But with no sign of a second summer wave nor an autumn eruption reminiscent of 1918, the commentariat has amended the definition. Suddenly, a “second wave” meant Covid’s seasonal return, in winter, a year on. Widespread adoption of a new phrase in the Covid lexicology – “winter wave” – has academically formalised the idea.
But instead of looking us square in the eye, the Tories have chosen Big Brother’s panopticon; No 10’s new Joint Biosecurity Centre, which will drive “whack-a-mole” local lockdowns, is slickness posing as strategy – and, as it happens, reporting into track-and-trace app failure Dido Harding. When the public twigs that the infection is unlikely to be controlled in this way, the sheer panic could send us back into national lockdown. Three scenarios might help avoid the latter: a vaccine comes along; the Government gets its act together with a plan to protect the vulnerable; or we put in place safety valves against mass hysteria.
Imperial College’s research needs to be particularly scrutinised, as its international influence grows. Dr Seth Flaxman – the first author in the paper that notoriously claimed lockdowns may have prevented over 3 million deaths in Europe – this week won fresh funding to model the pandemic across several countries.
Revelations that disrupt the narrative also need to find a stronger voice: within 24 hours, the scandal of PHE’s inflated daily death figures was running out of mileage. This week’s London School of Hygiene and Tropical Medicine modelling on the impact of the pandemic on cancer deaths never gathered steam. So too a paper by Oxford’s Prof Sunetra Gupta, which elegantly combined those uneasy epidemiological bedfellows – theory and evidence – to find some parts of the UK may already have reached herd immunity.
This recent crop of trials added 9,112 participants to the total randomised denominator of 13,259 and showed that masks alone have no significant effect in interrupting the spread of ILI or influenza in the general population, nor in healthcare workers.
The small number of trials and lateness in the pandemic cycle is unlikely to give us reasonably clear answers and guide decision-makers. This abandonment of the scientific modus operandi and lack of foresight has left the field wide open for the play of opinions, radical views and political influence.
- Some experts argued that masks would help slow the infection rate.
- Others pointed out that improper use of face masks can amplify risks, for instance by acting as a reservoir for virus particles.
- It seems that today’s mantra of ‘listen to the science’ is not as straightforward as it seems.
- Claims to wear masks are untested and unchallenged, then elevated to the status of ‘the science’.
- The hasty assembling of research articles in support of a policy position is not science. This is as likely to be to be dangerously misleading as it is to yield even negligible benefits.
- Scientific controversy in the 21st century is settled by institutional weight and muscle, not by experiment.
- The president of the Royal Society wants to have his cake and eat it: he wants the government to defer to institutional science, but not for science to be accountable for this influence.
- The government, weakened by its capitulations to breakfast TV anchors, politically motivated scientists and scientific institutions, may find itself unable to roll back policies which turn out to do more harm than good.
- There is no scientific evidence that masks are effective in reducing the risk of SARS-CoV-2 transmission.
- Sweeping mask recommendations will not reduce SARS-CoV-2 transmission, as evidenced by the widespread practice of wearing such masks in Hubei province, China.
- Cloth masks will be ineffective at preventing SARS-CoV-2 transmission, whether worn as source control or as PPE.
- Surgical masks likely have some utility as source control from a symptomatic patient in a healthcare setting to stop the spread of large cough particles and limit the lateral dispersion of cough particles.
- Surgical masks may also have very limited utility as source control or PPE in households.
- Authors do not know whether respirators are an effective intervention as source control for the public.
- A non-fit-tested respirator may not offer any better protection than a surgical mask.
- Respirators work as PPE only when they are the right size and have been fit-tested to demonstrate they achieve an adequate protection factor.
- There is no evidence to support use of cloth masks by the public or healthcare workers to control the emission of particles from the wearer.
- Wearing surgical masks in households appears to have very little impact on transmission of respiratory disease.
- There is no evidence that surgical masks worn by healthcare workers are effective at limiting the emission of small particles or in preventing contamination of wounds during surgery.
- There is moderate evidence that surgical masks worn by patients in healthcare settings can lower the emission of large particles generated during coughing and limited evidence that small particle emission may also be reduced.
- Data from laboratory studies indicate masks offer very low filter collection efficiency for the smaller particles.
