Vetting Our Elite Masters (3)

Ferguson-Staats

Dr. Neil Ferguson and Mrs. Antonia Staats.  Two elites at the pinnacle of power living in the depths of intellectual and moral impoverishment.

Dr. Neil Ferguson (2)

In a stunning, unexpected development, we find that Dr. Neil (Icarus) Ferguson has been unmasked as a pathetic hypocrite and intellectual poseur.  While it’s a difficult task to properly plumb the depths of this man’s depraved dishonesty, there are a few correspondents who are giving it a good try, such as Toby Young of the Spectator USA.

I originally had Neil Ferguson down as a kind of Henry Kissinger figure. The professor of mathematical biology at Imperial College London seemed to have bewitched successive prime ministers, blinding them with his brilliance. Whenever a health emergency broke out, whether it was mad cow disease or avian flu, there he was, PowerPoint in hand, telling the leaders of the United Kingdom what to do. And they invariably fell into line. In 2001, after the outbreak of foot and mouth, his team at Imperial advised Tony Blair’s government to adopt a strategy of pre-emptive culling, leading to the slaughter of more than six million animals. Gordon Brown consulted him about swine flu in 2009 and two months ago Boris Johnson was persuaded to put the country under lockdown after the 51-year-old boffin bamboozled him with one of his computer models.

But it turns out to be less a case of Dr Strangelove than Carry On Doctor. On Tuesday night, we discovered that the furrowed-browed scientist, who has been at the Prime Minister’s side throughout this crisis, is in fact Austin Powers in a lab coat. He’s been having an affair with a 38-year-old married woman who travels regularly across the capital from her home in south London to spend time with him. This revelation, which has to be the scoop of the year, was brought to us by the Telegraph and is the epitome of what newspapers call a ‘marmalade dropper’ — a story so astonishing it causes the typical reader to drop his toast mid-mouthful.

A good deal of the coverage has focused on Ferguson’s hypocrisy. After all, this is the man who has told 66 million Britons they must remain in their homes to protect the NHS and save lives. Under the draconian new rules imposed by the Coronavirus Act, we’re allowed to venture out only if we have a ‘reasonable excuse’ such as a medical emergency, daily exercise, essential food shopping or certain types of work. Hard to imagine an extra-marital affair falling under one of those headings. How can Professor Lockdown encourage the authorities to enforce these rules when he’s flagrantly breaking them himself?

And, John Daniel Davidson of The Federalist adds important detail to this appalling picture.

“On at least two occasions, Antonia Staats, 38, traveled across London from her home in the south of the capital to spend time with the government scientist, nicknamed Professor Lockdown,” reported the Telegraph.

Staats, we later learn, lives with her husband and two children in a £1.9 million home in south London. She’s a “left-wing campaigner” who is reportedly in an open marriage. According to the Telegraph, “She has told friends about her relationship with Prof Ferguson, but does not believe their actions to be hypocritical because she considers the households to be one.”

Ah yes, the old our-households-are-one-because-I’m-in-an-open-marriage argument. Never mind that a week before Ferguson and Staats’ first meeting, Britain’s Health Secretary had said even couples not living together must stay apart during the lockdown.

Wow, now that is indeed elite behavior!  But who is the Mrs. Antonia Staats?  The Power Line Blog answers this very question.

She is identified as a “senior campaigner at Avaaz.org,” much of whose work appears to be dedicated to climate change activism.

Finally, in an exception that proves the rule, the dear Dr. (Western Civilization Destructor) Ferguson has received a small measure of accountability for his hypocrisy and incompetence, as described in The Guardian.

Prof Neil Ferguson, the epidemiologist whose modelling helped shape Britain’s coronavirus lockdown strategy, has quit as a government adviser after flouting the rules by receiving visits from his lover at his home.

Ferguson runs the group of scientists at Imperial College London whose projections helped persuade ministers of the need to impose stringent physical distancing rules, or risk the NHS being overwhelmed.

In a statement on Tuesday, he said he was resigning his post on the government’s Scientific Advisory Group for Emergencies (Sage), over an “error of judgment”.

Although we can never know, it takes but a small effort to imagine these two elite do-gooders cackling together over their virtuous fraud by which Western Civilization has been shut down thus saving us from climate change!

