The UK’s pandemic response relies too heavily on scientists and other government appointees with worrying competing interests, including shareholdings in companies that manufacture covid-19 diagnostic tests, treatments, and vaccines. Government appointees are able to ignore or cherry pick science—another form of misuse—and indulge in anti-competitive practices that favour their own products and those of friends and associates.
- COVID-19 is not a dread disease that will kill everyone.
- The initially high case fatality rate of COVID-19 was because the medical community didn’t know how to treat it.
- The fatality rate of flu is 0.1% (1 in every 1,000 who are infected end up dying).
- Ventilators are the wrong option if you do not have an obstructed airway disease.
- Prod. Ioannidis: The infection fatality ratio of COVID-19 is 0.15%. This is pretty much the same as the flu.
- We should just ask people to be careful but otherwise go about your daily life.
- These things pass every year. This is the first ‘social media pandemic.’
- The normal practice for intensive care beds in the NHS is to run them almost full. This is because a lot of intensive care bed assignment is planned.
- ICU use at the height of the pandemic was has very low because the NHS was run as light as possible to cope with a second wave.
- Respiratory viruses don’t do waves.
- This is not opinion but is basic understanding among experts in the field. It is supposrted by the highest quality science. Sir Patrick Vallance knows this.
- COVID-19 follows the Gompertz Curve.
- You have immunity after your body has fought off a respiratory virus. If that was not the case, you’d be dead. Immunity probably lasts decades based on evidence from other viruses.
- Gompertz Curve is identical in all heavily infection regions.
- Something awefull happened in the middle of the year: PCR swab test.
- It is not true that if you test more people you’ll save more lives. A certain percentage of the test will come up positive even if there’s no virus in you.
- False positive rate wasn’t released.
- Kate Barker wrote in a government document on June 3rd, 2020, to SAGE: test has an unknown false positive rate; based on similar tests it may be between 1%-2%. This is a big deal.
- Based on 1%: for every 1,000 people you test, 10 will come back positive, even if they don’t have the virus. If prevalence is only 0.1% as reported by ONS, only 1 in 1,000 will be genuine. This means 9 in 10–in other words 90%–are false.
- Pillar 2 testing would have caused of the most of the positives to be false.
- 1,700 people die normally every day in the UK. During the summer, only about 10 were dying per day of covid.
- More testing, more false positives. We’ll never escape covid if we keep testing because most of the positives will be false. This is immunology 101. Sir Patrick Vallance would have known this.
- Influenza is a high mutation-rate virus. Coronaviruses are relatively stable so once you’ve recovered, you are probably immune for decades.
- COVID-19 kills 0.15%-0.2%, slightly more lethal than the average flu. Once it’s gone through the population, it won’t come back.
- 99.94% survive COVID-19 and will be resistant for a long time.
- COVID-19 is 80% similar to SARS-COV-1.
- People who were exposed to SARS have T-cell immunity 17 years later. Evidence for COVID-19 all point in direction.
- Our bodies have many lines of defense, including innate immunity and T-cells. Antibodies are in the last line of defense.
- Study shows around 30% prior immunity to SARS-COV-2. It was due to exposure to common-cold coronaviruses.
- The claim made by Sir Patrick Vallance that more than 90% are susceptible is a lie.
- Mass testing of the well populating is the worst problem as it generates false positives, fear and control.
- If you’re immune, you can’t be infected or infectious. Herd immunity is already in play in London.
- If SAGE is correct, London should be ‘ablaze’ with deaths.
- Current testing methods are not forensically sound.
- Tests detect common cold and dead virus.
- SARS-COV-2 has never really been a public health emergency.
- We do not need the vaccine to return to normal. Most people are not in danger from COVID-19. More people are in danger from car crashes and we accept that risk.
- Best case scenario is that the vaccine is 50% effective. Natural immunity might be better.
- The most vulnerable often don’t respond well to vaccines and die anyway.
- SAGE is giving lethally wrong advice.
- The reason the pandemic is not over is because SAGE says it’s not.
When deciding whom to listen to in the covid-19 era, we should respect those who respect uncertainty, and listen in particular to those who acknowledge conflicting evidence on even their most strongly held views. Commentators who are utterly consistent, and see whatever new data or situation emerge through the lens of their pre-existing views—be it “Let it rip” or “Zero covid now”—would fail this test.
- Scientists should not be involved in devising and implementing policies.
- The window of opportunity to suppress the virus is gone.
- The toll on public health caused by closed borders will be absolutely awful.
- Indefinite suppression may not have ever been an option.
- Vaccines may be helpful but won’t be a silver bullet.
- The virus is here to stay.
- Vaccines may be effective in reducing symptoms but we can’t gamble on an infection blocking vaccine.
- Some vaccines aren’t always suitable for the entire population.
- Banking everything on a vaccine is not a reasonable approach.
- National level measures are not convincing; targeted measures have more potential.
