Modelling

“Eye-Watering” SAGE Models Had “Too Much Weight”: Another SAGE Scientist Recants His Lockdown Zealotry as the Winds Change

The U.K. relied too much on “very scary” SAGE models to decide on lockdowns, according to the man behind some of those very projections who repeatedly called for longer lockdowns. MailOnline has more.

Just months after SAGE predicted 6,000 deaths per day and called for a Christmas lockdown in response to Omicron, Professor John Edmunds said the models were only supposed to be “one component” of decision-making but were leaned on too much by ministers.

He accepted the models failed to account for the economic harm and the knock-on health effects that lockdowns caused. 

Professor Edmunds admitted that these harms “in principle” could have been factored into models “but in practice they were not”.

His remarks come as Britons face the harsh reality of two years’ of shutting down the economy and health service, with the NHS grappling a backlog crisis that has seen one in nine people in England stuck on an NHS waiting list for treatment and inflation at its highest point in 30 years. 

The epidemiologist, who was among the most outspoken members of SAGE, said some of the death projections in the model were “truly eye-watering”.

Speaking at a medical conference on Tuesday, he said: “The epidemiological model is only one component [of decision-making] and I wondered and I worried that we’d had too much weight.”

He added: “There is of course an enormous economic impact from many of the interventions and other indirect impacts on psychological health and so on. Now these in principle could be included but in practice they were not.”

Professor Edmunds called for the first lockdown to be extended in summer 2021, warning Britain was “taking a risk” by unlocking while still logging 8,000 cases per day and that the decision was “clearly” political.

And he warned against easing the third national lockdown in early 2021, warning it would be a ‘”disaster” and put “enormous pressure” on the health service. 

Joy shall be in heaven over one sinner that repenteth and all that – but you can’t help feel the recantation is very convenient as we move on from the pandemic and people start to look back with more objectivity at all the crazy, costly things that were done in the name of ‘science’ and at the behest of modellers.

Worth reading in full.

WHO Estimates of India’s Covid Deaths Are Highly Suspect

On May 5th, the World Health Organisation (WHO) issued a new report estimating global excess deaths at 14.9m for two years of the pandemic 2020-21 as the true COVID-19 mortality toll, nearly triple the official toll of 5.44m. “Excess mortality” is the difference between the number of deaths that would be expected in any time period based on data from earlier years and the number of deaths that have occurred. For countries with robust data surveillance, reporting and recording systems, this poses no real difficulty. Unfortunately, these conditions are not met in many countries. Therefore their excess mortality can only be estimated and the accuracy is a function of the reliability of the methodology and modelling used in the exercise. Given the overwhelming evidence about the flaws and deficiencies of Covid-related modelling over the last two years, and the damage caused by governments trusting modelling projections over real-world data, this should immediately throw up a forest of red flags about the WHO report.

A second reason to be sceptical is the less than stellar role of the WHO in its well-known Covid-related deference to China, the abandonment of its own summary of the state of the art science on managing pandemics from October 2019, its willingness to manipulate definitions of ‘herd immunity’ in relation to vaccines and natural immunity in order to fit with the experimental pharmaceutical and non-pharmaceutical interventions (NPIs) that came to dominate Covid policy around the world, and its self-interest in expanding its budget, authority and role in steering global health policies and management by means of a new international treaty.

WHO’s Dubious Model that Claims the Real Pandemic Death Toll is 15 Million – and 5 Million of Them Are in India

First we had the Economist claiming to be able to work out how many had really died in the pandemic, then the Lancet joined in. Now it’s the turn of the World Health Organisation. While the Economist and Lancet claim the true toll is around 18 million (though find a very different distribution across countries), the WHO goes for 15 million. Once more we find that the (massive) gaps in reported data are filled in with modelling: “The methods rely on a statistical model derived using information from countries with adequate data; the model is used to generate estimates for countries with little or no data available.”

The estimates for India are particularly inflated and have drawn sharp criticism from the Indian Government. The WHO claims that India experienced 3,400 deaths per million over the two years (note the figures quoted in most reports as WHO estimates for 2020-21 are an average of the two years), which amounts to 4.69 million total deaths – almost a third of the global total. That’s nearly 10 times more than India’s official Covid death toll.

India’s official Covid death toll in 2020 is 148,994. The Government said this week that its official estimate of additional deaths in 2020 compared to 2019 is 474,806, which is 3.2 times higher than the official Covid toll. It hasn’t yet provided its estimate for additional deaths in 2021, but we know that the official Covid death toll for 2021 is 332,492. If we assume the same degree of undercounting then the number of additional deaths in 2021 would be 1.06 million. (Note that India has around 10 million deaths each year, so this represents about a 10% excess mortality in 2021.) Adding the two together gives 1.54 million additional deaths for 2020 and 2021. The WHO’s estimate of 4.69 million is three times higher than this. No wonder the Indian Government is disputing the findings.