Vetting Our Elite Masters (2)

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The man who launched the lockdown of Western Civilization, Dr. Neil Ferguson.

Dr. Neil Ferguson (1)

I have already discussed Dr. Neil Ferguson with regard to the Imperial College Model.  But his contribution to what is certainly a deep wounding of Western Civilization continues to be highlighted in many articles.  For example, here is a summary of the influence of his model on initial (and continuing) COVID-19 public policy (emphasis added).

In the current crisis the most alarming model, nay probably the most influential in the implementation of the draconian quarantines worldwide, projected a maximum of 2.2 million American deaths and 550,000 United Kingdom deaths unless there were severe restrictions for 18 months or until a vaccine was developed. The primary author: Neil Ferguson. …

Then a funny thing happened. A mere nine days after announcing his model, Ferguson said a better number for the U.K. would be only 20,000. The equivalent would be fewer than 80,000 American deaths.

The mind simply boggles at this sequence of events.  Dr. Ferguson’s predictions created a massive panic in both government officials and the general population.  The response in the West was a near uniform (Sweden excepted, and universally denounced) imposition of draconian, open ended lockdowns of social and economic commerce.

And yet, in the space of nine days this man and his model reduced the number of predicted deaths by a more than a factor of 27!  Note that nine days is far too short a time for any government policy to have taken effect fully, let alone turned the tide in number of deaths.  No, this was the admission of a massive, incredible error.  But the damage had already been done.  Here’s how one correspondent from the United Kingdom describes the situation (which is very similar to our own here in many States of the United States).

Well, this is where it really starts to matter. We are about a fortnight from the moment when huge numbers of jobs will be in danger of permanent extinction.

The only choice will be to spend so much non-existent money that even the wild gamblers who have taken over HM Treasury are scared to do it.

But here’s the problem for Mr Bumble [Boris Johnson, Prime Minister]. He did not just panic himself. He spread fear far and wide. More than half the population have been literally scared silly.

You meet them on pathways and pavements, flinching with real alarm at the approach of another human being as if bubonic plague were abroad. They genuinely fear to go back to normal life.

The above last two sentences accurately describe what is certainly a plurality (and maybe a majority) of people in the United States.  Thus, even if all our States were completely opened tomorrow our social, religious and economic lives would continue to suffer great self-inflicted harm.

What boggles the mind to an even higher level is the fact that Dr. Ferguson and his models have built a track record of massive failure over decades.  This article provides a good summary (emphasis added).

When it comes to wildly inaccurate predictions Prof. Ferguson’s work at Imperial College has a long and distinguished history. In 2002, he said that 50,000 people in the UK would die from “mad cow disease”, to date less than 200 have passed away; he predicted 200 million global deaths from the H5N1 bird flu. Currently it is a suspected factor in the deaths of 455 people world wide; in 2009 he told the UK Government that 65,000 could die from swine flu in the UK and worked with the World Health Organisation to predict millions of deaths from the H1N1 global flu pandemic.

Suspected resultant UK deaths from swine flu were estimated to be 457 and the global total showed 18,500 laboratory-confirmed deaths from the H1N1 pandemic. …

While Prof. Ferguson and his Imperial College colleagues have been consistently wrong they have also been unquestioningly believed by governments and intergovernmental bodies on every occasion. Seemingly without reservation.

Despite the clear evidence to the contrary, policy makers from all political parties have shown tremendous loyalty to Imperial College’s silly data models. In doing so, they have not only ignored the researchers woeful history of failed predictions but have also denied the scientific evidence which usually contradicts them.

In no way can basing policy decisions on Imperial Colleges computer models be considered science led decision making. Quite the opposite.

The last four sentences constitute a definitive description of our incompetent elite masters.  Dr. Ferguson and his models do not have credibility because of their track record of predictive accuracy, because the exact opposite has occurred.  No, he has credibility because of his academic credentials and position.  His models have credibility because they were developed in an academic institution with high prestige.

The reality is likely that government officials give this pathetic failure of a modeler credibility because  he will always give them reasons to expand their power.  The fear of mass death will always affect a significant portion of the public, who will then willingly cede another portion of their liberty in exchange for “safety” from the phantom, stupidly inaccurate predictions form the likes of Dr. Ferguson.