- Communication has been problematic so public trust has been lost.
- Fear over a long period of time is physiologically unhealthy and doesn’t ever just evaporate.
- The cost of allowing people to choose their own risk-level would be much lower than the current blanket proposals.
- Well-targeted testing can be extremely effective but mass testing in schools is not a good use of tests.
- The ‘medicalization’ of society is worrying.
- Blanket testing of asymptomatic people is completely new and presents multiple ethical problems.
- Proportion of asymptomatic cases for 2009 influenza pandemic was around 50%-75%; this is similar to what we’re finding COVID-19.
- COVID-19 is not so different from other viruses but the global approach is completely different.
- Normalising the mass testing of otherwise healthy testing is very dangerous.
- There’s not much to be gained from comparing the measures and results between countries; the move to technocracy is dangerous.
- Whole societies should not turn around public health.
- A constant climate of fear is counter-productive.
- There were other countries that took a similar approach to Sweden, such as Switzerland.
- Past pandemics have been comparable to COVID-19 but did not have the same response.
- Outbreaks in care homes is nothing new.
- The pandemic phase of COVID-19 should eventually be over by mid to end of 2021 and in all likelihood become endemic.
- The most important message: COVID-19 presents a severe health crisis but it is not a ‘new normal.’
My 30 years of working in academic environments, as both a scientist and a clinical academic, tell me this: a scientist’s career objective is to big up his subject, which increases his personal likelihood of gaining grants, influence and promotion. Scientists focus on narrow topics, often almost to the exclusion of everything else. Perspective is rarely a strong point. The more their subject is in the public eye, preferably centre stage, the better it is from a career point of view. Any crisis is, I’m afraid, a career opportunity for some. Unbiased, agenda-free, selfless public service is not, I believe, a key feature of academic life, nor is there any real reason to expect it to be.
The management of the Covid ‘crisis’ – a crisis substantially caused by the very management itself – has all the hallmarks of government being advised by a group of experts in the limelight, in thrall to groupthink, and with far too cosy a consensus to do effective science.
- Science has already proved that masks don’t work.
- Many large Randomised Control Trials (RCT) and meta-analyses over the past decade show masks offer no reduction in risk from respiratory viruses.
- We understand the mechanism of transmission of respiratory disease and the science is clear that masks can’t work.
- It can’t help others when you’re breathing out and it can’t help you when you’re breathing in.
- The mechanism of transmission is through very small aerosol particles.
- Any opening in the mask will allow enough of the minimal dose to infect you.
- One of the effects shown in studies with healthcare workers is that they had an increase in headaches.
- Many articles in support of masks are not relevant e.g. masks stop droplets but transmission is not via droplets.
- Diseases are seasonal because droplets are carried for a long time when the air is dry like in the winter.
- The government is purporting to engage with ‘The Science’, but it is also engaging in psychological operations.
- But a side-effect of compelling people to wear masks is that some may decide it is all too stupid, and they are not going to go to the shops until this idiocy is over.
- But a side-effect of compelling people to wear masks is that some may decide it is all too stupid, and they are not going to go to the shops until this idiocy is over.
- The science on masks is very weak. The claim is that you might spread Covid-19 without knowing, if you have it asymptomatically.
- Firstly, asymptomatic Covid-19 spreading around is good because it reduces the virulence of the virus.
- Secondly, the idea that masks stop the spread is not only totally unproven, but also facile. It is a failure of imagination.
- When a droplet hits a mask, it will dry out within seconds or, at most, minutes. If there is any substance to the droplet other than water, it will turn into a dust particle. Unless you superglue the mask to your face, there will be a constant rain of dust particles coming out from all directions around your mask as you breathe. They will be breathed in by others and the virus will do what it does.
- There seems to have been no assessment whatsoever of the effects of lockdown before we entered it. That violates a key principle of medicine: first, do no harm.
- There is a term in medicine for taking action without that knowledge: negligence. The government was negligent in putting us into lockdown with no assessment of what that would do.
- The most common symptoms of Covid-19 are not fever, cough, headache and respiratory symptoms – they are no symptoms at all, and around 99 per cent of those who catch this virus recover.
- The government painted itself into a corner very quickly. It doesn’t know how to get out of that corner apart from by acting out the scenario that it came up with in the first place, which is why, months after we could have abolished all these restrictions and got back to normal, we are going through more months of public virtue-signalling and ritualistic behaviour.
- The WHO is not fit for purpose and whose performance has been lamentable
- The WHO said there were no asymptomatic cases of Covid-19. Now, it is reckoned probably about 90 per cent of people who get Covid-19 are asymptomatic. That is a big change in viewpoint.
- Broadcasters have done a woeful job of presenting balance on this, and have not allowed views contrary to the mainstream narrative to reach the public.
- I also fear too many people are compliant, and complacent in thinking the government knows what it’s doing.
- This episode is showing us that personal freedom must not be taken for granted.
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.