths had peaked and then fallen back , it was surely speculative to predict huge increases in the future .
Speculative ?
But that ’ s where news stories and computer models played their part .
As Yoram Lass , a former Director General of the Israeli Health Ministry , has put it , the coronavirus was an illness with top-flight public relations .
PR which propelled politicians to draw up drastic measures ; while the measures themselves drove academics and journalists to @ @ @ @ @ @ @ Soon , in America , television anchors broke down in tears reading the news while The Guardian ran a characteristically self-serving feature about the ‘ strain ’ journalists were under .
Now , of course , illnesses are terrible things , and bring in their wake many personal tragedies , this virus no less than any other .
But this story rapidly spun out of control with the result that a crucial element of perspective along with accuracy was abandoned early on .
One kind of cognitive bias is ‘ Rear-view mirror syndrome @ @ @ @ @ @ @ a crisis by trying to find parallels with the past .
But the parallels chosen in this case were not , for example , the Swine Flu fiasco , where terrible prophecies came to naught – but rather the great flu epidemic of 1918 and even the Black Death of the Middle Ages .
Neither journalists nor politicians seemed to make even the quick trip to Wikipedia where they could have read that : Fewer still tried to read even short pieces by specialists like Stanford ’ s Professor of Public Health , @ @ @ @ @ @ @ “ “ mild ” coronaviruses may be implicated in several thousands of deaths every year worldwide , although the vast majority of them are not documented .
Instead , they are lost as noise among 60 million deaths from various causes every year .
[ 2 ] On the face of it , it ’ s quite an information failure when policymakers don ’ t appreciate the difference between terrifying science fiction scourges that can wipe out entire species and coronaviruses that actually infect many people every year , and are common especially @ @ @ @ @ @ @ with respiratory illness in the winter .
In a normal year , coronaviruses infect millions of people and kill thousands .
However , this year every even a solitary case and every early death became headline news .
Amazing , high magnification images of the virus exploding out of a human cell added a final ghastly , science fiction aspect to the tale .
Long , long ago , Aristotle , the man who said the Earth is fixed at the centre of the universe , proclaimed that Man was a rational animal @ @ @ @ @ @ @ the crisis revealed human beings as hopelessly irrational creatures whose thinking is driven not by calm consideration of ‘ the evidence ’ but rather by various kinds of deeply entrenched thinking errors and cognitive biases .
Here are some that throw light on the otherwise inexplicable worldwide response to the coronavirus .
First of all , there ’ s the bias caused by overconfidence .
Overconfidence results from a false sense of your skills and capabilities .
And governments are particularly prone to it .
One common manifestation is an illusion of control @ @ @ @ @ @ @ no control – things like the spread of an essentially airborne virus for example , or the ‘ contact tracing ’ of tens of thousands of people .
Illusions of control prompt people to talk with over-optimism about events and timings , such as that the ‘ curve of the epidemic will be flattened in two weeks or that a vaccine will be ready by September , or that virus spores will only travel a fixed distance of two meters .
It is all linked to infantile delusions of control rooted deep in @ @ @ @ @ @ @ because we want it to .
The flipside of overconfidence is ‘ Loss Aversion ’ and fear , things that with the coronavirus lead people to prioritise the threat of illness over concerns about writing off trillions of dollars of business and undermining the structures of society .
And , of course , fear is also at the heart of the phenomenon called ‘ Herd Mentality ’ .
The classic instance of this is finance , but herds rush about in many areas , from management innovations to everyday consumer fashions for clothes @ @ @ @ @ @ @ follow others on the sole basis that if so many people are doing something , well , ‘ there must be a good reason for it ’ , you have the potential for collective suicide .
Indeed , as many people including Stanford biophysicist Michael Levitt fear , the public health measures that have shut down large swaths of the economy could cause their own health catastrophe , as lost jobs lead to poverty and hopelessness .
“ What we need is to control the panic , ” Levitt has said , adding @ @ @ @ @ @ @ “ we ’ re going to be fine.
” Likewise , John Ioannidis , professor of Public Health at Stanford , says , that if you project the evidence of the mortality rate from the virus from the only real ‘ case study ’ of the virus that we have so far , the infamous cruise ship the Diamond Princess , onto the age structure of the U.S. population , the death rate among people infected with Covid-19 would be 0.125 % .
A death rate that is , in fact , rather @ @ @ @ @ @ @ deaths drive clicks , much of the media instead plays the role of “ availability entrepreneurs ” , as Edward Chancellor has put it for Reuters Breaking Views , placing excessive weight on images that are particularly vivid – such as halls full of grim-looking beds inside emergency hospitals or workers clad in full biohazard gear lowering coffins into graves .
And just as herd thinking means everyone must join the rush .
Groupthink requires everyone to defer to authority and individualism to give way to imitation .
Because shared ‘ social facts @ @ @ @ @ @ @ of order and control .
Indeed , as Edward Chancellor also says , in a crisis , contrarians are swiftly attacked by “ mind guards ” , .
A quick trip to Twitter will illustrate this .
Here , people I ’ ve conversed with for years there have told me in no uneertain terms , to “ just stop “ disputing the consensus , while even well-entrenched commentators like Peter Hitchens of Britain ’ s Daily Mail and Simon Jenkins of The Guardian , used to thousands of grovelling , approving comments @ @ @ @ @ @ @ daring to suggest that governments might be reacting inappropriately to the coronavirus .
Tolerating ambivalence and ‘ not knowing ’ plays a key role in maintaining openness to new information .
In contrast , anxiety during a perceived crisis leads to over-commitment to preferred narratives , and a failure to recognize their provisional nature .
It blocks out certain facts , such as that , for example , a surely noteworthy 99 % of Italian Covid-19 fatalities had several co-morbidities , to use the now prevalent jargon term .
( Research into 355 @ @ @ @ @ @ @ victims , 0.8 per cent , had been clear of illnesses before they were infected . )
Yet reports didn ’ t make a clear distinction between deaths “ precipitated ” by the virus and those “ caused ” by it .
Above all , Groupthink suppresses and distorts the collective memory .
Even though very recent history records multiple times when viruses sparked ‘ pandemic scares ’ in the West , and how each time the evidence for them was twisted to fit various agenda including the interests of Big Pharma – @ @ @ @ @ @ @ benefited from .
This kind of collective amnesia is very convenient for certain people .
It would otherwise be notable that Neil Ferguson of London ’ s Imperial College , one of the leading voices calling for radical social distancing and lockdown measures to combat the ‘ threat ’ of the coronavirus , was likewise pressing very similar strategies , based on very similar arguments during earlier epidemics , such as Swine Flu , which in the event turned out to be much less dangerous than his models predicted , as well as @ @ @ @ @ @ @ in which he insisted that all the cows not only from infected farms but neighbouring farms too had to be slaughtered .
Which they were , at a cost of many millions of pounds , producing apocalyptic scenes of vast funeral pyres .
There never was a good argument for the policy and in due course it was seen as a dreadful fiasco .
After such ‘ false alarms ’ , the world was supposed to have become more skeptical , and the WHO , in particular , to have changed its approach @ @ @ @ @ @ @ decade after the ‘ Swine Flu ’ fiasco , it is striking how much the public and political coverage has again coalesced around certain myths and misunderstandings of the virus and how dissenting voices , even of specialists like John Ioannidis , have been marginalised ( meaning confined to specialist publications ) while a false ‘ consensus ’ of ‘ all the experts ’ is created .
In a world in which scientists with computers have replaced priests with crucifix as the sources of unchallengeable truth and wisdom , the history of science @ @ @ @ @ @ @ phrase , that scientific progress is not and has never been solely and calmly about facts – far less , Platonic truths – at all , but is instead , a brutal fight in which the dominant view ( or paradigm ) invariably seeks to suppress its rivals .
Kuhn ’ s theory of so-called paradigm shifts should remind us how easily faulty reasoning can flourish and become entrenched .
But it doesn ’ t .
For better or for worse , the philosophy of science should remind us that individuals can influence @ @ @ @ @ @ @ For better , Louis Pasteur did it by challenging Aristotle ’ s thousand-year dogma that life is continually springing out of everyday chemicals in the air , mud and water , discovering germs and microorganisms .
For worse , activist researcher Ancel Keys managed to persuade governments and populations alike in the 1960s and 70s , that ‘ fatty foods ’ like cheese and butter really were killing everyone .
And now it seems that a handful of activist mathematical modellers of epidemics have managed to change the way we view viruses – @ @ @ @ @ @ @ , essential to life .
The problem is , as Amos Tversky and Daniel Kahneman , those iconic figures in the study of human cognitive bias and the handling of risk , have pointed out [ 3 ] , that there are really two kinds of human thinking : fast and slow .