- The authors were unable to locate any well-performed studies of cloth mask leakage when worn on the face—either inward or outward leakage.
- Many references to coverings employ very crude, non-standardized methods or are not relevant to cloth face coverings because they evaluate respirators or surgical masks.
- The National Academies of Sciences Rapid Expert Consultation on the Effectiveness of Fabric Masks for the COVID-19 Pandemic: “The evidence from…laboratory filtration studies suggests that such fabric masks may reduce the transmission of larger respiratory droplets. There is little evidence regarding the transmission of small aerosolized particulates of the size potentially exhaled by asymptomatic or presymptomatic individuals with COVID-19.”
- Authors concerned that many people do not understand the very limited degree of protection a cloth mask or face covering likely offers as source control for people located nearby.
- Cloth masks and face coverings likely do not offer the same degree of protection as physical distancing, isolation, or limiting personal contact time.
- Transmission is not simply a function of short random interactions between individuals, but rather a function of particle concentration in the air and the time exposed to that concentration.
- A cloth mask or face covering does very little to prevent the emission or inhalation of small particles.
Such is the quality of decision-making in the process generating our lockdown narrative. An early maintained but exaggerated belief in the lethality of the virus reinforced by modelling that was almost data-free, then amplified by further modelling with no proven predictive value. All summed up by recommendations from a committee based on qualitative data that hasn’t even been peer-reviewed.
- According to Office for National Statistics, this year comes only eighth in terms of deaths in past 27 years.
- The spread of viruses like Covid-19 is not new. What’s new is our response.
- The whole Covid drama has really been a crisis of awareness of what viruses normally do, rather than a crisis caused by an abnormally lethal new bug.
- Modelling is not science, for the simple reason that a prediction made by a scientist (using a model or not) is just opinion.
- To be classified as science, a prediction or theory needs to be able to be tested, and potentially falsified.
- A problem with the current approach: a wilful determination to ignore the quality of the information being used to set Covid policy.
- Most Covid research was not peer- reviewed.
- In medical science there is a well-known classification of data quality known as ‘the hierarchy of evidence’: a seven-level system gives an idea of how much weight can be placed on any given study or recommendation.
- Randomised controlled trials (RCTs) form the highest, most reliable form of medical evidence: Level 1 and 2.
- Virtually all evidence pertaining to Covid-19 policy is found in the lowest levels (much less compelling Levels 5 and 6): descriptive-only studies looking for a pattern, without using controls.
- Level 7 is at the bottom of the hierarchy (the opinion of authorities or reports of expert committees) because ‘authorities’ often fail to change their minds in the face of new evidence.
- Committees often issue compromise recommendations that are scientifically non-valid.
- The advice of Sage (or any committee of scientists) is the least reliable form of evidence there is.
- Far from following the science, the government turned its back on all available data.
- Until mid-April, with the escalating deaths in care homes agonisingly clear across Europe, government policy was still for patients to be discharged to care homes from hospitals without requiring negative tests. And so the toll: around half of UK Covid-19 deaths are care home residents, despite them accounting for only 0.6 per cent of our population.
- Germany, whose population is roughly 25 per cent bigger than ours, has suffered approximately a quarter of our Covid deaths.
- Ministers have deferred to scientists who themselves deferred to the projections of models, even when data on the ground told a completely different story.
- Statisticians on social media had a field day pointing out the chasm between modelled outcomes and reality, but it is not clear that the models on which SAGE relied (both their input parameters and mechanical dynamics) were continually refined with on-the-ground data (or simply discarded as wrong).
- Why weren’t Oxford’s team, who specialise in zoonotic viruses and who looked at the same data as Neil Ferguson’s modelling-led team but came to wildly different conclusions, on SAGE’s panel to provide an alternative view?
- Why were there no economists on SAGE? Economics is not the bloodless pursuit of money but the science of decision-making under uncertainty where resources are finite; could they really have brought nothing to the party?
- In mid-March, Stanford’s Nobel laureate Michael Levitt (biophysicist and professor of structural biology) discussed the “natural experiment” of the Diamond Princess cruise ship, a petridish disproportionately filled with the most susceptible age and health groups. Even here, despite the virus spreading uncontrolled onboard for at least two weeks, infection only reached a minority of passengers and crew.