But it’s actually far worse than this, so stay tuned.

Decoding Progressivism (14)

COVID-19 Hysteria Edition

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Gov. Pritzker’s “plan” to reopen Illinois.  Not dissimilar to “Our Vision for Health, Safety, Virtue, and Eternal Peace

Governor Pritzker of Illinois is only one of a cadre of Progressive governors whose apparently irrational and destructive policies are driving their states into wreck and ruin.  We on the receiving end of these policies can be forgiven for wondering just what could motivate these leaders to behave in this manner.  Particularly when their public explanations for what are without doubt their selected policy choices make no sense.

Gov-Pritzker-COVID-19-Dog

We Are in a State of Hysteria Over COVID-19 (1)

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I was recently informed about a Washington Post article that raised the specter of massive death by COVID-19 to the young in our population.  Of course, the tone isn’t “you’re all going to die” but rather “be afraid, be very afraid.”  Here’s the article’s title and subheading:

Young and middle-aged people, barely sick with covid-19, are dying of strokes
Doctors sound alarm about patients in their 30s and 40s left debilitated or dead. Some didn’t even know they were infected.

People’s imaginations can be relied on to fill in the gap, particularly those who have been fed a continuous stream of psychosis inducing stories for their entire lives.

The incidents discussed in the Washington Post are certainly concerning, but my thought is that they should be subjected to the same scientific rigor as are other aspects of COVID-19 treatments and physical effects. Otherwise we can be driven to emotional responses based on incomplete, uncertain data.

There’s also available data on the other side of the issue. Here’s a very relevant chart from the Massachusetts Department of Public Health COVID-19 Dashboard – Saturday, April 25, 2020. Yes, this chart is very concerning for people above 70, particularly those with other underlying health issues. But for people below 50 the likelihood of death due to COVID-19 is very small.

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Of course there is always the possibility that the virus causes lingering or even permanent damage to some of its victims. Therefore, we must continue our intense research efforts to understand and treat this disease.

Our young people are disproportionally suffering the consequences of this enforced shutdown. We also know that loss of livelihood, business, relationships and dreams can lead directly and indirectly to unnecessary death. By treating death by COVID-19 as the only meaningful issue we are ignoring all of the other less visible but just as real mental and physical consequences of our policies.

What I would like to see is our political leaders start to discuss a broader scope of issues relating to their policies. There are many legitimate perspectives that should be included in our deliberations.  But were this to happen the discussion would morph from one centered on the irrational terror of sudden death from COVID-19 to one that assesses the painful tradeoffs between the pros and cons of policy options.  While the former advances the power of our political and media class the latter encourages a rational public debate.

Are We in a State of Hysteria Over COVID-19? (6)

Reasons to Wonder

Model Based Projections

The IHME Model (Continued)

In previous posts I have cast doubt on the various COVID-19 models based on their demonstrated unreliability over time.  That is, they all have started with terrifyingly high projections of deaths (even with social distancing) but then were successively and significantly (massively in the Imperial College Model case) reduced, sometimes over a span of just days.

While the above information is devastating to these models’ credibility, there is another, more technical, means by which to judge them.  All responsible modelers acknowledge that there is uncertainty in their predictions.  They admit that, by use of uncertain / incomplete data and artificial mathematical manipulations, they cannot claim to predict the future with total accuracy.  The metric often used to convey this uncertainty is called the Confidence Interval.

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The 95% Confidence Interval for a population of results with a Gaussian probability distribution.

A confidence interval, in statistics, refers to the probability that a population parameter will fall between two set values for a certain proportion of times. Confidence intervals measure the degree of uncertainty or certainty in a sampling method. A confidence interval can take any number of probabilities, with the most common being a 95% or 99% confidence level.

In more simplistic terms, the modelers use statistical theory to determine the range of output values for which they are, say, 95% confident that the actual, real world data will be within.  Thus, if the model is useful and the mathematical calculations correct we expect that for 95% of real world cases the values will fall within the model’s 95% Confidence Interval.  However, if it turns out that far less than 95% of actual data falls within this Confidence Interval then the model has failed by its own terms.  That is, the model has failed to adhere to the level of uncertainty that the modelers themselves have specified.