‘ Slow ’ is when you work things out .
‘ Fast ’ is what we use in a crisis .
We have evolved in desperate times to jump to conclusions , ignoring gaps in information and data .
This @ @ @ @ @ @ @ had evolutionary advantages ago .
However , in the face of societal crises such as the coronavirus , it is careful , slow thinking that is needed .
Alas , it is ‘ fast thinking ’ that it gets .
Take the work of the computer modelers , for example .
These , just as much as members of the public , freely admitted ‘ knowledge gaps ’ and relied on ‘ fast thinking ’ – plugging in easy assumptions – instead .
Unfortunately , as Maggie Koerth , Laura Bronner and Jasmine @ @ @ @ @ @ @ Magazine , called ‘ Why It ’ s So Freaking Hard To Make A Good COVID-19 Model ’ [ 4 ] : Academic point ?
Not at all .
Take that influential model of Imperial College , the one said to have influenced particularly the UK and US responses to the virus .
In an interview [ 5 ] with Jemima Kelly of the Financial Times , Neil Ferguson , the academic in charge of the team behind it , seemed to reveal that the recommendations that included taking away millions of people @ @ @ @ @ @ @ cases livelihoods too was based on… shifting sand .
Or as Ferguson told Kelly : Crucial figures , like that for the ‘ Case Fatality Rate ’ for the virus were simply plucked from the general swirl of misinformation .
Recall the real-life case study of the spread and deadliness of the coronavirus that came about because several passengers on the cruise ship , ‘ The Diamond Princess ’ , had contacted the virus – turning the whole ship , into a kind of giant , awful , experimental test-tube .
The virus @ @ @ @ @ @ @ particularly those cooking for other members of the crew .
Eventually , of the 3,711 passengers and crew aboard , some 700 tested positive .
Seven people died .
This was rapidly adopted as the benchmark ‘ case fatality rate ’ – 1.0 % – ( Ferguson uses 0.9 % ) but doing so ignored the crucial fact that the this was not a normal mix of people but instead a largely elderly population , in which the death rate from Covid-19 was bound to be much higher .
As John Ioannidis also @ @ @ @ @ @ @ of the crisis , “ Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population , the death rate among people infected with Covid-19 would be 0.125 % ” – only one eighth as high .
Indeed , while other media ‘ experts ’ , and academic ‘ modelers ’ were plugging in figures as high as 10 % for coronavirus fatalities , Ioannidis calculated that a reasonable lower bound figure for the case fatality ratio in the general U.S. population was a mere from 0.05 % !
However @ @ @ @ @ @ @ and death issues of public health , the strategy for computer modellers and governments alike was , in the words of the French philosopher Jean-Jacques Rousseau centuries ago on social life in general , to start by saying : “ Let us begin then by laying facts aside , as they do not affect the question ” .
All of which highlights the thinking error dubbed , GIGO , for ‘ Garbage In , Garbage Out , which is that of according the pronouncements of computers ( and computer models ) far more @ @ @ @ @ @ @ being – even though , in reality , what the computer says is determined by the information fed into it by humans .
As early as 1964 , in an era when computers didn ’ t have any of the aura that they do today , the researcher Joseph Weizenbaum warned that even “ extremely short exposure to a relatively simple computer program could produce powerful delusional thinking in normal people ” [ 6 ] .
And unfortunately , we are not talking about normal people in this case , but politicians .
@ @ @ @ @ @ @ cheerfully acknowledged by Ferguson in interviews , that the data he fed his computer models was largely provisional and debatable , did not detract from the enormous authority given to the computer ’ s eventual pronouncements .
And , what the computer models suggested , in their unchallengeable way , was that so-called self-isolation and social distancing was the universal solution .
The ‘ Italian model ’ for dealing with the virus was to be backed up by medical staff in cumbersome protective clothing ; soldiers patrolling the streets ; and legally enforced @ @ @ @ @ @ @ the whole population .
The strategy was to be adopted by many other countries even though , in Italy , it didn ’ t seem to have worked .
Indeed , the figures from that unfortunate country were so bad , that it looked if anything as if it was making things worse .
But then another cognitive bias is the so-called ‘ Narrative Fallacy ’ .
With things like the coronavirus , we have been offered many stories , but one of the most compelling is that about people going out , @ @ @ @ @ @ @ other people .
Notice too , that we are subliminally wired to expect this kind of three-part story – the beginning , the middle and then the end .
In the U.K. , the Prime Minister gave public addresses with not one but three messages strapped to his podium : ‘ Stay home / Protect the NHS / Save lives ’ .
Advertisers know the power of triples , but so do political advisors .
Newspapers described the virus as a tiny , streamlined machine , which engulfs the cells deep in the @ @ @ @ @ @ @ hijacks their command and control mechanisms , before finally killing them and spewing out more of the infectious virus .
In a mediatised age , storytelling is doubly important .
The bias recognises that humans are story-telling animals who naturally try to arrange facts and events in a sequence .
Alas , sometimes the story takes on greater authority than it really deserves , propelling us towards a supposed ‘ conclusion ’ .
Speaking of storytelling , a harrowing series of tweets by a health official in the Obama administration outlined how the @ @ @ @ @ @ @ overrun with coronavirus cases by 23 March and a million Americans would die .
The tweets by Andy Slavitt , the former acting administrator of Medicare and Medicaid under President Barack Obama , helped shift public opinion in the US .
How much expertise is there in a tweet ?
Not maybe enough to take world-changing decisions on .
But it didn ’ t seem to matter .
Like the man shouting “ FIRE !
” in the cinema , Slavitt ’ s words had an effect .
“ What are mayors , @ @ @ @ @ @ @ he asked .
“ That people are jamming the bars .
I get it .
Home from work .
Cooped up .
Crisis mentality .
We need to let steam off .
Shared experience .
But stop that .
All the bars and restaurants are closed now across Europe.
” Describing the situation in Italian hospitals in particular , and what it might mean for the US , he tweeted [ emphasis added ] : And there again you have the tell-tale fingerprint of an information cascade .
The policy was right because @ @ @ @ @ @ @ right .
Another clue as to the quality of his diagnosis came in his final tweet about the origins of the crisis .
It was a Republican President ’ s mismanagement that had caused it .
Thus politicians can not help but play their usual games even as the world teeters on the brink of disaster .
Which without doubt , it was doing .
Only not because of the health crisis that Slavitt and so many others foresaw , a crisis caused by a biological virus – but because of a social @ @ @ @ @ @ @ and misinformation .
But let ’ s not deceive ourselves that it is only politicians who misread information and rush about like fools .
Consider two small stories making up the big virus tale .
One was the rumor that it was being transmitted by people with no symptoms .
A report documenting transmission by an asymptomatic individual had been published in the New England Journal of Medicine on January 30 .
Of course , transmission by people without symptoms would be a huge problem .
A few weeks later , however , @ @ @ @ @ @ @ did have symptoms , it was just that the researchers had er… not asked .
Similarly , the respected medical journal The Lancet published on February 24 a shocking account by two Chinese nurses about their front-line experience fighting the coronavirus .
[ 8 ] Only it turned out that the account was not quite what it seemed : it was not a first-hand account .
The authors soon retracted their contribution which was as a letter .
Such examples show how sensationalism affects even the most prestigious scientific journals .
Or take @ @ @ @ @ @ @ Fatality Rate figures , widely quoted , had been produced by the World Health Organization ( WHO ) [ 9 ] .
Their really rather outrageously high figure of 3.4 % , was arrived at by simply dividing the number of deaths by the number of documented cases as of early March .
But of course the number of documented cases was far less than the real level of illnesses .
In Germany , for example , where testing for the virus was being carefully done , the CFR was… 0.2 % .
@ @ @ @ @ @ @ trust information they have read in several places , without appreciating that the views may feed off each other .
Journalists , for example , read each other ’ s reports and feel reassured to be part of a consensus .
Politicians read the reports and shift policies to fit the journalists expectations .
In the coronavirus crisis , many journalists felt it was their duty to direct readers thinking in one direction only .
In the case of ITV ’ s Robert Peston , their senior political editor , his obligations even @ @ @ @ @ @ @ And don ’ t even mention statistics .
Newspapers AND experts would endlessly note sudden surges in the number of cases , without ever linking that to the numbers of people tested .
( If you text ten times as many people one day , then the number of cases is bound to go up . )
Objectively , all the shocking figures printed in counters everywhere for the ‘ number of cases ’ were meaningless .
The elephant in the statistical bathroom was that most people avoided becoming a statistic – and @ @ @ @ @ @ @ symptoms – would stay away from doctors or hospital and thus never be tested or reported .
