The epidemic model that panicked the world was junk
A software engineer has done a careful fact-based analysis of the code that runs the computer model of now disgraced and fired Neil Ferguson of Imperial College in London — the computer model that had predicted millions would die in mere weeks from COVID-19 and thus triggered the worldwide panic over it — and found that it is buggy, unreliable, produces different results with the same data, and often does so for completely irrelevant factors (such as simply running it on different computers).
Hat tip Rand Simberg at Transterrestrial Musings.
The conclusion from this software engineer:
All papers based on this code should be retracted immediately. Imperial’s modelling efforts should be reset with a new team that isn’t under Professor Ferguson, and which has a commitment to replicable results with published code from day one.
On a personal level, I’d go further and suggest that all academic epidemiology be defunded. This sort of work is best done by the insurance sector. Insurers employ modellers and data scientists, but also employ managers whose job is to decide whether a model is accurate enough for real world usage and professional software engineers to ensure model software is properly tested, understandable and so on. Academic efforts don’t have these people, and the results speak for themselves.
The second paragraph applies equally to all computer modeling in the climate field, which has been repeatedly found to have similar problems.
Science should be based on data, from the field, not models predicting that data. Models have a minor use as a guide, but it is beyond dangerous to depend on them in any manner at all. Had our politicians relied on the available data when COVID-19 first started to spread, instead of these fake models, they would not have panicked, and would have instead done what they should have, focused on protecting the elderly and the sick, the only part of the population under serious threat.
Similarly, had the public and the press ignored these bad models and focused on that same data, they too would not have been frozen in fear, and would have demanded a more rational approach to the epidemic.
I know I have been repeating myself on this subject, but it must be driven home. The modelers are unreliable. The modelers are often driven by political agendas, not the facts. The modelers must not be relied upon for any long term policy.
Repeat this mantra to yourself, over and over again. It should sound a warning in your brain every time you read another article predicting doomsday from something, from global warming, from sea level rise, from the ozone hole, from some disease, from any crises these frauds want to latch onto.
Readers!
Please consider supporting my work here at Behind the Black. Your support allows me the freedom and ability to analyze objectively the ongoing renaissance in space, as well as the cultural changes -- for good or ill -- that are happening across America. Fourteen years ago I wrote that SLS and Orion were a bad ideas, a waste of money, would be years behind schedule, and better replaced by commercial private enterprise. Only now does it appear that Washington might finally recognize this reality.
In 2020 when the world panicked over COVID I wrote that the panic was unnecessary, that the virus was apparently simply a variation of the flu, that masks were not simply pointless but if worn incorrectly were a health threat, that the lockdowns were a disaster and did nothing to stop the spread of COVID. Only in the past year have some of our so-called experts in the health field have begun to recognize these facts.
Your help allows me to do this kind of intelligent analysis. I take no advertising or sponsors, so my reporting isn't influenced by donations by established space or drug companies. Instead, I rely entirely on donations and subscriptions from my readers, which gives me the freedom to write what I think, unencumbered by outside influences.
You can support me either by giving a one-time contribution or a regular subscription. There are four ways of doing so:
1. Zelle: This is the only internet method that charges no fees. All you have to do is use the Zelle link at your internet bank and give my name and email address (zimmerman at nasw dot org). What you donate is what I get.
2. Patreon: Go to my website there and pick one of five monthly subscription amounts, or by making a one-time donation.
3. A Paypal Donation or subscription:
4. Donate by check, payable to Robert Zimmerman and mailed to
Behind The Black
c/o Robert Zimmerman
P.O.Box 1262
Cortaro, AZ 85652
You can also support me by buying one of my books, as noted in the boxes interspersed throughout the webpage or shown in the menu above.
A software engineer has done a careful fact-based analysis of the code that runs the computer model of now disgraced and fired Neil Ferguson of Imperial College in London — the computer model that had predicted millions would die in mere weeks from COVID-19 and thus triggered the worldwide panic over it — and found that it is buggy, unreliable, produces different results with the same data, and often does so for completely irrelevant factors (such as simply running it on different computers).
Hat tip Rand Simberg at Transterrestrial Musings.
The conclusion from this software engineer:
All papers based on this code should be retracted immediately. Imperial’s modelling efforts should be reset with a new team that isn’t under Professor Ferguson, and which has a commitment to replicable results with published code from day one.
On a personal level, I’d go further and suggest that all academic epidemiology be defunded. This sort of work is best done by the insurance sector. Insurers employ modellers and data scientists, but also employ managers whose job is to decide whether a model is accurate enough for real world usage and professional software engineers to ensure model software is properly tested, understandable and so on. Academic efforts don’t have these people, and the results speak for themselves.
The second paragraph applies equally to all computer modeling in the climate field, which has been repeatedly found to have similar problems.