How to Ensure Lockdowns Cannot Happen Again

There follows a guest post by former Google software engineer Mike Hearn.

How can we avoid a repeat of the last two years?

To ensure policy failure on such a scale never happens again, those of us who oppose them need concrete legislative proposals that could be implemented by a parliament or congress, and which address the root causes of the failed policies themselves. Very often in history we see that ideas for political reform have to be kicked around the public sphere for a while before being picked up by politicians. In that spirit I lay out some proposed changes to the law, designed to encode lessons learned from the Covid pandemic. Not all of these proposals apply to every country and they take for granted the acceptance of a viewpoint that is still contested – namely, that Covid non-pharmaceutical interventions (NPIs) were a mistake. But the ideas here will hopefully prove useful as a launching point for further discussion – and perhaps, eventually, political campaigns.

My goal here is to make proposals that are only partially within the Overton Window of currently acceptable political thought. The justification: ideas fully within the Window will be generated by politicians during any normal public inquiry anyway. Ideas fully outside it won’t be considered at all. All proposals should be somewhat uncomfortable to read for someone fully committed to mainstream politics, but not entirely so. Please note that anything related to pharmaceutical or financial interventions are out of scope for this article. Further work (perhaps by other people) may address legislative proposals around these.

What the COVID-19 Public Inquiry Needs to Address

Last week, we invited Daily Sceptic readers to submit suggestions of questions or topics that the U.K. COVID-19 Public Inquiry – which is presently consulting on its terms of reference, closing April 7th – ought to address. Here are some of the suggestions.

  • How did the Public Health Act come to overrule basic rights?
  • The classification of ‘cases’, Covid deaths, and the use of mass PCR and LFT testing in healthy people.
  • Lack of cost/benefit analysis of measures, including not estimating the quality-adjusted life years (QALYs) lost by everyone. Whether the three lockdowns were justified from a health standpoint and from an overall cost benefit standpoint.
  • Divisive nature of Government policy, asking people to report their neighbours and discriminating against and demonising the non-vaccinated.
  • The lack of a clear exit strategy when imposing the lockdown measures.
  • The evidence for the claim that the ’vaccines are safe’ and for the quickly shifting goalposts of ages to be vaccinated.
  • How can you claim it was for health when you locked down gyms and leisure centres? Particularly as some leisure centre gyms have GP referral schemes and are part of cardiac rehab phase 4.
  • Did the Government consider the impact on the drop in tax revenue, which funds the NHS, as a result of business closures and people losing their jobs?
  • How many people died because of the lockdowns, through delayed treatment, suicide and by other means?
  • Why did the Government lock down when it had determined that COVID-19 was not a high consequence infectious disease?
  • One of the worst aspects of Government restrictions was that power was given to thousands of managers, proprietors and other operators of businesses, which enabled them to dictate to their workers and staff just what should be done. That the measures were more often than not irrational and counterintuitive was ignored. With the various relaxations that have taken place, some of these people have continued to march, bark, hector and bully more or less unimpeded.
  • Why were so few swabs available for sample collection in 2020?
  • Why has the MHRA not made any comment or public report on the monthly Yellow Card adverse event record? Surely, its job is to examine this information to determine if it is reliable, understated or overstated, and to make recommendations as the regulator? If another medicine was producing these reports would they just keep logging numbers without any comment? And if they have been advised not to comment, by whom?
  • How were mandates implemented without any scientific backing? I am thinking about the Rule of 6, not allowing sitting on a bench outside when walking, the scotch egg debacle, where you were only allowed to sit down in a pub when there was a substantial meal, the mask mandates overall, but in particular having to wear a mask when walking in the pub but being allowed to take the mask off when sitting down, etc.
  • The use of the fear narrative by Government bodies such as Public Health England (now UKHSA).
  • Why was the Coronavirus Act extended for so long each time?

SAGE Stood Down, Signifying End of Pandemic

The Scientific Advisory Group for Emergencies (SAGE) has been stood down in a clear sign that the Government believes the Covid crisis is over. The Telegraph has more.

Although the group “stands ready if required” it will no longer meet regularly, the first time it has halted its ongoing response since January 2020.

The decision was taken after the Government acknowledged that Britain has entered a new phase of its response, and follows the lifting of all remaining legal restrictions in England as part of Downing Street’s Living With Covid plan.

The devolved nations have their own scientific advisory groups and are emerging from the epidemic on slightly different timelines.

The Telegraph understands that the Government will continue to receive Covid advice from other expert bodies, such as the UK Health Security Agency (UKHSA), the Joint Committee on Vaccination and Immunisation (JCVI), as well as from Sir Patrick Vallance, the Chief Scientific Advisor and Sir Chris Whitty, the Chief Medical Officer.