Nearly one-fifth of the passengers on the Diamond Princess who in fact turned out to be infected with the virus had no symptoms .
When passengers were tested : This lacuna was convenient because everywhere the political solutions offered revolved around ‘ social distancing ’ and the shutting down of all but ‘ essential ’ services .
We were supposed to imagine only a few thousand people had the virus , not a quarter or a @ @ @ @ @ @ @ : the computer modeling of the virus , that seemed so detailed and comprehensive , and fed fears of the disease , was based on very shaky assumptions .
For example , according to Professor Ferguson ’ s model , fewer than 5 % of people are infected , but according to researchers at Oxford ’ s Evolutionary Ecology of Infectious Disease lab , it could be ten times that , higher than 50 % .
Unfortunately , as logicians say , any conclusions at all follow – perfectly logically – from false @ @ @ @ @ @ @ Magazine [ 11 ] , John Ioannidis explained : “ If we assume that case fatality rate among individuals infected by SARS-CoV-2 is 0.3 % … ” ( which he says is only the ‘ mid-range ’ estimate from Diamond Princess analysis ) “ …and 1 % of the U.S. population gets infected… this would translate to about 10,000 deaths.
” This sounds a huge number , but is “ within normal flu toll ” .
However , such voices were drowned out .
Instead , terrifying predictions and lack of actual data @ @ @ @ @ @ @ calls for a strict policy of social isolation , and for medical systems to move quickly to reorganize and prioritize resources ready for the expected mass epidemic .
The immediate result was radical lockdowns of whole populations – actions that were unprecedented in peacetime .
The longer term result was that the global economy and society sustained serious damage from an epidemic that , as Ioannidis also put it , otherwise accounted for “ less than 0.01 % of all 60 million annual global deaths from all causes and that kills almost exclusively @ @ @ @ @ @ @ .
And all the time , even as media and politicians rushed frantically from rash idea to rasher policy , the facts were there in plain sight – only no one was prepared to look at them .
No one even attempted to explain how long social distancing measures and lockdowns could be maintained for months , even years potentially , without major consequences to the economy , society , and mental health .
Let alone how unpredictable effects including financial crisis , unrest , civil strife , war , and a ripping @ @ @ @ @ @ @ .
Instead , what people were fed were soundbites .
Like this one from London ’ s otherwise ‘ liberal ’ radio station , LBC : Lockdown was the most disastrous part of a policy taken by many countries and American states supposed to ‘ slow down ’ the spread of the virus , yet we must accept it had popular support .
Even though , the idea was to discourage people from leaving their homes , for walks or cinemas or cafés , and to require them to stay in claustrophobic proximity @ @ @ @ @ @ @ weeks on end .
In France , President Macron made long , emotional appeals to his ‘ compatriots ’ to join in a national struggle against ‘ an invisible enemy ’ , before listing respectfully those who had fallen already .
All public spaces were closed and citizens ( like myself ) were forbidden to leave their homes for weeks on end , except to buy essential foodstuffs in approved shops .
And to do this , they had to clutch an official document downloaded from the government website , setting out their @ @ @ @ @ @ @ interior minister , Christophe Castaner , ordered 100,000 military police to spread around the country to enforce the lockdown .
Of course , such people are immune from the virus – and can ’ t spread it either .
( Such a thought was no more irrational than the rest of the government ’ s plans . )
Writing in The Guardian [ 12 ] , Tobias Jones , that paper ’ s Italy correspondent , described his family ’ s life under lockdown .
He recalled how some of his friends had @ @ @ @ @ @ @ half-hour and put on surgical gloves before doing everyday actions like opening doors .
“ It ’ s hard not to begin to doubt your own sanity and wonder whether it ’ s rational to be following all these restrictions and rituals ” .
Quite .
Public bodies too were neurotically washing things .
Lorries sprayed streets with disinfectant , workers in rubber gloves and face masks stood by escalators wiping down the handrails , and of course everyone doing it wore facemasks .
Yes , the ones that protect other people from @ @ @ @ @ @ @ President ’ s Trump ’ s decision to close America ’ s borders made no scientific sense ( and nor does health screening at borders as it can not pick out people who may carry viruses but not yet have symptoms ) , even if in partisan political terms is seemed to reinforce his campaign themes of a strong fortress America – the one with a wall along the Mexico border .
Rechristening the virus “ the Chinese virus ” seemed to underline this xenophobic message .
Tying together all the plans however @ @ @ @ @ @ @ to ‘ Flatten the Curve ’ .
That is , to spread out the load of virus cases and relieve pressure on health services .
This had rapidly become the One Thing Everyone Agrees .
Yet even that simple relationship – lots of cases , overloading health services , so better to spread them out – is not entirely straightforward .
Because spreading infections out over a longer period of time can just as easily mean that instead of being overwhelmed during a short , acute phase , health services remain overwhelmed for @ @ @ @ @ @ @ services are overwhelmed , people die .
Because destroying livelihoods , disrupting social life and locking people in their homes for months kills people too .
In the absence of data , prepare-for-the-worst reasoning leads to extreme measures of social distancing and lockdowns .
Unfortunately , we do not know if these measures work [ 13 ] .
School closures , for example , may reduce transmission rates .
But they may also backfire if children socialize anyhow , if school closure leads children to spend more time with susceptible elderly family members @ @ @ @ @ @ @ parents ability to work , and more .
School closures may also diminish the chances of developing herd immunity in an age group that is spared serious disease .
So perhaps it is worth taking a moment to look at the background of one of the experts whose call for a swift clampdown on all social contact led to dramatic shifts in policy in both the UK and the US .
Professor Neil Ferguson , as I say , hails from Imperial College London – a university with a consolidated income of £1,033.0 @ @ @ @ @ @ @ the pharmaceutical industry .
Just days after the paper was published , Ferguson ’ s department of biomathematics announced it was sharing in £20 million of emergency coronavirus research investment courtesy of the UK government .
Not bad for one paper !
But the most revealing thing about Neil Ferguson and his department is that they had exactly the same concerns and exactly the same policy advice during the so-called ‘ Swine Flu ’ crisis back in 2009 .
Flashback to June 11 that year , and the World Health Organization was declaring @ @ @ @ @ @ @ grimmest ever – for a new pandemic sweeping the world .
This was the so-called Swine Flu or H1N1 virus , and despite having in previous years been found to have been wrong about the dangers of several other viruses , the WHO once again , sounded the deathly warning that ‘ this early pandemic and flu is somewhat similar to the 1918-1919 pandemic swine flu that killed millions ’ .
Exactly what this strain would do in the Fall and Winter of 2009 and into 2010 was unclear , the WHO said @ @ @ @ @ @ @ prepared.
’ Naturally , governments everywhere respected the advice of the World Health Organization , a U.N. agency which after all does so much good work combating disease and guiding research related to public health .
And so , after the Swine Flu warning , where necessary , they promised , schools and offices would be closed .
Facemasks were bought in the millions , and vaccines were stockpiled .
And also as part of their response , as I reported in my earlier book Paradigm Shift : How Expert Opinions Keep Changing @ @ @ @ @ @ @ Everything ( 2015 ) , a fount of ‘ advice ’ was offered to the public .
For example , people were told , when back at home in the evening , to disinfect dishes , cups and utensils by thoroughly soaking in detergent and washing and rinsing thoroughly everything by hand or in the dishwasher .
Everyone was to wash their hands frequently .
And if , despite staying away from work ordering the shopping by phone and disinfecting the dishes , they still fell victim – there was advice on ‘ @ @ @ @ @ @ @ , coughing , fatigue , congestion , muscle and bone ache , and vomiting and intestinal upset .
And then death .
No wonder governments spent so much to combat the threat .
No wonder , more specifically , that governments swiftly came up with large amounts of money to buy huge amounts of vaccine from pharmaceutical companies .
Yet , at the end of the day , Swine Flu proved to be a paper tiger , just as the skeptical doctors had indicated .
A year on , annoyingly , for the @ @ @ @ @ @ @ people could be found to be said to have died from ‘ H5NI ’ , even though ordinary ‘ flu regularly kills several tens of thousands of people each winter .
However , for a while , each of these viruses was the public health concern , we could say the fashion .
Quite possibly more people , suffering from other complaints , died from the ‘ emergency precautions ’ surrounding the virus , such as being refused entry to doctors surgeries or from being injected with the vaccine .
But these could @ @ @ @ @ @ @ And all over the ( rich ) world , millions of germ masks and vaccines began to deteriorate in storage , unused and unusable .
Back then , an erroneous piece of expert advice cost an unknown number of lives and enormous sums of money .
