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Professor Neil Ferguson, who led the COVID-19 modeling team at Imperial College in London, resigned May 5 from his government advisory role after breaking the very same British lockdown rules that he had a role in influencing.

Ferguson led the Imperial College team that designed the computer model that, among others, had been used to justify the recent stay-at-home orders in England as well as in the United States. We now know the model was so highly flawed it never should have been relied upon for policy decisions to begin with.

Epidemiology—the study of the incidence, prevalence, and impact of disease—frequently calls upon models to forecast potential outcomes of diseases. Not surprisingly, once COVID-19 became a pandemic, policy experts from all across the world began relying on such models.

The Imperial College researchers ran one such model they had used in prior research and forecast a number of potential outcomes, including that, by October, more than 500,000 people in Great Britain and 2 million people in the U.S. would die as a result of COVID-19.

The model also predicted the United States could incur up to 1 million deaths even with “enhanced social distancing” guidelines, including “shielding the elderly.” Imperial’s modeling results influenced British Prime Minister Boris Johnson to impose a nationwide lockdown and influenced the White House as well.

I asked Ferguson and his colleagues for their model on multiple occasions to see how they got their numbers, but they never replied to my emails.

According to Nature, they had been “working with Microsoft to tidy up the code and make it available.” I also asked the U.S. Centers for Disease Control and Prevention for the codes it used to develop its COVID-19 forecasts, but got no response.

So, my colleague Norbert Michel and I decided to take a publicly available COVID-19 epidemiological model and forecast the prevalence and mortality of the disease under a variety of plausible scenarios.

The results varied, depending on the assumptions we made about mortality rates within hospital intensive care units, asymptomatic rates, and the specification of the R0 (pronounced R-naught) value, which measures how easily the virus spreads.

We found mortality rate predictions can be quite variable depending on the age and comorbidities of those contracting the virus.

Under varying assumptions regarding a mortality rate in intensive care units between 5% and 30%, we found that predicted mortality because of the disease could range from near 78,000 deaths to as many as 810,000 deaths in the U.S. by Aug. 1.

Recent testing data indicates that the asymptomatic rate for COVID-19 is likely not trivial, and data from Iceland indicates this rate can be as high as 50%. Assuming an asymptomatic rate ranging from 15% to 55%, one can project deaths in the U.S. of between 118,000 and 394,000 by Aug. 1.

Lastly, we looked at the model’s assumption about the virus’ basic reproductive number, the aforementioned R0 value. Popularized in the 2011 movie “Contagion,” the R0 value quantifies the average number of people who will get the virus from someone who is an infected.

Under assumptions of the R0 value ranging from 1.5 to 3.5—plausible estimates based on medical research as discussed in our paper—the model predicted from 44,000 dead to 1.1 million dead by Aug. 1 in the U.S.

According to the Johns Hopkins University coronavirus tracker, we are currently over 83,000 deaths, which exceeds our lower-end estimates. But the point our research made is that these types of models produce many plausible scenarios, depending on reasonable assumptions.

As we learn more about the new coronavirus, it is imperative to continue to update the assumptions used in these models.

After we had published our work, news surfaced that Microsoft had actually made some headway in making the Imperial College team’s model available. But the codes it released are a highly modified version of what the Imperial team actually used.

And, it turns out, the model has serious flaws, which a former software engineer from Google discusses at length in his blog.

The Imperial College code provides different answers using the same inputs. In particular, the same assumptions can provide results that differ by 80,000 deaths over a span of 80 days. The software engineer has noted there are apparently myriad other problems as well—including undocumented codes and numerous bugs.

This isn’t the first time bad models have made their way into policy. As we discussed in our work, statistical models can be useful tools for guiding policy, but they are only as credible as the assumptions on which they are based.

It is fundamentally important for models used in policy to be made publicly available, have assumptions clearly stated, and have their robustness to changes to these assumptions tested. Models also need to be updated as time goes on in line with the best available evidence.

Bottom line: The Imperial College model didn’t meet any of these criteria. And sadly, its model was one of the inputs relied on as the basis for locking down two countries.

The codes we used at The Heritage Foundation are available here. Our assumptions are clearly stated in our paper here.
 

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All I can say is, you have way too much time on your hands. You need to go find something constructive to occupy your time.
 