Science should be based on data, from the field, not models predicting that data. Models have a minor use as a guide, but it is beyond dangerous to depend on them in any manner at all. Had our politicians relied on the available data when COVID-19 first started to spread, instead of these fake models, they would not have panicked, and would have instead done what they should have, focused on protecting the elderly and the sick, the only part of the population under serious threat.
Similarly, had the public and the press ignored these bad models and focused on that same data, they too would not have been frozen in fear, and would have demanded a more rational approach to the epidemic.
I know I have been repeating myself on this subject, but it must be driven home. The modelers are unreliable. The modelers are often driven by political agendas, not the facts. The modelers must not be relied upon for any long term policy.
Repeat this mantra to yourself, over and over again. It should sound a warning in your brain every time you read another article predicting doomsday from something, from global warming, from sea level rise, from the ozone hole, from some disease, from any crises these frauds want to latch onto.
Readers!
Please consider supporting my work here at Behind the Black. Your support allows me the freedom and ability to analyze objectively the ongoing renaissance in space, as well as the cultural changes -- for good or ill -- that are happening across America. Fourteen years ago I wrote that SLS and Orion were a bad ideas, a waste of money, would be years behind schedule, and better replaced by commercial private enterprise. Only now does it appear that Washington might finally recognize this reality.
In 2020 when the world panicked over COVID I wrote that the panic was unnecessary, that the virus was apparently simply a variation of the flu, that masks were not simply pointless but if worn incorrectly were a health threat, that the lockdowns were a disaster and did nothing to stop the spread of COVID. Only in the past year have some of our so-called experts in the health field have begun to recognize these facts.
Your help allows me to do this kind of intelligent analysis. I take no advertising or sponsors, so my reporting isn't influenced by donations by established space or drug companies. Instead, I rely entirely on donations and subscriptions from my readers, which gives me the freedom to write what I think, unencumbered by outside influences.
You can support me either by giving a one-time contribution or a regular subscription. There are four ways of doing so:
1. Zelle: This is the only internet method that charges no fees. All you have to do is use the Zelle link at your internet bank and give my name and email address (zimmerman at nasw dot org). What you donate is what I get.
2. Patreon: Go to my website there and pick one of five monthly subscription amounts, or by making a one-time donation.
3. A Paypal Donation or subscription:
4. Donate by check, payable to Robert Zimmerman and mailed to
Behind The Black
c/o Robert Zimmerman
P.O.Box 1262
Cortaro, AZ 85652
You can also support me by buying one of my books, as noted in the boxes interspersed throughout the webpage or shown in the menu above.
The modelers are often driven by political agendas, not the facts.
Consider the possibility that the critics of the models and modelers are driven by political agendas – as the software engineer admits to – on a personal level.
“Had our politicians relied on the available data when COVID-19 first started to spread, instead of these fake models, they would not have panicked”
Yes, and no. The public panicked based on a poor understanding of the meaning of Pandemic to a large extent. The opponents of President Trump jumped on the chance to force him into mistakes, and knowing this, he had little choice but to overreact.
The similarities to the shortfalls of the climate models is scary. Seems pretty clear to me that the universities are scrambling for research dollars by any means possible.
I go back to the argument that scientists should not make policy. While policy makers should consider the information provided by scientists, it is policy makers who have a wider knowledge base and are better able for decision making by weighing ALL factors not readily available to scientists limited focus: And I say this as a scientist (retired)!
From the Article:
–“In 2001, Ferguson helped spark a panic over U.K. beef when he predicted that 136,000 people could die from “mad cow” disease in coming decades.”
–“In 2005, Ferguson predicted the bird flu pandemic could kill 200 million people.”
–“Elon Musk had it right when he took to Twitter to thrash Ferguson, saying “this guy has caused massive strife to the world with his absurdly fake ‘science.’”
Andrew_W,
A succinct precis of the modern leftist mindset – “You don’t agree with my politics. Therefore I don’t have to take anything you say about anything seriously.”
The criticisms of the Imperial College/Ferguson code base are completely apolitical. Only the closing policy recommendations are political. Reject those if you insist, but, unless you are prepared to go full tilt boogie into the post-modernist everything-is-socially-constructed fever swamps and insist that computer science and software engineering are both just tools of white, Christian, capitalist, sexist, racist, imperialist oppression – and maybe you are – you need to deal with the substance of the technical criticisms.
Also: Given the pervasive no-enemies-on-the-left postulate of progressivism, it is close to impossible to imagine anyone of a political persuasion similar to Dr. Ferguson’s standard-issue academic leftism being willing to criticize his work so long as it advances The Narrative. That being the case, it is almost axiomatic that substantive criticism will only come from people not sharing Dr. Ferguson’s politics. On the left, “truth” is whatever The Narrative requires it to be. People who don’t believe in intellectual honesty are hardly likely to call anyone to account, especially one of their own, for the commission of mortal sins against that – now former, for the most part – academic ideal.