Not long after , two independent reports , one by the Council of Europe and another that appeared as a paper for the British Medical Journal ( 3 June 2010 ) put a belated spotlight on the fact that three of the crucial experts arguing for expensive @ @ @ @ @ @ @ Roche ( the makers of Tamiflu ) and GlaxoSmithKiline ( the makers of Relenza ) – were also paid consultants for the companies .
Now I don ’ t myself believe that individual researchers are knowingly skewing research reports in order to make money , either for themselves or their institutions .
But the structural pressures are there and they can create the same effect .
Research is a business and so its conclusions are skewed towards the ‘ needs ’ of the paymasters .
And you may well ask , how big @ @ @ @ @ @ @ answer is that they can be a very big deal indeed .
In the US alone , Congress had appropriated $ 7.65 billion in June to fight the 2009 pandemic [ 14 ] .
In the UK , in order to deal with the Swine Flu threat , the impressively titled and ennobled Chief Medical Officer , Sir Liam Donaldson , said that a £1 billion ( $ 1.5 billion ) emergency program of vaccination was needed .
If it sounds a lot for a small country , remember , without it – @ @ @ @ @ @ @ !
The most ‘ optimistic assessment ’ was for 19 000 deaths .
His fears were confirmed by virologists such as one Dr. John Oxford , who added that without immediate action he had calculated that soon half the population could be infected .
Imagine , tens of millions of people dying – and only the government able to save them .
But the funds made available for the coronavirus were on a totally different scale .
Even with the number of cases globally still relatively tiny , in March 17 , 2020 @ @ @ @ @ @ @ $ 14 billion to help its members to respond to the threat [ 15 ] .
What sort of things was the money to be spent on ?
One component was to pay for everyone in the population to be tested for the virus .
Vaccines make for profits , but testing is a great earner too .
Often in this case tests were to be followed by the isolation of anyone who tested positive .
Even though , as Galli , Prof. at Milan , warned , in a rare note of @ @ @ @ @ @ @ the asymptomatic population could be useless : Governments wouldn ’ t wish to implement pointless and even dangerous polices though , would they ?
Alas , the herd memory is short and nor are herds known for their willingness pause and reflect .
Otherwise they might have learned lessons from 1976 , when President Gerald Ford ’ s administration reacted at speed to the swine flu outbreak , ignoring the World Health Organization ’ s words of caution and vowing to vaccinate “ every man , woman and child in the United States.
@ @ @ @ @ @ @ , the flu turned out to be mild .
Worse , researchers discovered that some of the vaccinated — roughly 450 in all — had developed Guillain-Barré syndrome , a rare disorder in which the body ’ s immune system attacks the nerves , leading to paralysis .
At least 30 people died .
Or from 2017 , when a rushed campaign — endorsed by the WHO — to vaccinate nearly 1 million children for mosquito-borne dengue in the Philippines was halted for safety reasons .
The Philippine government indicted 14 state officials @ @ @ @ @ @ @ vaccinated children , saying the program was launched “ in haste ” .
But back to the earlier Swine Flu outbreak in the UK , the one where the Chief Medical Officer swept aside skeptical voices , and instead advised the British government to order without further delay 32 million face masks to go with that £1 billion-plus worth of vaccines .
In France and other European countries , a similar story had played out – another billion-dollar supply of vaccines stockpiled here , another mountain of unused face masks there .
With @ @ @ @ @ @ @ expensive .
Yet it ’ s worth recalling thought that for a few months the Swine Flu pandemic was also genuinely terrifying everyone .
Like the coronavirus , it had appeared around March and rapidly spread throughout many places on the planet , ( invitation for luridly colored world maps on websites ) all doubtless helped by sniffling travelers on airplanes .
The Center for Disease Control in the US started a website page to keep track of the death toll for 50 U.S. states and territories : by June 2009 the HTML @ @ @ @ @ @ @ .
The next month , a special counter on the World Health Organization website registered total cases already at 177,457 with a toll of 1,462 deaths .
Admittedly , the figures were not yet exceptional , but the question everyone was asking was how many more might die soon ?
Basing their view on U.S. statistics , and the lack of a jab for swine flu experts thought there would be ‘ about 300 million ’ at risk initially : ‘ typically , anyone who has not had the vaccine ’ .
For @ @ @ @ @ @ @ it had seemed to a terrified public that the only real way to avoid dying was to ‘ Get vaccinated as soon as possible ’ .
Advice , in other words coming from the drugs industry funded labs that certainly suited the industry .
Unfortunately , the vaccines would be available only in … early October .
Just as in the spring of 2020 , there were endlessly repeated helpful hygiene tips , such as to : • Avoid putting fingers and hands to the mouth or eyes since these are portals of @ @ @ @ @ @ @ from large crowds , and all infected people .
• Remember to wear a face mask .
Certainly if going out of the house .
• Wash hands regularly , before eating or drinking and after visiting the restroom .
With Swine Flu , much of the advice related to safety at school .
But with the coronavirus , even though school-age children were recognised as very low risk , schools were immediately shut down .
We should be suspicious of experts recycling old advice .
After all , they may be guilty @ @ @ @ @ @ @ phenomenon known as ‘ one model thinking ’ whereupon only evidence that fits the model is visible .
There is either a duck , or a rabbit [ 16 ] but not both , to use the example that Wittgenstein made famous , but originated in 1892 issue of Fliegende Blätter , a German humour magazine .
And there is Confirmation Bias , which is the idea that people seek out information and data that confirms their pre-existing ideas while ignoring contrary information however potentially significant for the decision .
The almost non-existent @ @ @ @ @ @ @ of views and strategies for the coronavirus shows that this is one of the most dangerous biases of them all .
Martin Cohen ( Twitter @ docmartincohen ) is a writer , lecturer and researcher who specialises in social science whose books have been translated into twenty different languages .
His doctoral research involved looking at social and psychological myths constructed around the power of computers and his books , including , Paradigm Shift : How Expert Opinions Keep Changing on Life , the Universe , and Everything ( 2015 ) have explored @ @ @ @ @ @ @ food myths and previous pandemic scares as well as the groupthink that enabled them .

Martin Cohen
“The end of everything we call life is at hand and cannot be evaded”
H. G. Wells (1946)
The coronavirus doesn’t just make individual people ill – it threatens the whole of society too. Measures used to control the virus destroy people’s livelihoods, trample basic freedoms and, if prolonged, could eventually bring about wholesale societal collapse.
However, thus far, talk about the virus has been focused on the medical and epidemiological facts – about which there seems to be an astonishing lack of agreement. We still have no real idea of how dangerous the virus is, nor how easily it spreads, nor how many people at the moment have it. Yet, the absence of real information hasn’t caused governments to move extra cautiously. On the contrary, it has encouraged them to take ever more radical steps.
To understand why, requires an appreciation of how all knowledge, most definitely including scientific facts too, is socially constructed, and how human beings, for all the philosophers’ assurances to the contrary, are at heart, irrational animals. We are fearful and gullible creatures whose response to crises is governed by deeply entrenched cognitive biases.
On January 11 2020, China announced its first death from the virus, a 61-year-old man who had purchased goods in a seafood market. For the following two months the world followed the story essentially as spectators.
But then, on March 7, an American public looking forward to the weekend instead woke to the grim news from Dr. James Lawler, a University of Nebraska Medical Center professor, that about 96 million Americans could become infected with coronavirus. Of these, Lawler calculated 4.8 million would be hospitalized and nearly half a million – 480,000 – would die!
For the Western world, watching the virus was no longer a spectator sport. Worse news followed only days later when British experts in London published their research. This seemed to show that without drastic action, not half a million but two and half million Americans faced an imminent and nasty end at the hands of the mystery virus. The detailed and apparently authoritative assessment by Professor Neil Ferguson and his team at Imperial College in London predicted at least half a million deaths in the UK alone.
Soon after, in London, the usually jocular Boris Johnson, the politician who had hung from a zip wire waving a union jack to the delight of the media, took unsmilingly to the airwaves to address the nation. “I must level with the British public,” the Prime Minister said. “Many more families are going to lose loved ones before their time.”
The broadcast was followed hours later by emergency regulations shutting down many aspects of normal life and announcing plans to quarantine all elderly people for a period – just to get started – of four months.
At the same time, even as President Donald Trump ‘hesitated’, over in the US, state legislatures began to rush out their own emergency plans. A bill in Alabama called on individuals to ‘fist bump’ rather than shake hands; New York suspended some mortgage payments for small businesses and Rhode Island formally requested that Trump ‘declare a National Emergency for the coronavirus Pandemic’.