Based on these concepts a group of researchers decided to test the predictions of the IHME COVID-19 model using the Confidence Interval defined by the IHME modelers themselves.  The chose the easiest possible future prediction test; that being:

Given all the deaths by State data up to a given date, prediction of the next day’s number of deaths per State.

In other words, all the IHME model had to do was predict the next day’s death count per state within the Confidence Interval (i.e., the actual number of deaths is between the least and most death values for which the modelers said they could predict with 95% confidence).

The paper’s authors picked four dates: March 30 & 31 and April 1 & 2.  Since for each date the number of predicted deaths were made for each of the 50 States in the U.S., this resulted in a total of 200 model predictions.  If the model performed with the confidence predicted by the modelers that would mean that only 10 of the 200 predictions would fall outside of the 95% Confidence Intervals.  The following chart shows what actually occurred.

IHME-CI-Model-Results

Confidence Interval IHME Model results from “Learning as We Go: An Examination of the Statistical Accuracy of COVID19 Daily Death Count Predictions” for next day number of deaths prediction by State.  The total number of data points utilized is 200 (i.e., 50 States times 4 days).

Note that the number of next day predictions that fall outside of the IHME modeler’s defined 95% Confidence Interval is 130 as opposed to the expected 10.  The unavoidable conclusion is that the IHME modelers are not able to accurately predict the reliability of their model’s output data even for the easiest test case (i.e., predict the next day’s number of deaths).  The paper authors summarize their findings as follows.

Our results suggest that the IHME model substantially underestimates the uncertainty associated with COVID19 death count predictions. We would expect to see approximately 5% of the observed number of deaths to fall outside the 95% prediction intervals. In reality, we found that the observed percentage of death counts that lie outside the 95% PI to be in the range 49% – 73%, which is more than an order of magnitude above the expected percentage.

But it’s far worse than this.  For a model that is incapable of predicting number of deaths one day in advance has been used by policy makers to predict weeks, even months into the future.  This result exposes the entire COVID-19 public safety initiative as having been based on modeling that is utterly discredited even if evaluated on the terms set by the modelers themselves.  This is the basis upon which our economy has been devastated, with potentially millions of citizens forced into poverty and lost hope, with all of the associated lives lost due to increased suicide, drug abuse, depression, domestic and community violence, undiagnosed disease, among other causes.  This is a massive scientific scandal with direct devastating consequences for hundreds of millions and indirect for billions of human beings worldwide.

Failure of the Conservative Imagination (1)

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As any reader of this blog knows I’m appalled by and critical of the Progressive movement in all of its forms.  However, as a believing Reformed Christian I also am convinced that neither I nor those who theologically / politically agree with me occupy a position of arbitrary moral superiority.  If we do in some respects live by higher moral standards then it is only by the sanctifying power of God that is completely unearned by any inherent merit.  Therefore, it is only right and proper that we should inquire into the guilt that we bear for the wreckage of our civilization.

Guilt can take many forms and occurs at many levels.  The fact that we admit guilt for a tragic situation need not diminish that of others.  But we who consider ourselves to be “conservatives,” “traditionalists” and the “orthodox” have certainly contributed to the civilizational wreckage which is becoming obvious to all but the purposefully blind.

There are many dimensions that could be addressed, from our acceptance of prosperity built on ever accumulating debt to creeping acceptance of ideas that have undermined our morals.  But the dimension that has recently bubbled to the surface is the lack of imagination that has enabled us to accept a false facade of consensus behind which lies true intentions.

To become specific, we conservatives have for far too long insisted on pretending that our disagreements with the Progressive movement centered on the means to achieve commonly shared ends (e.g., the reduction of poverty).  We also assumed that there was a shared devotion to the Constitutional framework undergirding our nation’s political and civil life.  Of course there are many people who consider themselves to be Progressive for whom these assumptions remain valid.  However, this fact doesn’t mean that the elite power brokers of the Progressive movement share this mindset.  It can simply mean that their deception encompasses a larger cohort than non-Progressives.

But with the COVID-19 crisis the Progressive elite’s masks have been completely (by themselves!) removed.  Take for example:Screen Shot 2020-04-22 at 5.53.41 AM

I could go on, but the point is made.  That being the Progressive Left is using this crisis to seize the power over U.S. citizens that had previously been out of reach.  Their behavior seems irrational because it is destroying the very economy that funds all of their beloved government programs.  But that may be a small price to pay for the destruction of the independent people and businesses who stand in the way of full Progressive political victory.

