Neil Ferguson, who became known as “professor lockdown” after convincing Boris Johnson to radically curtail everyday freedoms, acknowledged that, despite relying on “quite similar science”, the Swedish authorities had “got a long way to the same effect” without a full lockdown.
What’s truly surprising is just how recent the theory behind lockdown and forced distancing actually is. So far as anyone can tell, the intellectual machinery that made this mess was invented 14 years ago, and not by epidemiologists but by computer-simulation modelers. It was adopted not by experienced doctors – they warned ferociously against it – but by politicians.
We spoke to Sunetra Gupta, Professor of Theoretical Epidemiology at the University of Oxford and head of the team that released a study in March which speculated that as much as 50% of the population may already have been infected and the true Infection Fatality Rate could be as low as 0.1%.
In her first major interview since the Oxford study was published, she goes further by arguing that Covid-19 has already passed through the population and is now on its way out. She said:
• Many of the antibody tests are “extremely unreliable”
• They do not indicate the true level of exposure or level of immunity • “Different countries have had different lockdown policies, and yet what we’ve observed is almost a uniform pattern of behaviour”
• “Much of the driving force was due to the build-up of immunity”
• “Infection Fatality Rate is less than 1 in 1000 and probably closer to 1 in 10,000.”
• That would be somewhere between 0.1% and 0.01%
On lockdown policy:
• Referring to the Imperial model: “Should we act on a possible worst case scenario, given the costs of lockdown? It seems to me that given that the costs of lockdown are mounting that case is becoming more and more fragile”
• Recommends “a more rapid exit from lockdown based more on certain heuristics, like who is dying and what is happening to the death rates”
On the UK Government response:
• “We might have done better by doing nothing at all, or at least by doing something different, which would have been to pay attention to protecting the vulnerable”
On the R rate:
• It is “principally dependent on how many people are immune” and we don’t have that information.
• Deaths are the only reliable measure.
On New York:
• “When you have pockets of vulnerable people it might rip through those pockets in a way that it wouldn’t if the vulnerable people were more scattered within the general population.”
On social distancing:
• “Remaining in a state of lockdown is extremely dangerous”
• “We used to live in a state approximating lockdown 100 years ago, and that was what created the conditions for the Spanish Flu to come in and kill 50m people.”
On next steps:
• “It is very dangerous to talk about lockdown without recognising the enormous costs that it has on other vulnerable sectors in the population”
• It is a “strong possibility” that if we return to full normal tomorrow — pubs, nightclubs, festivals — we would be fine.
On the politics of Covid:
• “There is a sort of libertarian argument for the release of lockdown, and I think it is unfortunate that those of us who feel we should think differently about lockdown”
• “The truth is that lockdown is a luxury, and it’s a luxury that the middle classes are enjoying and higher income countries are enjoying at the expense of the poor, the vulnerable and less developed countries.”
One reason why the models failed is that they – just like most countries’ politicians – underestimated how millions of people spontaneously adapt to new circumstances. They only thought in terms of lockdowns vs business as usual, but failed to consider a third option: that people engage in social distancing voluntarily when they realise lives are at stake and when authorities recommend them to do so.
As countries plan how to leave lockdown, they can look at Sweden and ask: what happens if you don’t involve the police, if you don’t issue edicts about how many of your relatives or neighbours you can visit, and just ask people to be careful? Might that work? The Swedish experiment casts huge doubts on the models, and makes the case for trusting the public.
Imperial College’s modelling of non-pharmaceutical interventions for Covid-19 which helped persuade the UK and other countries to bring in draconian lockdowns will supersede the failed Venus space probe and could go down in history as the most devastating software mistake of all time, in terms of economic costs and lives lost.
…when a codebase is used to craft scholarly publications that are in turn used to influence public policy, the authors of those publications (and ultimately policy) need to ensure that the science is verifiable in a public sense. The lack of tests makes that an impossibility. So closure of this Issue, by retraction of studies based on it, is meant as a critique of the publication and policy authors, not the contributors to this repo
…for thirteen years, taxpayer funding from the MRC went to Ferguson and his team, and all it produced was code that violated one of the most fundamental precepts of good software development – intelligibility.
This Ferguson Model is such a joke it is either an outright fraud, or it is the most inept piece of programming I may have ever seen in my life. There is no valid test to warrant any funding of Imperial College for providing ANY forecast based upon this model. This is the most UNPROFESSIONAL operation perhaps in computer science. The entire team should be disbanded and an independent team put in place to review the world of Neil Ferguson and he should NOT be allowed to oversee any review of this model.