Dick Eagleson, read this carefully:
When updated data in the Imperial team’s model1 indicated that the United Kingdom’s health service would soon be overwhelmed with severe cases of COVID-19, and might face more than 500,000 deaths if the government took no action, Prime Minister Boris Johnson almost immediately announced stringent new restrictions on people’s movements. The same model suggested that, with no action, the United States might face 2.2 million deaths; it was shared with the White House and new guidance on social distancing quickly followed.
Actions were taken which altered the trajectory of the spread of the disease, so Ferguson was not wrong when his models are considered in the correct context. The dishonest claim is to imply that he projected 500,000 or 2.2 million deaths even with the actions that have been taken. Given that obvious difference, projections based on no action led to actions being taken lowering death rates and slower spread of the virus. So yes, the criticisms, which ignore the obvious actual sequence of events, are dishonest and politically motivated.
https://www.nature.com/articles/d41586-020-01003-6
The level of honesty being demonstrated by the critics is on a par with a patient whom, after being told by a doctor that they need to take measures to protect their health or face an early grave, they take the measures advised, then, when their health remains good, calling the doctor a quack because they didn’t suffer the ill health the doctor forecast.
The patient would reasonable be considered deranged for that use of logic, but such logic makes perfect sense to people who need to rationalize to justify ideological positions.
Andrew_W “The level of honesty being demonstrated by the critics is on a par with a patient whom, after being told by a doctor that they need to take measures to protect their health or face an early grave, they take the measures advised, then, when their health remains good, calling the doctor a quack because they didn’t suffer the ill health the doctor forecast.”
A nice comforting thought, and one of the narratives being pushed. However, the actual data does not support this.
https://amgreatness.com/2020/05/04/the-failed-experiment-of-social-distancing/
However, the actual data does not support this.
Wrong, where policies like social distancing have been adopted to reduce the transmission the rates of transmission have been reduced within 2-3 weeks, and the more thorough the adherence the quicker the rate of decline. The reason the rate of decline in the US has been poor is because many Americans have been too preoccupied with fighting against those measures, unable to adhere due to financial or housing issues or just too indifferent.
https://www.worldometers.info/coronavirus/#countries
@Andrew_W
We’re not going to obey you, Andrew_W, anymore.
These quack scientists should be sued personally by their victims. And then be given the Flynn treatment after the FBI gets purged by President Trump.
Dick–
Great stuff.
Andrew_W:
Could it be that Ferguson was preoccupied with his extensive extracurricular activities, with someone else’s wife?
(In the American Democrat Party, that is considered a resume-enhancer.)
(I’m reminded of a Poem….
“On the first Feminian Sandstones we were promised the Fuller Life
(Which started by loving our neighbor and ended by loving his wife)
Till our women had no more children and the men lost reason and faith,
And the Gods of the Copybook Headings said: “The Wages of Sin is Death.” “)
Ref–“many Americans have been too preoccupied with fighting against those measures, unable to adhere due to financial or housing issues or just too indifferent.”
When did Americans start “fighting against those measures?”
When did Americans become “too indifferent?”
Obama cured the homeless problem, we didn’t hear about homeless people for 8 years.
But on a more serious note–
Q: Have you ever actually been to the United States?
“Per Andy W- The level of honesty being demonstrated by the critics is on a par with a patient whom, after being told by a doctor that they need to take measures to protect their health or face an early grave, they take the measures advised, then, when their health remains good, calling the doctor a quack because they didn’t suffer the ill health the doctor forecast.”
What if i had a small scratch on my finger and the doctor recommends amputating it; so i will not get infection and remain in good health; is the doctor a quack?
“Prof Chris Whitty: How to Control a Pandemic”
Gresham College Public Lecture
Oct 18, 2018
https://youtu.be/rn55z95L1h8
53:40
-The title is somewhat a misnomer, but he does provide suggestions therein. He does do a very good job of giving an historical perspective.
“70% of inmates test positive for coronavirus at Lompoc federal prison”
* https://www.latimes.com/california/story/2020-05-09/coronavirus-cases-lompoc-federal-prison-inmates
That’s about 800 of 1150 inmates testing positive. Data from captive populations like this or the Diamond Princess are invaluable to analysts in determining IFR (Infection Fatality Rate). As with the Diamond Princess passengers and crew, the population of a prison will not necessarily be representative of the population as a whole, but if anonymized health records are provided to researchers to determine age and comorbidity vs. outcome, strong inferences can be gathered.