Professor Carl Heneghan, Director of the Centre for Evidence-Based Medicine at the University of Oxford said:

The standing down of SAGE signifies the end of the pandemic in the U.K. This is a remarkable turnabout of events given that just before Christmas, SAGE advisors were warning infections could hit two million per day and were pushing for further restrictions. The Government will need to review whether SAGE is fit for purpose when it comes to pandemics. Particularly given its lack of clinical input and its overreliance on modelling – which we now know is no more than ‘guesswork’ – and its tendency to fixate on a particular set of assumptions.

Neil Ferguson’s Modelling that Led to Britain’s First Lockdown Based on ‘Inaccurate’ Case Data

Professor Lockdown’s modelling team did not have accurate Covid case numbers, and were unsure of hospitalisation and death rates when they published their models suggesting that more than 500,000 people could die if Britain took no action in the first wave of the pandemic, it has emerged after the Telegraph got hold of SAGE minutes with an FOI request. Sarah Knapton, the paper’s Science Editor, has more.

On March 16 2020, Imperial College published its ‘Report 9’ paper suggesting that failing to take action could overwhelm the NHS within weeks and result in hundreds of thousands of deaths.

Before the paper, the UK coronavirus strategy was to flatten the peak rather than suppress the wave, but after the modelling was made public, the Government made a rapid u-turn, which eventually led to lockdown on March 23rd.

However SPI-M (Scientific Pandemic Influenza Group on Modelling) minutes released to the Telegraph under a Freedom of Information request show that by March 16, modellers were still “uncertain” of case numbers “due to data limitations”.

The minutes show that members were waiting for comprehensive mortality data from Public Health England (PHE) and said that current best estimates for the infection fatality rate, hospitalisation rates, and the number of people needing intensive care were still uncertain.

They also believed that modelling only showed “proof of concept” that lockdowns could help, and warned that “further work would be required”.

The team was also encouraged to look for collaborators and resources outside of the infectious diseases network.

Imperial College held a press briefing about its model on the afternoon of March 16th, and on the same day, Boris Johnson ordered the public to avoid pubs, restaurants and non-essential contact and work from home if possible.

At the briefing, Prof Ferguson told journalists that the new conclusions had been reached because “the last few days” had provided “refinements” in the estimates of intensive care demand and hospital surge capacity.

But the minutes now show that SPI-M did not believe the data were complete.

Worth reading in full.

And if you can’t get past the Telegraph’s pay wall, MailOnline has published its own version of the story.

Stop Press: Carl Heneghan tells Julia Hartley-Brewer that the Imperial College modelling team’s mistakes were “inexcusable”.

How The Green Blob Duped Boris over Climate Change

A January 2020 Cabinet Office presentation that is said to have changed Boris Johnson’s mind over the causes of climate change and acted as a ‘road to Damascus’ has been ridiculed by a number of sceptical journalists after it came to light last week following a FOI request. U.S.-based Climate Depot run by Marc Morano said Johnson had been “duped” by U.K. activists, while Paul Homewood from Not A Lot of People Know That, preferred the word “conned”. Overall, Homewood described the event as a “childish attempt to scare the PM”.

It seems to have succeeded. After the meeting Johnson noted “an almost vertical kink upwards in the temperature graphs. He said: “This was a very important moment for me.” Of course, most of the kinks came from climate models, now commonly referred to in the green climate business as ‘evidence’. In fact they are nothing of a kind, having registered 40 straight years of wrong and usually ludicrously high forecasts.

Climate Depot suggested that a more relevant chart to show the Prime Minister was recently produced by the Smithsonian Institution and tracked global temperatures since life took off on Earth (see above). It is very clear, said Climate Depot, that the current temperature of the Earth does “not represent a ‘climate emergency”.

There appears to have been a concerted effort around this time by green advisers, official and unofficial, to bring Boris Johnson fully on board with the green Net Zero agenda. Shortly after becoming Prime Minister in 2019, his partner (now wife) Carrie Symonds said that politicians had a “gigantic responsibility to make the right decisions” about what she described as a climate crisis.

The climate presentation was run by Sir Patrick Vallance, the Government’s Chief Scientific Adviser. Also attending were a number of special advisers, according to documents released under a recent Freedom of  Information request, along with other interested individuals whose names were redacted. The purpose of the meeting was clearly set out in an email from Professor Stephen Belcher, the Chief Scientist at the Met Office. He prepared a slide show and said it demonstrated the goal was to “stabilise climate, which requires net zero emissions”.

At the beginning of 2020, Government scientists were working on stopping the climate warming, citing information from computer models. Within weeks another group of Government scientists, led again by Vallance, would use computer models to justify societal lockdowns, house detention, economic destruction and social distancing to try to stop a common global virus.