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Oh, here we go again with the personal insults; you want to debate? Then attack the discourse, not the speaker........
 

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All I can say is, you have way too much time on your hands. You need to go find something constructive to occupy your time.
How anybody wants to spend their time here is their business as long as they obey the rules. No need to comment on it and especially not in this manner.
 

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Illinois was the second state to go on lockdown. There was no flattening of the curve.

Explain what was fixed please.

I'll ask if it was worth ruining so many people's lives.

In our ghettos liberals actively prevent the poor from getting an education so they can't support themselves. But wait! I can prevent those with jobs from making a living now!

Thanks government. Great job.
 

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Oh, here we go again with the personal insults; you want to debate? Then attack the discourse, not the speaker........
I didn't insult you. I merely stated a fact. No, I didn't read your cut and paste. I can access that stuff myself if I choose to. You need to state 'cut and paster', not speaker. You didn't say anything, least nothing I was interested in.

I'm done with you.
 

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Sweden ignored this defective "scientifically based model" (it's beyond defective, but actually fraudulent) and didn't suffer excessive illness and deaths, plus maintained their economy.

Boris Johnson in England was widely criticized when he discovered the fraudulent nature of this "scientist's" model, and decided to treat it as the trash it really was.

What follows is somewhat long winded, but it contains the detailed facts of what was wrong with the Ferguson / Imperial College Covid-19 Epidemic model that many politicians have based their politically correct and cowardly decisions on. Note that many politicians are now making phased re-opening decisions in direct contradiction of their CDC infection models, which have not really met the criteria for relaxing social engineering controls.

Here are some specifics from analysis of the fraudulent work:
- - - - -
Here is a very technical review of the Ferguson - Imperial College algorithm and coding from an anonymous software engineer. I’m guessing the writer is probably afraid of retribution from the far-left leadership at Google and Facebook. These highly ideological companies have a history of vengeful reactions to those who stray from the fold.

There is a follow up (mentioned in the beginning) to this original analysis which includes a statement from someone in the insurance industry where statistical modeling is at the heart of their decision making process:
  • “We always use 2 different internal models plus for major decisions an external, independent view normally from a broker. It’s unbelievable that a decision of this magnitude was based off a single model“
Clearly this statement is an indictment of W.H.O. and government groups like the US CDC for failing to employ basic statistical modeling cross-checking methodology prior to announcing their apocalyptic response measures. After the revelations of fraud from the Climategate email breaches of 2009 and 2011 the world should have been been very wary of university research groups and their distant relationship with the truth when far-left objectives are at stake. Naturally media leftist are always thrilled to help out by engineering the coverups that follow these scandals.


Code Review of Ferguson’s Model
6 May 2020. Updated 10 May 2020.
by Sue Denim (not the author’s real name)
[Please note: a follow-up analysis is now available here.]

Imperial finally released a derivative of Ferguson’s code. I figured I’d do a review of it and send you some of the things I noticed. I don’t know your background so apologies if some of this is pitched at the wrong level.
My background. I have been writing software for 30 years. I worked at Google between 2006 and 2014, where I was a senior software engineer working on Maps, Gmail and account security. I spent the last five years at a US/UK firm where I designed the company’s database product, amongst other jobs and projects. I was also an independent consultant for a couple of years. Obviously I’m giving only my own professional opinion and not speaking for my current employer.
The code. It isn’t the code Ferguson ran to produce his famous Report 9. What’s been released on GitHub is a heavily modified derivative of it, after having been upgraded for over a month by a team from Microsoft and others. This revised codebase is split into multiple files for legibility and written in C++, whereas the original program was “a single 15,000 line file that had been worked on for a decade” (this is considered extremely poor practice). A request for the original code was made 8 days ago but ignored, and it will probably take some kind of legal compulsion to make them release it. Clearly, Imperial are too embarrassed by the state of it ever to release it of their own free will, which is unacceptable given that it was paid for by the taxpayer and belongs to them.
The model. What it’s doing is best described as “SimCity without the graphics”. It attempts to simulate households, schools, offices, people and their movements, etc. I won’t go further into the underlying assumptions, since that’s well explored elsewhere.
Non-deterministic outputs. Due to bugs, the code can produce very different results given identical inputs. They routinely act as if this is unimportant.
This problem makes the code unusable for scientific purposes, given that a key part of the scientific method is the ability to replicate results. Without replication, the findings might not be real at all – as the field of psychology has been finding out to its cost. Even if their original code was released, it’s apparent that the same numbers as in Report 9 might not come out of it.
Non-deterministic outputs may take some explanation, as it’s not something anyone previously floated as a possibility.
The documentation says:
The model is stochastic. Multiple runs with different seeds should be undertaken to see average behaviour.
“Stochastic” is just a scientific-sounding word for “random”. That’s not a problem if the randomness is intentional pseudo-randomness, i.e. the randomness is derived from a starting “seed” which is iterated to produce the random numbers. Such randomness is often used in Monte Carlo techniques. It’s safe because the seed can be recorded and the same (pseudo-)random numbers produced from it in future. Any kid who’s played Minecraft is familiar with pseudo-randomness because Minecraft gives you the seeds it uses to generate the random worlds, so by sharing seeds you can share worlds.
Clearly, the documentation wants us to think that, given a starting seed, the model will always produce the same results.
Investigation reveals the truth: the code produces critically different results, even for identical starting seeds and parameters.
I’ll illustrate with a few bugs. In issue 116 a UK “red team” at Edinburgh University reports that they tried to use a mode that stores data tables in a more efficient format for faster loading, and discovered – to their surprise – that the resulting predictions varied by around 80,000 deaths after 80 days:

That mode doesn’t change anything about the world being simulated, so this was obviously a bug.
The Imperial team’s response is that it doesn’t matter: they are “aware of some small non-determinisms”, but “this has historically been considered acceptable because of the general stochastic nature of the model”. Note the phrasing here: Imperial know their code has such bugs, but act as if it’s some inherent randomness of the universe, rather than a result of amateur coding. Apparently, in epidemiology, a difference of 80,000 deaths is “a small non-determinism”.
Imperial advised Edinburgh that the problem goes away if you run the model in single-threaded mode, like they do. This means they suggest using only a single CPU core rather than the many cores that any video game would successfully use. For a simulation of a country, using only a single CPU core is obviously a dire problem – as far from supercomputing as you can get. Nonetheless, that’s how Imperial use the code: they know it breaks when they try to run it faster. It’s clear from reading the code that in 2014 Imperial tried to make the code use multiple CPUs to speed it up, but never made it work reliably. This sort of programming is known to be difficult and usually requires senior, experienced engineers to get good results. Results that randomly change from run to run are a common consequence of thread-safety bugs. More colloquially, these are known as “Heisenbugs“.
But Edinburgh came back and reported that – even in single-threaded mode – they still see the problem. So Imperial’s understanding of the issue is wrong. Finally, Imperial admit there’s a bug by referencing a code change they’ve made that fixes it. The explanation given is “It looks like historically the second pair of seeds had been used at this point, to make the runs identical regardless of how the network was made, but that this had been changed when seed-resetting was implemented”. In other words, in the process of changing the model they made it non-replicable and never noticed.
Why didn’t they notice? Because their code is so deeply riddled with similar bugs and they struggled so much to fix them that they got into the habit of simply averaging the results of multiple runs to cover it up… and eventually this behaviour became normalised within the team.
In issue #30, someone reports that the model produces different outputs depending on what kind of computer it’s run on (regardless of the number of CPUs). Again, the explanation is that although this new problem “will just add to the issues” … “This isn’t a problem running the model in full as it is stochastic anyway”.
Although the academic on those threads isn’t Neil Ferguson, he is well aware that the code is filled with bugs that create random results. In change #107 he authored he comments: “It includes fixes to InitModel to ensure deterministic runs with holidays enabled”. In change #158 he describes the change only as “A lot of small changes, some critical to determinacy”.
Imperial are trying to have their cake and eat it. Reports of random results are dismissed with responses like “that’s not a problem, just run it a lot of times and take the average”, but at the same time, they’re fixing such bugs when they find them. They know their code can’t withstand scrutiny, so they hid it until professionals had a chance to fix it, but the damage from over a decade of amateur hobby programming is so extensive that even Microsoft were unable to make it run right.
No tests. In the discussion of the fix for the first bug, Imperial state the code used to be deterministic in that place but they broke it without noticing when changing the code.
Regressions like that are common when working on a complex piece of software, which is why industrial software-engineering teams write automated regression tests. These are programs that run the program with varying inputs and then check the outputs are what’s expected. Every proposed change is run against every test and if any tests fail, the change may not be made.
The Imperial code doesn’t seem to have working regression tests. They tried, but the extent of the random behaviour in their code left them defeated. On 4th April they said: “However, we haven’t had the time to work out a scalable and maintainable way of running the regression test in a way that allows a small amount of variation, but doesn’t let the figures drift over time.”
Beyond the apparently unsalvageable nature of this specific codebase, testing model predictions faces a fundamental problem, in that the authors don’t know what the “correct” answer is until long after the fact, and by then the code has changed again anyway, thus changing the set of bugs in it. So it’s unclear what regression tests really mean for models like this – even if they had some that worked.
Undocumented equations. Much of the code consists of formulas for which no purpose is given. John Carmack (a legendary video-game programmer) surmised that some of the code might have been automatically translated from FORTRAN some years ago.
For example, on line 510 of SetupModel.cpp there is a loop over all the “places” the simulation knows about. This code appears to be trying to calculate R0 for “places”. Hotels are excluded during this pass, without explanation.
This bit of code highlights an issue Caswell Bligh has discussed in your site’s comments: R0 isn’t a real characteristic of the virus. R0 is both an input to and an output of these models, and is routinely adjusted for different environments and situations. Models that consume their own outputs as inputs is problem well known to the private sector – it can lead to rapid divergence and incorrect prediction. There’s a discussion of this problem in section 2.2 of the Google paper, “Machine learning: the high interest credit card of technical debt“.
Continuing development. Despite being aware of the severe problems in their code that they “haven’t had time” to fix, the Imperial team continue to add new features; for instance, the model attempts to simulate the impact of digital contact tracing apps.
Adding new features to a codebase with this many quality problems will just compound them and make them worse. If I saw this in a company I was consulting for I’d immediately advise them to halt new feature development until thorough regression testing was in place and code quality had been improved.
Conclusions. 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.
My identity. Sue Denim isn’t a real person (read it out). I’ve chosen to remain anonymous partly because of the intense fighting that surrounds lockdown, but there’s also a deeper reason. This situation has come about due to rampant credentialism and I’m tired of it. As the widespread dismay by programmers demonstrates, if anyone in SAGE or the Government had shown the code to a working software engineer they happened to know, alarm bells would have been rung immediately. Instead, the Government is dominated by academics who apparently felt unable to question anything done by a fellow professor. Meanwhile, average citizens like myself are told we should never question “expertise”. Although I’ve proven my Google employment to Toby, this mentality is damaging and needs to end: please, evaluate the claims I’ve made for yourself, or ask a programmer you know and trust to evaluate them for you.
 