- The data towards the end of March clearly showed we were already near the tipping point of the bell-curve (meaning the disease is on the wane). We were already past the point where lockdown could have made much difference.
- Knut Wittkowski: “respiratory diseases [including Covid-19] . . . remain only about two months in any given population”.
Writing for the Telegraph, Professors Carl Heneghan and Tom Jefferson, from the University of Oxford, said there is little evidence to support the restriction and called for an end to the “formalised rules”.
The University of Dundee also said there was no indication that distancing at two metres is safer than one metre.
The scientific establishment in this country has had a bad war. Its mistakes have probably made the Covid-19 epidemic, as well as the economic downturn, worse. Britain entered the pandemic late, with lots of warning, so we should have done better than other countries. Instead we are one of the worst affected in Europe and one of the last to begin to recover.
Britain’s lockdown nightmare may be far from over, but an attempt to rewrite the history of the country’s greatest political blunder has already begun. With the UK now past the peak, the lack of evidence that lockdown served any useful purpose is glaring. And crucially, thanks to a growing abundance of raw data – from deaths and hospital admissions, to Covid-related 111 calls and mobile tracking intelligence –we now have the power to piece together what Britain’s lockdown achieved (or didn’t) in hideous technicolour.
Getting at the truth will be an uphill struggle, however: Downing Street has shown no appetite whatsoever for sifting through the evidence, even though it could inform (or, let’s face it, rip apart) its uniquely odd approach to easing lockdown. We must also beware the shape-shifting, scientific architects of the stay-at-home order; as criticism grows, are they attempting to dress their reconstructed reality in the language of scientific pedantry?
One of the key things about science – obvious to its practitioners, but often obscure to outsiders – is that it is fuelled by doubt, not certainty. When the ‘facts’ change (as they often do), and when original assumptions are qualified or overturned, then any scientist worth their salt re-examines and, if necessary, alters their conclusions. The presence of cross-reactive helper cells in maybe half the population means that ideas about a possible second wave must be rewritten. This finding must make a second wave less likely, probably much less likely. And the fact that there has been no ‘second wave’ (as opposed to isolated outbreaks) anywhere where lockdown has been released also fits this hypothesis. It may well also explain why the first wave didn’t infect much higher proportions of the population.
Pharmaceutical companies are putting pressure on scientific results says Philippe Douste-Blazy, Cardiology MD, Former France Health Minister.
- There were many signs that were really available by the end of February indicating this is a virus that has ‘weak legs.’
- The data was all available by the end of February  and anyone who can use Excel could analyse it.
- “The best statistical test is the eyeball test.” And if you chart things in Excel, you can very quickly make an instinctive judgement.
- No country succeeded in protecting the elderly and nursing homes–it’s hard thing to do.
- We had a soft flu season. The people who would have been susceptible to a generic flu were hit by a virus that came late and swept through rapidly. This could explain the high COVID-19 death numbers among the vulnerable.
- Many analysts agree that the lockdown did nothing to affect the peak of infections and deaths.
- None of the pro-lockdown people seemed to analyse the data and used the data to support lockdown.
- Many pro-lockdown scientific colleagues are academics receiving salaries; their lives would not be negatively affected by the lockdown. Scientists love nothing more than staying at home to work.
- What really matters is the years lost rather than the number of dead. Life is risky and when you’re old, life is more risky. You’re expecting younger people to give their future to get two more months of life.
- While COVID-19 is not the same as the flu, the numbers look very similar.
- People rolled over for a lockdown based on no real solid science.
- There’s a whole fallacy about the R value because it is dependent on the time you’re infected and no one knows what the time infected is, no one knows about hidden cases.
Source website: https://thefatemperor.com
The observation that the greatest reduction in COVID-19 cases was achieved under the combined [social distancing] intervention is not surprising. However, the assessment of the additional benefit of each intervention, when implemented in combination, offers valuable insight. Since each approach individually will result in considerable societal disruption, it is important to understand the extent of intervention needed to reduce transmission and disease burden.
The effectiveness and societal impact of quarantine and social distancing will depend on the credibility of public health authorities, political leaders, and institutions. It is important that policy makers maintain the public’s trust through use of evidence-based interventions and fully transparent, fact-based communication.