The TV and newspapers lapped it up. Years of exaggeration plus a new internet-fueled appetite for ‘clickbait’ headlines and tantalizing images had left the press no longer minded to separate fact from fiction. Instead, all over the world, media, politicians – and health experts too – combined forces to convince the world that it was facing imminent doom.
The result was what social scientists call ‘an information cascade’. A radical shift in ideas and beliefs driven not by carefully assessed and evaluated data but rather by uncritically embraced observation and reinforcement of the views of others. In an information cascade, the actions and decisions of everyone else become more important than evidence you are directly acquainted with let alone your own judgement.
In this way, a particular view ‘cascades’ down the side of an ‘informational pyramid’ – like a waterfall.
How many waterfalls really cascade down pyramids? Not many. But that is not the point. Rather, the insight is that it is often easier for people, if they do not have either the ability or the interest to find out for themselves, to adopt the views of others. This is without doubt a useful social instinct.
As the economist Pierre Lemieux has put it, cascade theory reconciles ‘herd behavior’ with rational-choice because it is often perfectly rational for an individual to rely on information passed on to them by others. Often… but not always!
And in the grim spring of 2020, the news and media coverage, academic research and computer models and, above all, actual policy announcements all became a swirl of self-reinforcing misinformation.
A Reuters summary March 18, 2020 headed: ‘Factbox: Latest on the spread of coronavirus around the world’ [1] accidentally hinted at a kind of herd panic. Under the heading: DEATHS, INFECTIONS, it announced:
All 50 states in the United States have reported cases, with the total number of known infections surging past 6,400. The Senate is expected on Wednesday to vote on a multibillion-dollar coronavirus bill that passed the House of Representatives over the weekend.
Chile’s president declared a 90-day state of catastrophe on Wednesday.
Ukraine, where a lawmaker tested positive, has imposed a state of emergency in the region around the capital Kiev.
Indonesia’s death toll jumped on Wednesday from five to 19 and Malaysia warned of “a tsunami” of cases if people did not follow new restrictions as infections surged across Southeast Asia.
In a highly mediatized age, there is a bias towards seeing normal amounts of illness and death as exceptional. Perspective is lost. The seasonal toll of flu (or “flu like illness”), the virus everyone agrees is much less serious than the new corona one, is between 290,000 and 650,000 people.
Worldwide, every year, between four and fifty million symptomatic cases in Europe alone, with a death toll there estimated at between 15,000 and 70,000 each winter.
By comparison, as of March 16, 2020, a date at which a good proportion of Western Europe had entered ‘lockdown’, there had been 2,337 deaths in Europe overall from the coronavirus with the first recorded European death, in France, on February 15.
Put another way, by mid-March, amid peak political concern, the coronavirus had not killed exceptionally high numbers of people. And since in some countries (like China, Taiwan and Hong Kong) the numbers of deaths had peaked and then fallen back, it was surely speculative to predict huge increases in the future.
Speculative? But that’s where news stories and computer models played their part. As Yoram Lass, a former Director General of the Israeli Health Ministry, has put it, the coronavirus was an illness with top-flight public relations. PR which propelled politicians to draw up drastic measures; while the measures themselves drove academics and journalists to view the situation ever more apocalyptically.
Soon, in America, television anchors broke down in tears reading the news while The Guardian ran a characteristically self-serving feature about the ‘strain’ journalists were under.
Now, of course, illnesses are terrible things, and bring in their wake many personal tragedies, this virus no less than any other. But this story rapidly spun out of control with the result that a crucial element of perspective along with accuracy was abandoned early on.
One kind of cognitive bias is ‘Rear-view mirror syndrome’. This occurs when we evaluate a crisis by trying to find parallels with the past. But the parallels chosen in this case were not, for example, the Swine Flu fiasco, where terrible prophecies came to naught – but rather the great flu epidemic of 1918 and even the Black Death of the Middle Ages. Neither journalists nor politicians seemed to make even the quick trip to Wikipedia where they could have read that:
“Coronaviruses are a group of related viruses that cause diseases in mammals and birds. In humans, coronaviruses cause respiratory tract infections that can be mild, such as some cases of the common cold (among other possible causes, predominantly rhinoviruses), and others that can be lethal, such as SARS, MERS, and COVID-19.”
Fewer still tried to read even short pieces by specialists like Stanford’s Professor of Public Health, John Ioannidis, to discover that: ““mild” coronaviruses may be implicated in several thousands of deaths every year worldwide, although the vast majority of them are not documented. Instead, they are lost as noise among 60 million deaths from various causes every year.[2]
On the face of it, it’s quite an information failure when policymakers don’t appreciate the difference between terrifying science fiction scourges that can wipe out entire species and coronaviruses that actually infect many people every year, and are common especially in the elderly and in hospitalized patients with respiratory illness in the winter.
In a normal year, coronaviruses infect millions of people and kill thousands. However, this year every even a solitary case and every early death became headline news. Amazing, high magnification images of the virus exploding out of a human cell added a final ghastly, science fiction aspect to the tale.
Long, long ago, Aristotle, the man who said the Earth is fixed at the centre of the universe, proclaimed that Man was a rational animal, but In 2020, instead, the crisis revealed human beings as hopelessly irrational creatures whose thinking is driven not by calm consideration of ‘the evidence’ but rather by various kinds of deeply entrenched thinking errors and cognitive biases.
Here are some that throw light on the otherwise inexplicable worldwide response to the coronavirus.
First of all, there’s the bias caused by overconfidence. Overconfidence results from a false sense of your skills and capabilities. And governments are particularly prone to it.
One common manifestation is an illusion of control in matters over which you actually have no control – things like the spread of an essentially airborne virus for example, or the ‘contact tracing’ of tens of thousands of people.
Illusions of control prompt people to talk with over-optimism about events and timings, such as that the ‘curve of the epidemic will be flattened in two weeks or that a vaccine will be ready by September, or that virus spores will only travel a fixed distance of two meters. It is all linked to infantile delusions of control rooted deep in our reptile brain that something will happen because we want it to.
The flipside of overconfidence is ‘Loss Aversion’ and fear, things that with the coronavirus lead people to prioritise the threat of illness over concerns about writing off trillions of dollars of business and undermining the structures of society.
And, of course, fear is also at the heart of the phenomenon called ‘Herd Mentality’. The classic instance of this is finance, but herds rush about in many areas, from management innovations to everyday consumer fashions for clothes or foods. When people opt to follow others on the sole basis that if so many people are doing something, well, ‘there must be a good reason for it’, you have the potential for collective suicide.
Indeed, as many people including Stanford biophysicist Michael Levitt fear, the public health measures that have shut down large swaths of the economy could cause their own health catastrophe, as lost jobs lead to poverty and hopelessness. “What we need is to control the panic,” Levitt has said, adding reassuringly that in the grand scheme, “we’re going to be fine.”
Likewise, John Ioannidis, professor of Public Health at Stanford, says, that if you project the evidence of the mortality rate from the virus from the only real ‘case study’ of the virus that we have so far, the infamous cruise ship the Diamond Princess, onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%. A death rate that is, in fact, rather similar to flu.
Unfortunately, since deaths drive clicks, much of the media instead plays the role of “availability entrepreneurs”, as Edward Chancellor has put it for Reuters Breaking Views, placing excessive weight on images that are particularly vivid – such as halls full of grim-looking beds inside emergency hospitals or workers clad in full biohazard gear lowering coffins into graves.
And just as herd thinking means everyone must join the rush. Groupthink requires everyone to defer to authority and individualism to give way to imitation. Because shared ‘social facts’ reduce anxiety by offering a sense of order and control. Indeed, as Edward Chancellor also says, in a crisis, contrarians are swiftly attacked by “mind guards”,. A quick trip to Twitter will illustrate this.
Here, people I’ve conversed with for years there have told me in no uneertain terms, to “just stop“ disputing the consensus, while even well-entrenched commentators like Peter Hitchens of Britain’s Daily Mail and Simon Jenkins of The Guardian, used to thousands of grovelling, approving comments on their articles, are attacked for daring to suggest that governments might be reacting inappropriately to the coronavirus.
Tolerating ambivalence and ‘not knowing’ plays a key role in maintaining openness to new information.
In contrast, anxiety during a perceived crisis leads to over-commitment to preferred narratives, and a failure to recognize their provisional nature.
It blocks out certain facts, such as that, for example, a surely noteworthy 99% of Italian Covid-19 fatalities had several co-morbidities, to use the now prevalent jargon term. (Research into 355 deaths found that just three of the victims, 0.8 per cent, had been clear of illnesses before they were infected.)
Yet reports didn’t make a clear distinction between deaths “precipitated” by the virus and those “caused” by it.