If we want to save our Constitutional Republic then we must abandon the fantasy that the elite Progressive Left shares any of our goals or values.  Yes, they remain our fellow citizens.  But they are “fellows” who are seeking the utter destruction of our nation so that it can be “rebuilt” as Socialist and totalitarian.  We should try to convince Progressives of good intentions that this would be a disaster for their humane goals.  We must defeat the Progressive Left politically so that this current power grab is only a temporary blip on this nation’s life of liberty and human hope.

Are We in a State of Hysteria Over COVID-19? (5)

COVID-19-GIGO-Model

Reasons to Wonder

Model Based Projections

The IHME Model

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Sean Davis exposes the “successful social distancing” lie.

The discrediting of the Imperial and associated Act Now models (plus perhaps U.S. national pride) led to the selection of a new model as the authority on COVID-19 infections and deaths.  That model is the University of Washington’s Institute for Health Metrics and Evaluation (IHME) model.  However, given the experience of the Imperial model numerous journalists decided to take a more critical look at these models in general, and the IHME model in particular.

For example Sean Davis has carefully watched as the IHME modelers repeatedly significantly reduce their predicted deaths over just a few days.  In addition to debunking the dishonest excuse that these reductions were due to the success of “social distancing” he has commented on the implications for current policy (emphasis added).

We can not remain locked down another full month because the damage to the economy will be unbelievably deep and harmful to the average Americans. What we need to do now is not be afraid to reevaluate why these models were so inflated and whether that means we can start to transition back to normal life sooner rather than later.

Yes, there are risks, but there are also profound risks to essentially destroying the economy. That includes deaths that could be prevented by finding a middle ground that still promotes social distancing yet allows people to go back to work in most cases. Our leaders need to start coming up with some hard data about what aspects of our mitigation are actually working and what’s unnecessary. Right now, it feels as if we are flying blind, with very little rationale for some of the things we are doing. For example, would social distancing and masks be just as effective as a total lock down? These are the kinds of questions that must be answered soon.

Another journalist who has dug deep into the COVID-19 modeling scandal is Alex Berenson (emphasis added).

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Alex Berenson demolishes the Progressive elite claim that assumes time travel for its credibility.

… what Berenson is claiming is simple: the models guiding the response were wrong and that it is becoming clearer by the day.  …

“I’ve been paying incredibly close attention to the modeling and trying to figure out whether it lines up with what we’re seeing in reality — and the answer is it hasn’t lined up at all,” he said.

Recently he’s been focusing on discrepancies within the University of Washington’s Institute for Health Metrics and Evaluation (IHME) model. That model has come under renewed scrutiny as it has revised its metrics multiple times. It once predicted more than 90,000 deaths by August but recently issued a new estimate that has the figure closer to 60,000. Government officials say it’s a model that’s moving with what the country is doing. …

But Berenson argues that those models have social distancing and other measures baked into them. As for further proof, he says that outside of places like New York there has not been a national health crisis that was predicted — nor are there signs that the level of lockdown in various states has made a difference.

“Aside from New York, nationally there’s been no health system crisis. In fact, to be truly correct there has been a health system crisis, but the crisis is that the hospitals are empty,” he said. “This is true in Florida where the lockdown was late, this is true in southern California where the lockdown was early, it’s true in Oklahoma where there is no statewide lockdown. There doesn’t seem to be any correlation between the lockdown and whether or not the epidemic has spread wide and fast.”

If we eventually realize that we destroyed major sections of our economy in over response to this virus then a major cause would be use of these deceptive, inaccurate models.  For it is these models that our political and cultural leaders have used to justify their power grabs.

How can we tell the difference between politicians who were misled as opposed to those who enthusiastically sought unconstitutional power?  We can differentiate by their response to exiting this current social and economic lockdown.  Those who support a return to normalcy can be forgiven and trusted.  Those who demand indefinite continuation must be opposed and rejected.