There’s almost a whiff of superstition about No 10’s secretive “evidence-based” approach to lifting lockdown. Ministers are peddling an esoteric assortment of “precautionary” measures, from a scientifically baseless two-metre rule to a pointless 14-day holiday quarantine. They are obscure and enigmatic on risks and trade-offs. And, in the daily press conferences, they continue to bewitch an already hyper-paranoid public with lurid graphs and charts that propagate bogus science.
‘Evidence’ has been turned into a gospel truth and that’s bad for political decision-making.
With ministers and officials involved with the country’s coronavirus strategy braced for an eventual public inquiry, this week we’re being given a glimpse of how it might play out. During a morning broadcast round on Tuesday, Work and Pensions Secretary Thérèse Coffey set the cat among the pigeons when she was asked about mistakes the government may have made. It’s clear that this is a row No. 10 does not wish to be having right now.
Coffey replied by saying ministers can ‘only make judgments based on the advice’ they are given. She went on to say that on issues such as testing capacity, if the scientific advice at the time was ‘wrong’, she would not be surprised if people think ‘we made the wrong decisions’. Those comments were quick to gain traction – with critics claiming Coffey was attempting to scapegoat scientists for the government’s U-turn on testing.
The idea that government advisers can separate science and politics is bogus, says Melanie Smallman
…having spent seven years in frontline science advice, I find the persistence of the idea that scientific advice can be separated from politics surprising.
…because it was impossible to describe the science without revealing the policy advice. The questions being asked and the particular science being used were all shaped by the direction that policy was taking—and vice versa.
At a time of a global pandemic, bringing more—and more diverse—expertise to bear on the issue has to be welcome. But the danger is that, in pursuing some ideal of scientific independence, political issues get disguised as technical matters. This risks handing decisions to scientific experts rather than elected politicians, hiding both decisions and politicians from public scrutiny.
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- Credentials: MSc PhD
- E-mail: [email protected]
- Website: www.kevinpcorbett.com
- Download: PDF from external site
An Interactive Anti-Coronavirus Toolkit
“He had moved from thought to words, and now from words to actions.”George Orwell, 1984
In this toolkit I draw on the predictive power of fiction together with various medical and other sources to both describe and illustrate how the Hysteria over the ‘novel Coronavirus’ is leading towards a form of physical and cultural death.
This Hysteria has bred mass delusion biasing medical diagnosis to more fully bolster and grossly inflate the evidence for the spurious disease category of ‘Covid-19’. This occurs through the medical generation of illness and death, caused by faulty clinical reasoning during medical examination and treatment [‘iatrogenesis’]. This process of iatrogenesis is assisted also by powerful social forces like Terror and Fear [‘sociogenesis’] .
All of these medical and social forces are being marshalled and fuelled in Great Britain and overseas by the confluence of Hysteria from the respective elected Governments, The World Health Organisation, the US Centres for Disease Control (CDC) and other non-elected supranational agencies, which are all now fatally impacting on our national psyches and policy makers.
These unelected agencies include, the 24-7 cycling Mainstream Media (MSM), The Bill and Melinda Gates Foundation (who fund Imperial College London a British source of Lockdown modelling), Gilead, and other pharmaceutical interests.
All of the above respective commercial and academic interests stand to gain financially from any subsequent mandatory mass screening, testing, treatment and travel certification (‘passporting’).
The investigative journalists are right on it. Celia Farber cites the above confluence of vested interests, the “Gates-led Pandemic Reich”. Jon Rappoport calls them the “..actual conspiracy theorists—Gates, WHO, CDC—who invented the conspiracy..” ‘Covid-19’ and the government Lockdowns.
Read the full monograph. (Opens PDF from external site.)
The biggest political ruse of our time has now spiralled so far out of control that it has become almost impossible to distinguish fact from deception. Every day we are besieged with such a selective and biased artillery of “scientific” assertions that it makes a mockery of expert insight.
Every day we are subjected to yet more bitesized epidemiology that gives an utterly false impression of risk. And every day we are bombarded with terrifying death figures so out of context that they are effectively meaningless.
Government scientific advisers are furious at what they see as an attempt to censor their advice on government proposals during the Covid-19 lockdown by heavily redacting an official report before it was released to the public, the Guardian can reveal.