Above all, Groupthink suppresses and distorts the collective memory. Even though very recent history records multiple times when viruses sparked ‘pandemic scares’ in the West, and how each time the evidence for them was twisted to fit various agenda including the interests of Big Pharma – but lessons from past cannot be benefited from.
This kind of collective amnesia is very convenient for certain people. It would otherwise be notable that Neil Ferguson of London’s Imperial College, one of the leading voices calling for radical social distancing and lockdown measures to combat the ‘threat’ of the coronavirus, was likewise pressing very similar strategies, based on very similar arguments during earlier epidemics, such as Swine Flu, which in the event turned out to be much less dangerous than his models predicted, as well as the ‘Foot and Mouth’ one in which he insisted that all the cows not only from infected farms but neighbouring farms too had to be slaughtered.
Which they were, at a cost of many millions of pounds, producing apocalyptic scenes of vast funeral pyres. There never was a good argument for the policy and in due course it was seen as a dreadful fiasco.
After such ‘false alarms’, the world was supposed to have become more skeptical, and the WHO, in particular, to have changed its approach to pandemics.
Instead, only a decade after the ‘Swine Flu’ fiasco, it is striking how much the public and political coverage has again coalesced around certain myths and misunderstandings of the virus and how dissenting voices, even of specialists like John Ioannidis, have been marginalised (meaning confined to specialist publications) while a false ‘consensus’ of ‘all the experts’ is created.
In a world in which scientists with computers have replaced priests with crucifix as the sources of unchallengeable truth and wisdom, the history of science shows, in Thomas Kuhn’s phrase, that scientific progress is not and has never been solely and calmly about facts – far less, Platonic truths – at all, but is instead, a brutal fight in which the dominant view (or paradigm) invariably seeks to suppress its rivals.
Kuhn’s theory of so-called paradigm shifts should remind us how easily faulty reasoning can flourish and become entrenched. But it doesn’t.
For better or for worse, the philosophy of science should remind us that individuals can influence the way we see the world. For better, Louis Pasteur did it by challenging Aristotle’s thousand-year dogma that life is continually springing out of everyday chemicals in the air, mud and water, discovering germs and microorganisms.
For worse, activist researcher Ancel Keys managed to persuade governments and populations alike in the 1960s and 70s, that ‘fatty foods’ like cheese and butter really were killing everyone. And now it seems that a handful of activist mathematical modellers of epidemics have managed to change the way we view viruses – the invisible other halo the human biome, essential to life.
The problem is, as Amos Tversky and Daniel Kahneman, those iconic figures in the study of human cognitive bias and the handling of risk, have pointed out[3], that there are really two kinds of human thinking: fast and slow. ‘Slow’ is when you work things out. ‘Fast’ is what we use in a crisis. We have evolved in desperate times to jump to conclusions, ignoring gaps in information and data. This leap before you look mindset may have had evolutionary advantages ago.
However, in the face of societal crises such as the coronavirus, it is careful, slow thinking that is needed. Alas, it is ‘fast thinking’ that it gets.
Take the work of the computer modelers, for example. These, just as much as members of the public, freely admitted ‘knowledge gaps’ and relied on ‘fast thinking’ – plugging in easy assumptions – instead. Unfortunately, as Maggie Koerth, Laura Bronner and Jasmine Mithani asked in an article for 538 Magazine, called ‘Why It’s So Freaking Hard To Make A Good COVID-19 Model’[4]:
“Every variable is dependent on a number of choices and knowledge gaps. And if every individual piece of a model is wobbly, then the model is going to have as much trouble standing on its own as a data journalist who has spent too long on a conference call while socially isolated after work.”
Academic point? Not at all. Take that influential model of Imperial College, the one said to have influenced particularly the UK and US responses to the virus.
In an interview [5] with Jemima Kelly of the Financial Times, Neil Ferguson, the academic in charge of the team behind it, seemed to reveal that the recommendations that included taking away millions of people’s basic rights and in some cases livelihoods too was based on… shifting sand. Or as Ferguson told Kelly:
…there is no master plan in the background being followed here. There is a lot of research being done in real time, which is feeding into policy, to try and work out: is there in some sense an optimal strategy which keeps the NHS functioning, allows more economic and social activity to continue than is going on at the moment and gets us through the next, frankly, 18 months? I don’t know quite what that will look like or even if it’s completely feasible. We don’t have a clear exit strategy at the moment.”
Crucial figures, like that for the ‘Case Fatality Rate’ for the virus were simply plucked from the general swirl of misinformation.
Recall the real-life case study of the spread and deadliness of the coronavirus that came about because several passengers on the cruise ship, ‘The Diamond Princess’, had contacted the virus – turning the whole ship, into a kind of giant, awful, experimental test-tube. The virus quickly spread through food service workers, particularly those cooking for other members of the crew.
Eventually, of the 3,711 passengers and crew aboard, some 700 tested positive. Seven people died. This was rapidly adopted as the benchmark ‘case fatality rate’ – 1.0% – (Ferguson uses 0.9%) but doing so ignored the crucial fact that the this was not a normal mix of people but instead a largely elderly population, in which the death rate from Covid-19 was bound to be much higher.
As John Ioannidis also pointed out, right from the start of the crisis, “Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%” – only one eighth as high.
Indeed, while other media ‘experts’, and academic ‘modelers’ were plugging in figures as high as 10% for coronavirus fatalities, Ioannidis calculated that a reasonable lower bound figure for the case fatality ratio in the general U.S. population was a mere from 0.05%!
However, it seemed that even with life and death issues of public health, the strategy for computer modellers and governments alike was, in the words of the French philosopher Jean-Jacques Rousseau centuries ago on social life in general, to start by saying: “Let us begin then by laying facts aside, as they do not affect the question”.
All of which highlights the thinking error dubbed, GIGO, for ‘Garbage In, Garbage Out, which is that of according the pronouncements of computers (and computer models) far more weight than anything produced by a human being – even though, in reality, what the computer says is determined by the information fed into it by humans.
As early as 1964, in an era when computers didn’t have any of the aura that they do today, the researcher Joseph Weizenbaum warned that even “extremely short exposure to a relatively simple computer program could produce powerful delusional thinking in normal people” [6]. And unfortunately, we are not talking about normal people in this case, but politicians.
For these, the fact, so cheerfully acknowledged by Ferguson in interviews, that the data he fed his computer models was largely provisional and debatable, did not detract from the enormous authority given to the computer’s eventual pronouncements.
And, what the computer models suggested, in their unchallengeable way, was that so-called self-isolation and social distancing was the universal solution. The ‘Italian model’ for dealing with the virus was to be backed up by medical staff in cumbersome protective clothing; soldiers patrolling the streets; and legally enforced, profound changes to the lives of the whole population.
The strategy was to be adopted by many other countries even though, in Italy, it didn’t seem to have worked. Indeed, the figures from that unfortunate country were so bad, that it looked if anything as if it was making things worse.
But then another cognitive bias is the so-called ‘Narrative Fallacy’. With things like the coronavirus, we have been offered many stories, but one of the most compelling is that about people going out, passing the virus on, and killing other people. Notice too, that we are subliminally wired to expect this kind of three-part story – the beginning, the middle and then the end.
In the U.K., the Prime Minister gave public addresses with not one but three messages strapped to his podium: ‘Stay home / Protect the NHS / Save lives’. Advertisers know the power of triples, but so do political advisors.
Newspapers described the virus as a tiny, streamlined machine, which engulfs the cells deep in the tiny air sacs of the lung, hijacks their command and control mechanisms, before finally killing them and spewing out more of the infectious virus.
In a mediatised age, storytelling is doubly important. The bias recognises that humans are story-telling animals who naturally try to arrange facts and events in a sequence. Alas, sometimes the story takes on greater authority than it really deserves, propelling us towards a supposed ‘conclusion’.
Speaking of storytelling, a harrowing series of tweets by a health official in the Obama administration outlined how the largest US cities and hospitals would be overrun with coronavirus cases by 23 March and a million Americans would die. The tweets by Andy Slavitt, the former acting administrator of Medicare and Medicaid under President Barack Obama, helped shift public opinion in the US.
How much expertise is there in a tweet? Not maybe enough to take world-changing decisions on. But it didn’t seem to matter. Like the man shouting “FIRE!” in the cinema, Slavitt’s words had an effect.
“What are mayors, governors and their staffs reporting?” he asked. “That people are jamming the bars. I get it. Home from work. Cooped up. Crisis mentality. We need to let steam off. Shared experience. But stop that. All the bars and restaurants are closed now across Europe.”