 

Are We in a State of Hysteria Over COVID-19? (4)

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COVID Act Now site map

Reasons to Wonder

Model Based Projections

COVID Act Now Model

This model is summarized as follows:

The Imperial College report was also the basis for the modeling used by the website COVID Act Now, which local and state officials in the U.S. then used to issue “shelter-in-place” mandates. COVID Act Now, which was founded by a handful of Democratic activists in Silicon Valley, is an online mapping tool that generates models predicting coronavirus hospitalizations, which have also already proved to be wildly inaccurate.

Note that this model is based on the discredited Imperial Collage Model.  These Democratic activists have publicly stated their bias (emphasis added).

So why is the organization or seemingly innocent online mapping tool using inaccurate algorithms to scaremonger leaders into tanking the economy? Politics, of course.

Founders of the site include Democratic Rep. Jonathan Kreiss-Tomkins and three Silicon Valley tech workers and Democratic activists …

Perhaps the goal of COVID Act Now was never to provide accurate information, but to scare citizens and government officials into to implementing rash and draconian measures. The creators even admit as much with the caveat that “this model is designed to drive fast action, not predict the future.”

They generated this model under the guise of protecting communities from overrun hospitals, a trend that is not on track to happen as they predicted. Not only is the data false, and looking more incorrect with each passing day, but the website is optimized for a disinformation campaign.

This example of highly partisan, politicized “scientific modeling” should cause great concern to all U.S. citizens.  What is exposed here is that naked use of, at best unreliable and at worst knowingly false, information to attain political power.  If we fail to recognize this situation and demand accountability then we are meekly submitting to these Pied Pipers of civilizational death and destruction.

Are We in a State of Hysteria Over COVID-19? (3)

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Dr. Neil Ferguson and model results (image from The Federalist)

Reasons to Wonder

Model Based Projections

So, even with all of the above described difficulties, how have the pandemic modelers performed in practice?  Although there ate many models from which to choose, I’ll limit this discussion to those that appear to have been most influential to the formation of public policy.

The Imperial College Model

This model has been by far the most influential in the setting of government policy to fight COVID-19.

British scientist Neil Ferguson ignited the world’s drastic response to the novel Wuhan coronavirus when he published the bombshell report predicting 2.2 million Americans and more than half a million Brits would be killed.

Based on these terrifying predictions the United States and the United Kingdom, among many other countries have virtually shut down their economies.  Tens of millions of people are losing their jobs.  Tens of thousands of businesses may never reopen due to loss of revenue and financial barriers to reopening.

So, how has this model’s accuracy done as the pandemic played out.  Let’s led the good doctor Ferguson, the model’s primary author explain (emphasis added).

But after tens of thousands of restaurants, bars, and businesses closed, Ferguson is now retracting his modeling, saying he feels “reasonably confident” our health care system can cope when the predicted peak of the epidemic arrives in a few weeks. Testifying before the U.K.’s parliamentary select committee on science and technology on Wednesday, Ferguson said he now predicts U.K. deaths from the disease will not exceed 20,000, and could be much lower.

That’s at least a 25-to-1 error in predicted deaths in the U.K.!  Some have attempted to lessen the blow of this modeling fiasco by claiming the change is due to aggressive government policy.  However this answer falls flat.

Former New York Times reporter Alex Borenson called Ferguson’s revised predictions a “remarkable turn,” …

“The UK only began its lockdown 2 days ago, and the theory is that lockdowns take 2 weeks or more to work,” Borenson said. “Not surprisingly, this testimony has received no attention in the US – I found it only in UK papers. Team Apocalypse is not interested.”

This is a stunning recantation of results that had driven governments across the world to choose highly aggressive policies. It is an example of gross professional incompetence at the very least.  Dr. Ferguson and his team should suffer a complete loss in credibility and professional standing.  However, as certified “elites” the likelihood of any real accountability for the massive failure is remote.

But it’s worse than that.  In point of fact there already is a history for the performance of these models in predicting real-world infection results…and it’s very poor.

But the Times goes on to ask an important question that I have not previously seen raised: do disease modelers have a track record that deserves to inspire the remarkable confidence that is being reposed in them?

… and it was from Imperial that Ferguson and Anderson dominated the government response to foot and mouth.