Should All Predictive Modelling Be Banned?

Today we’re publishing a piece by James Lewisohn, who says the problem with complex predictive models is they’re too unreliable to be trusted, but he’s not convinced they’re reliably unreliable enough to be banned.

What are the world’s worst inventions? Winston Churchill famously regretted the human race ever learned to fly. I don’t (I’m looking forward to my next holiday too much). Instead, observing the destruction wrought by government pandemic responses predicated upon projected Covid cases, I’m beginning to regret mankind ever invented the computer model.

I have form here. I spent the early years of my career building financial models, hunched over antique versions of Excel on PCs so slow the software might take twenty minutes to iterate to its results – which, once received, were often patently wrong. I developed a healthy mistrust for models, which frequently suffer from flaws of design, variable selection, and data entry (“Variables won’t. Constants aren’t,” as the saying goes).

Models allow outcomes to be presented as ranges. In business, it’s often the best-case outcome which kills you – early-stage companies typically model ‘hockey stick’ revenue growth projections which mostly aren’t realised, to the detriment of their investors. In pandemics, though, beware the worst case. In December, SAGE predicted that Covid deaths could peak at up to 6,000 a day if the Government refused to enact measures beyond Plan B.  The actual number of Covid deaths last Saturday: 262. 

SAGE’s prediction was its worst-case analysis, but the fact that the media (and then the Government) tends to seize upon the worst-case is nothing new. In 2009, Professor Neil Ferguson of Imperial College, to his subsequent regret, published a worst-case scenario of 65,000 human deaths from that year’s swine flu outbreak (actual deaths: 457). As Michael Simmons noted in the Spectator recently: “The error margin of pandemic modelling is monstrous because there are so many variables, any one of which could skew the picture. Indefensibly, Sage members are under no obligation to publish the code for their models, making scrutiny harder and error-correction less likely.”

Worth reading in full.

SAGE Gloomsters Admit They Were Wrong About Omicron

The scientific modellers who warned that Britain had little option but to impose severe restrictions or face tens of thousands of deaths from Omicron were last night in retreat – although they haven’t yet admitted they were wrong about every previous variant as well. MailOnline has more.

First, modellers who advise the Government said winter deaths from the highly transmissible variant would be “substantially” lower than they had originally believed, then Independent SAGE, a group of Left-leaning scientists who have pushed for lockdowns, distanced themselves from the need to impose further curbs.

Before Christmas, epidemiologists at the London School of Hygiene and Tropical Medicine produced a series of dire scenarios in which they warned Omicron could lead to between 25,000 and 75,000 deaths by the end of April.

Dr. Nick Davies said that he and his team were working on revised scenarios that will soon be presented to scientific advisers and senior civil servants.

Tory MP William Wragg, a member of the party’s Covid Recovery Group, said the U-turn provided evidence that many in the scientific community had been too gloomy about the threat from coronavirus.

“Once again, it appears that certain scientists and experts so quick to spread gloom and panic at the arrival of Omicron are having to come to terms with a reality that is far from the catastrophe they were predicting,” he said.

“It all shows that Boris Johnson and his Cabinet were right to avoid condemning us to another lockdown with the dismal effects on people’s livelihoods and liberties.”

The School of Hygiene’s team built its original models – published on December 11th – on the assumption that Omicron was as naturally lethal as the Delta strain, meaning it would kill the same proportion of unvaccinated people who had not been exposed to Covid before.

Dr. Davies argued that while South African doctors were already finding Omicron appeared to be less severe, the reports were “anecdotal” so the School of Hygiene’s supposition was “a reasonable assumption to make at the time”.

Over the past month, however, considerable evidence has built up that Omicron is less dangerous. This includes statistical studies by Imperial College London, Edinburgh University and the U.K. Health Security Agency, as well as research from South Africa and Denmark. Laboratory studies have also found Omicron is less adept at infecting the lungs.

Dr. Davies said the December model had assumed that once a patient ended up in hospital with Omicron, their chance of needing intensive care and dying was the same as with Delta – which has proved to be incorrect.

“We now know that doesn’t seem to be at all the case, as people are ending up in hospital with Omicron, but they are not requiring critical care [to the same extent as with Delta],” he said. “The deaths number will come down very substantially [compared with original estimates].”

Worth reading in full.

Stop Press: According to Gordon Rayner in the Telegraph, questions are now being asked about why SAGE’s modellers – and England’s Chief Medical Officer – were so dismissive of the evidence from South Africa three weeks ago showing Omicron was “very, very mild” and wouldn’t result in a big uptick in hospital admissions.

Stop Press 2: Daily Covid cases across Britain have fallen for the fourth day in a row and are down 6.7% compared to last Sunday. MailOnline has more.