Describing the situation in Italian hospitals in particular, and what it might mean for the US, he tweeted [emphasis added]:
“EVERY REPORT describes this as a tsunami. And if it happens like a tsunami, in major cities we will have tens of thousands more cases than we have beds and we will have one ventilator for every eight people who need one.”[7]
And there again you have the tell-tale fingerprint of an information cascade. The policy was right because “every report” says it is right. Another clue as to the quality of his diagnosis came in his final tweet about the origins of the crisis. It was a Republican President’s mismanagement that had caused it.
“The original sin is Trump’s months long denial and his dismantling of public health and response infrastructure.”
Thus politicians cannot help but play their usual games even as the world teeters on the brink of disaster. Which without doubt, it was doing. Only not because of the health crisis that Slavitt and so many others foresaw, a crisis caused by a biological virus – but because of a social and economic rupture caused by rash actions and misinformation.
But let’s not deceive ourselves that it is only politicians who misread information and rush about like fools. Consider two small stories making up the big virus tale.
One was the rumor that it was being transmitted by people with no symptoms. A report documenting transmission by an asymptomatic individual had been published in the New England Journal of Medicine on January 30. Of course, transmission by people without symptoms would be a huge problem.
A few weeks later, however, it turned out that the specific patient did have symptoms, it was just that the researchers had er… not asked.
Similarly, the respected medical journal The Lancet published on February 24 a shocking account by two Chinese nurses about their front-line experience fighting the coronavirus.[8]
Only it turned out that the account was not quite what it seemed: it was not a first-hand account. The authors soon retracted their contribution which was as a letter. Such examples show how sensationalism affects even the most prestigious scientific journals.
Or take an influential early report of the Case Fatality Rate figures, widely quoted, had been produced by the World Health Organization (WHO) [9]. Their really rather outrageously high figure of 3.4%, was arrived at by simply dividing the number of deaths by the number of documented cases as of early March.
But of course the number of documented cases was far less than the real level of illnesses. In Germany, for example, where testing for the virus was being carefully done, the CFR was… 0.2%.
A further reasoning error occurs when people trust information they have read in several places, without appreciating that the views may feed off each other. Journalists, for example, read each other’s reports and feel reassured to be part of a consensus. Politicians read the reports and shift policies to fit the journalists expectations.
In the coronavirus crisis, many journalists felt it was their duty to direct readers thinking in one direction only. In the case of ITV’s Robert Peston, their senior political editor, his obligations even involved controlling the way people walked.
Robert Peston @Peston
Among the many emails I receive with brilliant ideas to suppress and conquer #Covid19, I really like this simple one – that supermarket aisles should be made one-way lanes to reduce the risk of accidental proximity to other shoppers. Is this happening anywhere?
And don’t even mention statistics. Newspapers AND experts would endlessly note sudden surges in the number of cases, without ever linking that to the numbers of people tested. (If you text ten times as many people one day, then the number of cases is bound to go up.)
Objectively, all the shocking figures printed in counters everywhere for the ‘number of cases’ were meaningless. The elephant in the statistical bathroom was that most people avoided becoming a statistic – and if they had only mild or no symptoms – would stay away from doctors or hospital and thus never be tested or reported.
Nearly one-fifth of the passengers on the Diamond Princess who in fact turned out to be infected with the virus had no symptoms. When passengers were tested:
There were so many infected people with no symptoms onboard. They even surprised themselves. For example, there were spouses—the husband had a test, due to having the symptoms of the flu, while the wife, who did not have any symptoms, also had the test, just because she was in the same room with him—he was negative, but she was positive.” [10]
This lacuna was convenient because everywhere the political solutions offered revolved around ‘social distancing’ and the shutting down of all but ‘essential’ services. We were supposed to imagine only a few thousand people had the virus, not a quarter or a third of the population.
Bottom line: the computer modeling of the virus, that seemed so detailed and comprehensive, and fed fears of the disease, was based on very shaky assumptions.
For example, according to Professor Ferguson’s model, fewer than 5% of people are infected, but according to researchers at Oxford’s Evolutionary Ecology of Infectious Disease lab, it could be ten times that, higher than 50%. Unfortunately, as logicians say, any conclusions at all follow – perfectly logically – from false premises.
In an article for STAT Magazine[11], John Ioannidis explained: “If we assume that case fatality rate among individuals infected by SARS-CoV-2 is 0.3%…” (which he says is only the ‘mid-range’ estimate from Diamond Princess analysis) “…and 1% of the U.S. population gets infected… this would translate to about 10,000 deaths.” This sounds a huge number, but is “within normal flu toll”.
However, such voices were drowned out. Instead, terrifying predictions and lack of actual data were was the context for near universal calls for a strict policy of social isolation, and for medical systems to move quickly to reorganize and prioritize resources ready for the expected mass epidemic.
The immediate result was radical lockdowns of whole populations – actions that were unprecedented in peacetime. The longer term result was that the global economy and society sustained serious damage from an epidemic that, as Ioannidis also put it, otherwise accounted for “less than 0.01% of all 60 million annual global deaths from all causes and that kills almost exclusively people with relatively low life expectancy”.
And all the time, even as media and politicians rushed frantically from rash idea to rasher policy, the facts were there in plain sight – only no one was prepared to look at them.
No one even attempted to explain how long social distancing measures and lockdowns could be maintained for months, even years potentially, without major consequences to the economy, society, and mental health. Let alone how unpredictable effects including financial crisis, unrest, civil strife, war, and a ripping of the social fabric could be avoided. Instead, what people were fed were soundbites. Like this one from London’s otherwise ‘liberal’ radio station, LBC:
@LBC If you’re still planning to go out this weekend despite bars being closed, first listen to this remarkable call from an intensive care doctor who warned: “If you go out, it’s going to kill people.”
Lockdown was the most disastrous part of a policy taken by many countries and American states supposed to ‘slow down’ the spread of the virus, yet we must accept it had popular support. Even though, the idea was to discourage people from leaving their homes, for walks or cinemas or cafés, and to require them to stay in claustrophobic proximity with each other in their homes for weeks on end.
In France, President Macron made long, emotional appeals to his ‘compatriots’ to join in a national struggle against ‘an invisible enemy’, before listing respectfully those who had fallen already.
All public spaces were closed and citizens (like myself) were forbidden to leave their homes for weeks on end, except to buy essential foodstuffs in approved shops. And to do this, they had to clutch an official document downloaded from the government website, setting out their reasons for leaving their house.
The interior minister, Christophe Castaner, ordered 100,000 military police to spread around the country to enforce the lockdown. Of course, such people are immune from the virus – and can’t spread it either. (Such a thought was no more irrational than the rest of the government’s plans.)
Writing in The Guardian [12], Tobias Jones, that paper’s Italy correspondent, described his family’s life under lockdown. He recalled how some of his friends had started to neurotically wash their hands every half-hour and put on surgical gloves before doing everyday actions like opening doors. “It’s hard not to begin to doubt your own sanity and wonder whether it’s rational to be following all these restrictions and rituals”. Quite.
Public bodies too were neurotically washing things. Lorries sprayed streets with disinfectant, workers in rubber gloves and face masks stood by escalators wiping down the handrails, and of course everyone doing it wore facemasks. Yes, the ones that protect other people from your germs.
In the US, President’s Trump’s decision to close America’s borders made no scientific sense (and nor does health screening at borders as it cannot pick out people who may carry viruses but not yet have symptoms), even if in partisan political terms is seemed to reinforce his campaign themes of a strong fortress America – the one with a wall along the Mexico border. Rechristening the virus “the Chinese virus” seemed to underline this xenophobic message.
Tying together all the plans however was the central conviction that we had to ‘Flatten the Curve’. That is, to spread out the load of virus cases and relieve pressure on health services. This had rapidly become the One Thing Everyone Agrees. Yet even that simple relationship – lots of cases, overloading health services, so better to spread them out – is not entirely straightforward.
Because spreading infections out over a longer period of time can just as easily mean that instead of being overwhelmed during a short, acute phase, health services remain overwhelmed for a more protracted period. When health services are overwhelmed, people die. Because destroying livelihoods, disrupting social life and locking people in their homes for months kills people too.
In the absence of data, prepare-for-the-worst reasoning leads to extreme measures of social distancing and lockdowns. Unfortunately, we do not know if these measures work [13].
School closures, for example, may reduce transmission rates. But they may also backfire if children socialize anyhow, if school closure leads children to spend more time with susceptible elderly family members, if children at home disrupt their parents ability to work, and more. School closures may also diminish the chances of developing herd immunity in an age group that is spared serious disease.
So perhaps it is worth taking a moment to look at the background of one of the experts whose call for a swift clampdown on all social contact led to dramatic shifts in policy in both the UK and the US.
Professor Neil Ferguson, as I say, hails from Imperial College London – a university with a consolidated income of £1,033.0 million in 2017/18 including profitable links to the pharmaceutical industry.