I still think we need a lot of informed-consent volunteer testing, and that existing restrictions need to be loosened, but for now we need to rely on “accidental” experiments found in the wild. My biggest concern is that waiting on accidental exposure for phase III efficacy testing of vaccines will take much longer than a program which allowed for intentional inoculation/infection of volunteers.
What I don’t know is if phase III time is the limiting factor. I know that, with the aid of government grants, companies are proceeding with “at risk” production of untested vaccines. But does that production take long enough to scale up that even if they knew they had a safe and effective vaccine today, it still wouldn’t be widely available until next year?
British [deleted] Leftis Socialist Control Now Everyone get back to Work.
jose sauceda: I have deleted the obscenity from your comment. You are new here, so I haven’t suspended you. However, read the rules just above the list of last ten comments in the right column. No obscenities allowed. Do it again and I will suspend you for a week. Do it a third time and it is bye-bye forever.
You are welcome to comment. I expect however commenters to act like adults. If you can’t go somewhere else.
Robert wrote: “Science should be based on data, from the field, not models predicting that data. Models have a minor use as a guide, but it is beyond dangerous to depend on them in any manner at all.”
Many science models should not predict data but should explain the data. Only once they have managed to successfully predict, during testing, a lot of future data can predictive models be used for prediction of future data (e.g. weather, spacecraft trajectories, stock market values, crop yields, etc.). Sue Denim showed that Ferguson’s model was bogus all along.
More than just science should be based on the data from the field. Decisions are better when they are based upon existing data rather than models. Even by March there was a lot of existing data that demonstrated the actual behavior of the virus and disease, such as the elderly being more vulnerable, the young being almost completely safe, and those with existing morbidities being most vulnerable. Thus, rather than protecting those most vulnerable, schools were closed, and soon everyone, not just the vulnerable, were locked down, and the police patrolled the streets heavily to intimidate those reluctant to obey. Many people complained at the time that the reactions were wrong, but the complaints fell on ears that listened to the modelers, not the data from the field.
A risk, as with the climate models, is that those who relied upon the flu models became so married to the predictions that they modified the data, making the models look not quite so wrong. The data collected in the U.S. is so corrupted away from what the model sought, the number dying from Wuhan flu (not with the flu or suspected, or assumed, or assigned (for disaster relief revenue)), that it cannot be used to rectify the models that predicted doom and gloom.
Another risk was that the models initially did not consider simple measures that were already in effect, such as hand washing, which had become commonplace due to previous flus and illnesses. The earliest model did not consider hand washing or travel bans — or even the social distancing that was already in place at the time of lockdown — and predicted an unacceptable number of deaths, a number that was not going to happen by the time of the decision for economic shutdown. Decisions were made not based upon the situation at hand but based upon a non-existent situation. It was not until after the shutdown-lockdown decision was made and implemented that the truth emerged, that basic hand washing and travel bans removed 90% of the predicted deaths that the decision makers thought the shutdown-lockdown solution was supposed to prevent. The modelers waited until after the implementation to tell the decision makers that the models predicted not that 2 million lives would be saved, but that the loses were predicted to be reduced to 60,000, under conditions of shutdown, from the 100,000 under conditions of light social distancing. The modelers predicted forty thousand lives would be saved in America by a three-week shutdown, as announced by Fauci.
Another risk is that the intent of the models was not to predict other consequences, intended or not. Thus, the models did not predict economic losses (personal, business, or governmental); collateral deaths; societal changes or breakdowns, temporary or permanent; worldwide food supply-chain breakdowns and associated starvation; the inability to restart the economy in a timely manner due to fears that any further deaths would result in political, economic, or legal consequences; political and dictatorial overreach in all branches and levels of government; mission creep (moved goalposts) and the associated devastation; or civil disobedience. Recommendations and decisions were made in panic without proper consideration of the consequences. The problem was the panic, not the disease, and the panic has yet to be addressed — or modeled. The panicked reaction is turning out to be far more deadly and devastating than the disease.
Even in the absence of political agendas, models have limitations. As with climate models those limitations were not addressed (or understood?) by the modelers for the Wuhan flu. Science also has limitations, which is why many, most, or all decisions should not be based solely on the science, either.
Thid should be a lesson to those eager to drastically change policies based on predictions made by equally unreliable, politically driven models on climate change that have provided no correct predictions thus far.
Here is Mike Huckabee’s take.
https://www.youtube.com/watch?v=ry8zmPB3cgc
I’ll toss this in here—
“Are Left and Right Experiencing Two Different Pandemics?”
Tom Woods Show, episode 1648
May 8, 2020
https://youtu.be/VALE-ogLcqg
34:51
“Jeff Deist, chairman of the Mises Institute, joins me to try to get to the bottom of why the response to COVID-19 (and the lockdowns) seems for the most part to divide along ideological lines, an outcome I myself did not expect.”
Tom Woods