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More reliable information on lockdowns.

Even when new case numbers are low, lifting restrictions will always carry a risk of a second wave of infections. South Korea brought its outbreak under control with a stringent policy of testing, isolation and contact tracing. In recent weeks, the country was reporting only around 10 new cases per day. However, following eased restrictions from 6 May, the Korea Centers for Disease Control and Prevention last week confirmed 102 new cases linked to nightclubs in Seoul. As a result, some clubs and bars have been ordered to close again.
Read more: How can countries know when it’s safe to ease coronavirus lockdowns?
 

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Sweden ignored this defective "scientifically based model" (it's beyond defective, but actually fraudulent) and didn't suffer excessive illness and deaths, plus maintained their economy.
No. Sweden is a model for HOW NOT TO fight the Coronavirus.

Sweden has the highest mortality rate per capita at this stage of the epidemic, according to a Financial Times tracker that uses a seven-day rolling average of new deaths. It has overtaken the UK, Italy and Belgium in recent days.


 

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Discussion Starter #11
So when was it safe for folks to go out and about during flu seasoin, where with a vaccine, over 80,000 dies yet we didn't shut down the entire country.
It's really quite simple - if YOU want to stay locked away in your home, please feel free to do so; but to mandate everyone ELSE needs to do so to alleviate YOUR fears is not only wrong, it is unconscionable on your part.
 