Professor Neil Ferguson of Imperial College “stepped back” from the Sage group advising ministers when his lockdown-busting romantic trysts were exposed. Perhaps he should have been dropped for a more consequential misstep. Details of the model his team built to predict the epidemic are emerging and they are not pretty. In the respective words of four experienced modellers, the code is “deeply riddled” with bugs, “a fairly arbitrary Heath Robinson machine”, has “huge blocks of code – bad practice” and is “quite possibly the worst production code I have ever seen”.
Even if one could understand why lockdown was imposed, it very rapidly became apparent that it had not been thought through. Not in terms of the wider effects on society (which have yet to be counted) and not even in terms of the ways that the virus itself might behave. But at the start, there was hardly any evidence. Everyone was guessing. Now we have a world of evidence, from around the globe, and the case for starting to reverse lockdown is compelling.
- You cannot understand the significance of this virus simply by looking at the raw death figures
- The policy response to the virus has been driven by modelling of Covid – not other factors
- We don’t know if lockdown is working
- We should ease the lockdown to save lives
- Lockdown is not sustainable
- Lockdown directly harms those most likely to be affected by coronavirus
- Lockdown directly harms those who will be largely unaffected by coronavirus
- The health service has not been overwhelmed nor likely to be
- The virus is almost certainly not a constant threat
- People can be trusted to behave sensibly
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.
Indeed, Ferguson’s Imperial College model has been proven wildly inaccurate. To cite just one example, it saw Sweden paying a huge price for no lockdown, with 40,000 COVID deaths by May 1, and 100,000 by June. Sweden now has 2,854 deaths and peaked two weeks ago. As Fraser Nelson, editor of Britain’s Spectator, notes: “Imperial College’s model is wrong by an order of magnitude.”
Throughout the UK’s coronavirus crisis, the government has stressed its response has been guided not by ideology; not by politics – but by the science. So what are the scientific justifications for lockdown?
Disruption to tuberculosis services due to the Covid-19 pandemic could lead to as many as 6.3 million additional cases of TB and 1.4 million deaths worldwide over the next five years, a new study has shown
Perspectives on the Pandemic – Episode 6: When Dr. Dan Erickson and Dr. Antin Massihi held a press conference on April 22nd about the results of testing they conducted at their urgent care facilities around Bakersfield, California, the video, uploaded by a local ABC news affiliate, went viral. After reaching five million views, YouTube took it down on the grounds that it “violated community standards.” We followed up with the doctors to determine what was so dangerous about their message. What we discovered were reasonable and well-meaning professionals whose voices should be heard.
With a purely statistical perspective, [Prof Michael Levitt] has been playing close attention to the Covid-19 pandemic since January, when most of us were not even aware of it. He first spoke out in early February, when through analysing the numbers of cases and deaths in Hubei province he predicted with remarkable accuracy that the epidemic in that province would top out at around 3,250 deaths.
Science is not a good guide for society. Of course science is essential to our understanding of the world and to the creation of the new insights, technologies and treatments our societies need. But it cannot tell us what is best for our societies in political, moral or economic terms…
If it is true that Boris put the country into lockdown partly in response to media pressure, then the media themselves may have a lot of questions to answer about the damage currently being done by this unprecedented freeze on working life and the economy.
Overall, however, the fact that good-sized regions from Utah to Sweden to much of East Asia have avoided harsh lockdowns without being overrun by Covid-19 is notable….And empirical analyses of national and regional response strategies…do not necessarily find that costly lockdowns work better against the virus than social distancing.
- UK policy on lockdown and other European countries are not evidence-based
- The correct policy is to protect the old and the frail only
- This will eventually lead to herd immunity as a “by-product”
- The initial UK response, before the “180 degree U-turn”, was better
- The Imperial College paper was “not very good” and he has never seen an unpublished paper have so much policy impact
- The paper was very much too pessimistic
- Any such models are a dubious basis for public policy anyway
- The flattening of the curve is due to the most vulnerable dying first as much as the lockdown
- The results will eventually be similar for all countries
- Covid-19 is a “mild disease” and similar to the flu, and it was the novelty of the disease that scared people.
- The actual fatality rate of Covid-19 is the region of 0.1%
- At least 50% of the population of both the UK and Sweden will be shown to have already had the disease when mass antibody testing becomes available
Summary from 21st Century Wire.