Just days after the paper was published, Ferguson’s department of biomathematics announced it was sharing in £20 million of emergency coronavirus research investment courtesy of the UK government. Not bad for one paper! But the most revealing thing about Neil Ferguson and his department is that they had exactly the same concerns and exactly the same policy advice during the so-called ‘Swine Flu’ crisis back in 2009.
Flashback to June 11 that year, and the World Health Organization was declaring a ‘six-level alert’ – its grimmest ever – for a new pandemic sweeping the world.
This was the so-called Swine Flu or H1N1 virus, and despite having in previous years been found to have been wrong about the dangers of several other viruses, the WHO once again, sounded the deathly warning that ‘this early pandemic and flu is somewhat similar to the 1918-1919 pandemic swine flu that killed millions’.
Exactly what this strain would do in the Fall and Winter of 2009 and into 2010 was unclear, the WHO said, but ‘everyone needs to be prepared.’
Naturally, governments everywhere respected the advice of the World Health Organization, a U.N. agency which after all does so much good work combating disease and guiding research related to public health. And so, after the Swine Flu warning, where necessary, they promised, schools and offices would be closed.
Facemasks were bought in the millions, and vaccines were stockpiled. And also as part of their response, as I reported in my earlier book Paradigm Shift: How Expert Opinions Keep Changing on Life, the Universe, and Everything (2015), a fount of ‘advice’ was offered to the public.
For example, people were told, when back at home in the evening, to disinfect dishes, cups and utensils by thoroughly soaking in detergent and washing and rinsing thoroughly everything by hand or in the dishwasher. Everyone was to wash their hands frequently. And if, despite staying away from work ordering the shopping by phone and disinfecting the dishes, they still fell victim – there was advice on ‘the symptoms’. Fever, chills, coughing, fatigue, congestion, muscle and bone ache, and vomiting and intestinal upset. And then death.
No wonder governments spent so much to combat the threat. No wonder, more specifically, that governments swiftly came up with large amounts of money to buy huge amounts of vaccine from pharmaceutical companies.
Yet, at the end of the day, Swine Flu proved to be a paper tiger, just as the skeptical doctors had indicated. A year on, annoyingly, for the governments and their advisors, almost no people could be found to be said to have died from ‘H5NI’, even though ordinary ‘flu regularly kills several tens of thousands of people each winter. However, for a while, each of these viruses was the public health concern, we could say the fashion.
Quite possibly more people, suffering from other complaints, died from the ‘emergency precautions’ surrounding the virus, such as being refused entry to doctors surgeries or from being injected with the vaccine. But these could hardly be added to the statistics. And all over the (rich) world, millions of germ masks and vaccines began to deteriorate in storage, unused and unusable.
Back then, an erroneous piece of expert advice cost an unknown number of lives and enormous sums of money.
Not long after, two independent reports, one by the Council of Europe and another that appeared as a paper for the British Medical Journal (3 June 2010) put a belated spotlight on the fact that three of the crucial experts arguing for expensive programs of vaccine preparation by companies like Roche (the makers of Tamiflu) and GlaxoSmithKiline (the makers of Relenza) – were also paid consultants for the companies.
Now I don’t myself believe that individual researchers are knowingly skewing research reports in order to make money, either for themselves or their institutions. But the structural pressures are there and they can create the same effect. Research is a business and so its conclusions are skewed towards the ‘needs’ of the paymasters.
And you may well ask, how big a business is an epidemic? The answer is that they can be a very big deal indeed. In the US alone, Congress had appropriated $7.65 billion in June to fight the 2009 pandemic[14].
In the UK, in order to deal with the Swine Flu threat, the impressively titled and ennobled Chief Medical Officer, Sir Liam Donaldson, said that a £1 billion ($1.5 billion) emergency program of vaccination was needed. If it sounds a lot for a small country, remember, without it – up to 65 000 people would die!
The most ‘optimistic assessment’ was for 19 000 deaths. His fears were confirmed by virologists such as one Dr. John Oxford, who added that without immediate action he had calculated that soon half the population could be infected. Imagine, tens of millions of people dying – and only the government able to save them.
But the funds made available for the coronavirus were on a totally different scale. Even with the number of cases globally still relatively tiny, in March 17, 2020, the World Bank had set aside $14 billion to help its members to respond to the threat [15].
What sort of things was the money to be spent on? One component was to pay for everyone in the population to be tested for the virus. Vaccines make for profits, but testing is a great earner too. Often in this case tests were to be followed by the isolation of anyone who tested positive. Even though, as Galli, Prof. at Milan, warned, in a rare note of rationality, carrying out mass tests on the asymptomatic population could be useless:
The contagions are constantly evolving, a man who tests negative today could contract the disease tomorrow.”
Governments wouldn’t wish to implement pointless and even dangerous polices though, would they? Alas, the herd memory is short and nor are herds known for their willingness pause and reflect.
Otherwise they might have learned lessons from 1976, when President Gerald Ford’s administration reacted at speed to the swine flu outbreak, ignoring the World Health Organization’s words of caution and vowing to vaccinate “every man, woman and child in the United States.” After 45 million people were vaccinated, the flu turned out to be mild.
Worse, researchers discovered that some of the vaccinated — roughly 450 in all — had developed Guillain-Barré syndrome, a rare disorder in which the body’s immune system attacks the nerves, leading to paralysis. At least 30 people died.
Or from 2017, when a rushed campaign — endorsed by the WHO — to vaccinate nearly 1 million children for mosquito-borne dengue in the Philippines was halted for safety reasons. The Philippine government indicted 14 state officials in connection with the deaths of 10 vaccinated children, saying the program was launched “in haste”.
But back to the earlier Swine Flu outbreak in the UK, the one where the Chief Medical Officer swept aside skeptical voices, and instead advised the British government to order without further delay 32 million face masks to go with that £1 billion-plus worth of vaccines.
In France and other European countries, a similar story had played out – another billion-dollar supply of vaccines stockpiled here, another mountain of unused face masks there.
With hindsight it seems just silly – and expensive.
Yet it’s worth recalling thought that for a few months the Swine Flu pandemic was also genuinely terrifying everyone. Like the coronavirus, it had appeared around March and rapidly spread throughout many places on the planet, (invitation for luridly colored world maps on websites) all doubtless helped by sniffling travelers on airplanes.
The Center for Disease Control in the US started a website page to keep track of the death toll for 50 U.S. states and territories: by June 2009 the HTML counter registered 6,506 cases and 436 deaths. The next month, a special counter on the World Health Organization website registered total cases already at 177,457 with a toll of 1,462 deaths.
Admittedly, the figures were not yet exceptional, but the question everyone was asking was how many more might die soon? Basing their view on U.S. statistics, and the lack of a jab for swine flu experts thought there would be ‘about 300 million’ at risk initially: ‘typically, anyone who has not had the vaccine’.
For a few weeks back then too, it had seemed to a terrified public that the only real way to avoid dying was to ‘Get vaccinated as soon as possible’. Advice, in other words coming from the drugs industry funded labs that certainly suited the industry. Unfortunately, the vaccines would be available only in … early October. Just as in the spring of 2020, there were endlessly repeated helpful hygiene tips, such as to:
Avoid putting fingers and hands to the mouth or eyes since these are portals of entry for microbes.
Stay away from large crowds, and all infected people.
Remember to wear a face mask. Certainly if going out of the house.
Wash hands regularly, before eating or drinking and after visiting the restroom.
With Swine Flu, much of the advice related to safety at school. But with the coronavirus, even though school-age children were recognised as very low risk, schools were immediately shut down.
We should be suspicious of experts recycling old advice. After all, they may be guilty of two more cognitive biases: the phenomenon known as ‘one model thinking’ whereupon only evidence that fits the model is visible. There is either a duck, or a rabbit [16] but not both, to use the example that Wittgenstein made famous, but originated in 1892 issue of Fliegende Blätter, a German humour magazine.
And there is Confirmation Bias, which is the idea that people seek out information and data that confirms their pre-existing ideas while ignoring contrary information however potentially significant for the decision. The almost non-existent political and media examination of the range of views and strategies for the coronavirus shows that this is one of the most dangerous biases of them all.
Martin Cohen (Twitter @docmartincohen) is a writer, lecturer and researcher who specialises in social science whose books have been translated into twenty different languages. His doctoral research involved looking at social and psychological myths constructed around the power of computers and his books, including, Paradigm Shift: How Expert Opinions Keep Changing on Life, the Universe, and Everything (2015) have explored key issues in philosophy of science including food myths and previous pandemic scares as well as the groupthink that enabled them.