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So when was it safe for folks to go out and about during flu seasoin, where with a vaccine, over 80,000 dies yet we didn't shut down the entire country.
It's really quite simple - if YOU want to stay locked away in your home, please feel free to do so; but to mandate everyone ELSE needs to do so to alleviate YOUR fears is not only wrong, it is unconscionable on your part.
The flu has averaged about 40,000 deaths with a six-month season over the years. Your claim of 80,000 is grossly excessive.
Corona, on the other hand, has killed almost 100,000 in less than four months and it's just getting started. It will far exceed any flu this year.

No, it's not that simple. It's unconscionable on your part if you go out and help the disease kill more vulnerable people.
 

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Your article is citing WHO? Seriously? The same folks, like Pelosi and DeBlasio who encouraged getting out, going to crowded areas and participating in games, etc and going to restaurants.................
No. If you want to gain any credibility you have to refute the info itself.......NOT just claim that the source is no good. That's a rookie move and simply of no value.
 

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I am done with both you and Sidecar; have fun living in fear and isolation; the rest of us will go on living our lives as WE choose, not how some nazi tyrannical governor decides
 

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I am done with both you and Sidecar; have fun living in fear and isolation; the rest of us will go on living our lives as WE choose, not how some nazi tyrannical governor decides
Considering what you've been posting, that's your best move.
 

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Considering what you've been posting, that's your best move.

Just keep it totally one sided and if there is an opposing viewpoint, start whining. Just because Verminator and I don't agree with you is no reason to act like a child.

Like I stated before, there is NO cure. The is NO recognized treatment so the ONLY way to keep from getting it is using common sense, social distancing and wearing a mask when in a public place.

I don't agree with our Governors heavy handed tactics but I do feel that just forgetting about Covid and adopting a cavalier attitude will only net you one thing. Covid.

Because of people like you constantly hammering negativity, I don't come here much anymore and I don't see that changing either.

Only forum I visit with so much negativity and most of that negativity comes from you.

I remember when you first started posting, your posts were actually readable and constructive. Not now.

Too bad really.
 

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Just keep it totally one sided and if there is an opposing viewpoint, start whining. Just because Verminator and I don't agree with you is no reason to act like a child.

Like I stated before, there is NO cure. The is NO recognized treatment so the ONLY way to keep from getting it is using common sense, social distancing and wearing a mask when in a public place.

I don't agree with our Governors heavy handed tactics but I do feel that just forgetting about Covid and adopting a cavalier attitude will only net you one thing. Covid.

Because of people like you constantly hammering negativity, I don't come here much anymore and I don't see that changing either.

Only forum I visit with so much negativity and most of that negativity comes from you.

I remember when you first started posting, your posts were actually readable and constructive. Not now.

Too bad really.
Considering that I just yesterday locked a thread that was degrading into the toilet I disagree, but YMMV. Abby's Dad walked away here from another thread possibly going down the old "crapper". There were three common elements between both threads: Abby's Dad, you and Verminator. Abby's Dad decided to not continue to participate in what is a losing situation and to just let things go because it is not worth it, not to continue and possibly be seen as a troublemaker. That is the adult move.
 

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If up to 60,000 annual flu-related deaths isn't enough to shut down barbers, auto dealer sales, churches, libraries... on and on... every year from Oct-May, how much is enough?

If corona kills 100,000 every year, should I be legally allowed to get a haircut or forever banned? How about going to the dentist for a vanity teeth whitening or straighten a smile? Open wide bro! No mask... shudder to think.

Arguments to ban so-called "non-essential" lack the fundamentals of liberty and Bill of Rights, although gun-grabbing liberals are well practiced. You don't need six bullets to kill a deer. You don't need it... it's not essential. It poses unnecessary risk to society. Attending church is non-essential. It poses unnecessary risk to society. To heck with the Bill or Rights, government will tell you what is essential. After all, it's about saving lives. As gun owners, how many times have we heard that?

Arguments to ban 'non-essential' invariably lack any account to the cost that these lockdowns burden society, both economic and human suffering. There was a study/model published the other day that the human toll could be up to 75,000 lost lives, not including the incalculable misery and despair.

IIRC, someone mentioned selfishness. How selfish is it to burden our children and grandchildren with trillions more in debt as a direct result of government lockdowns? How selfish is it for a 73-year-old shut-in to champion government mandates forbidding young heathy people (who are at little risk of severe illness) from making a living to support themselves and their families?
 
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