That response, involving the slaughter of more than 11 million sheep and cattle at a cost of more than £8bn was based entirely on modelling and remains hugely controversial — with many believing the modellers got it wrong. They were modelling a fast-moving epidemic with little accurate data. A subsequent government inquiry was damning of the general approach and its conclusions may be relevant to the current crisis. It said: “The FMD epidemic in UK in 2001 was the first situation in which models were developed in the ‘heat’ of an epidemic and used to guide control policy . . . analyses of the field data, suggest that the culling policy may not have been necessary to control the epidemic, as was suggested by the models produced within the first month of the epidemic. If so it must be concluded that the models supporting this decision were inherently invalid.”

The Imperial modellers’ next big public challenge came eight years later when swine flu swept the world — fortunately killing few Britons because older people tended to be immune and younger ones were strong enough to fight it off. Britain was, however, left with 34 million doses of unused and expensive vaccines. Again there was an inquiry — which concluded that ministers had once again treated modellers as “astrologers”, asking them to provide detailed forecasts when they had too little data.

“Modelling did not provide early answers,” it concluded. “The major difficulty with producing accurate models was the lack of a relatively accurate idea of the total number of cases . . . This is not to reject the use of models, but to understand their limitations: modellers are not ‘court astrologers’.”

The tragic fact is that we had no valid reason to base our social and public health policies on these modelers and their models.  The argument could be made that, at the very beginning of a novel form of pandemic, we had little choice but to use these crude, unreliable tools because nothing else was available (but I have my doubts).  However, the argument cannot be made that, after having exposed the stunning failure of these modelers and their models we are bound to continue following then into ruin.

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Are We in a State of Hysteria Over COVID-19? (2)

hysteria

Reasons to Wonder

It would be irresponsible at this point to claim that our response to the COVID-19 situation is hysterical.  However, I do believe that it is legitimate to ask the question and explore the possibility that it is.  It’s indisputable that many people in the media, government and general population have behaved in hysterical ways as the pandemic unfolded.  But that fact in and of itself doesn’t necessarily mean that the overall government and cultural response is hysterical.  There are, however, reasons to wonder.

Model Based Projections

General Considerations

Given my previous concerns about the use of computer models to “predict” global warming / climate change (see here and here), it raises a yellow flag when I see our political leaders basing their decisions on this resource.  The flag turns to red when I hear the very people who claim expertise to create and interpret models of COVID-19 infection and mortality complaining about the lack of sufficient and/or accurate data.

A computer model can be conceptualized to consist of two main components, those being:

  1. The set of data necessary for the model to function and
  2. The mathematical functions that transform the input data into the desired output data.

In the cases of COVID-19 the data may be the number of new infections and deaths over time for a defined geographical region.  The transformation functions are difficult because the modeler must make assumptions about key dimensions and then convert these assumptions into mathematical relationships that describe reality, for example:

  • How contagious the virus is
  • The modes of virus transmission
  • Sensitivity of transmission to population density, mobility, etc.
  • Sensitivity of transmission to government policy (e.g., quarantine, stay at nome orders, etc.)
  • Severity of illness as functions of age, underlying health conditions, medical intervention, etc.
  • Mortality as functions of age, underlying health conditions, medical intervention, etc.
  • Among others…

Thus, when considering the predictions of models for a new and little-understood virus decision makers and the general public should respond with caution.  That is, they should understand that these models are not predictors of reality, but rather abstract, artificial constructions based on insufficient data and human understanding.  This all isn’t intended to exclude the use of models, but rather to ensure that their predictions are treated with the caution that the unseen but real uncertainties associated with their construction demand.

For those of us whose professional careers depend on mathematical modeling, and who are held accountable for the results, one statement attributed to the statistician George Box, best summarizes our position, that being: “All models are wrong, but some are useful.”  Dr. Deborah Birx of the White House COVID-19 task force put this model wisdom into practice with this recent statement.

“Models are models. When people start talking about 20% of a population getting infected, it’s very scary, but we don’t have data that matches that based on our experience.”

The good doctor isn’t denigrating models,  but she is insisting that they cannot be substitutes for reality.

We would all like to accurately predict the future for something as terrifying as a new virus that has caused a global pandemic.  And unfortunately there are too many people in the scientific community who are willing to take advantage of that desire.  So, when credulous politicians, media and general public come into contact with modelers seeking influence and notoriety, the results can be devastating.  In the following posts this issue will be illuminated  and discussed at length.