First major inquiry into the Covid crisis says the tragic losses in care homes were among the highest in Europe
The report finds that deaths could have been prevented but instead elderly were treated as ‘an afterthought’
Finding is just one among catalogue of failings detailed in the inquiry by the health and science committees
The report found test and trace system which cost Government £37billion was also branded ‘chaotic’ fiasco
The ONS antibody studies suggest that nearly half of 16 and 17 year olds have been previously infected. We don’t know the equivalent figure for 12 to fives but it is likely to be similar. That means the vaccine effect relative to all unvaccinated (previously infected and not) will be drastically lower than the figure used in the modelling paper. In turn, even the 15 minutes of prevented lost schooling will be a significant overestimate.
We write as concerned doctors, nurses, and other allied healthcare professionals with no vested interest in doing so. To the contrary, we face personal risk in relation to our employment for doing so and / or the risk of being personally “smeared” by those who inevitably will not like us speaking out.
Modelling that helped persuade the Government to delay the June 21 reopening was overly pessimistic and the lockdown lifting should “possibly” have gone ahead on time, a government adviser has admitted.
Dr Mike Tildesley, an epidemiologist from Warwick University, said Britain had been in a “much better situation than we thought” when his group released models suggesting third wave deaths could hit 72,000.
As Sarah Knapton has revealed in these pages, the brutal postponement of Freedom Day coincided with the release of a bunch of alarmist models predicting a huge new wave of deaths. The most pessimistic, inevitably from Imperial College, forecast 203,824 deaths over the next year. It did so by assuming just a 77-87 per cent reduction in hospitalisations following two vaccinations, despite the fact that real world data shows two vaccinations to be between 92 per cent (AstraZeneca) and 96 per cent (Pfizer) effective in preventing hospitalisation. That would cut the Imperial forecast of deaths by a gob-smacking 90 per cent to 26,854.
This keeps happening. In April the modellers assumed a 30 per cent effectiveness for the vaccine at preventing the spread of the virus. This was described as “a pessimistic view – but it is plausible, it’s not extreme”, by Professor Graham Medley, chairman of the SPI-M sub-group of Sage. It turns out it was far from plausible. At the end of March the BBC’s favourite modeller, Imperial College’s Neil Ferguson, was forecasting that by June 21, even with “optimistic” assumptions, less than half of Britain would be protected against severe disease by vaccination. The true figure is over 80 per cent.
It’s amazing how often Sweden still crops up in conversations. It didn’t impose tough lockdown, kept primary schools and core economic activities functioning, issued clear guidelines and relied on voluntary social distancing and personal hygiene practices to manage the crisis. For harsh lockdowns to be justified elsewhere, Sweden had to be discredited. Hence the harsh criticisms of Sweden’s approach last year by the New York Times, Newsweek, USA Today, CBS News and others.
But with Sweden’s demonstrable success, goalposts have shifted. Every time it’s mentioned as a counter to Europe’s high Covid-toll lockdown countries, the response now is: ‘But their Nordic neighbours did much better. Look at Denmark’. Let’s ‘interrogate’ this argument.
Do we risk swamping the NHS with Covid-19 cases if the government proceeds with Step 4 on time on June 21st? In the Spring of 2020, there were about 22,000 Covid cases per week admitted to hospital, at the peak.
In January 2021 there were about 29,500 at that peak.
Neither of those occasions produced any British equivalent of the distressing scenes we recently saw in India where hospitals ran out of resources and turned sick people away, with relatives forced to watch their loved-ones die, untreated, in hospital car parks.
The NHS was not swamped, in that sense, on those occasions. And we should not understate how important it was that it was not.
So, the third wave is officially no more. New modelling by SPI-M, the government’s committee on modelling for pandemics, has, at a stroke, eradicated the predicted surge in new infections, hospital admissions and deaths which it had pencilled in for the autumn or winter as a result of lockdown being eased.
…As Philip Thomas explained here on Sunday, Imperial College has also assumed strangely low estimates for the number of people in Britain carrying antibodies. If you are going to use assumptions that are far more pessimistic than real world data suggests, it is small wonder that SPI-M keeps predicting waves and surges that turn out to be wide of the mark. The question is: why are these modelling teams using such negative assumptions?
Professor Neil Ferguson struck an unusually optimistic tone this week. With just one Covid death reported on Monday, and infection levels at an eight-month low in the UK, the architect of the original lockdown said: ‘The data is very encouraging and very much in line with what we expected.’ The first half of that statement is certainly true; the second half much less so.
I won’t have been the only parent concerned by news last week that the Pfizer vaccine may be approved for use on children as early as June and potentially rolled out to school pupils from September. Healthy children are at almost no serious risk from Covid-19 – the recovery rate for this age group has been calculated at over 99.99 per cent. The argument that children should have the vaccine is not based on a belief that they need or benefit from it but on the logic that it would be good for our communities at large if children were jabbed. In short, those advocating it assume that children have an obligation to protect adults.
It’s worth noting that the UK Government has granted immunity from liability for harms to all Covid-19 vaccine manufacturers. Can we really ask children to accept a greater risk than the manufacturers themselves are prepared to live with?
Texas Gov. Greg Abbott announced last week that his state is ending its mask mandate and business capacity limits. While Democrats and many public-health officials denounced the move, ample data now exist to demonstrate that the benefits of stringent measures aren’t worth the costs.
…We have since learned that the virus never spreads exponentially for very long, even without stringent restrictions. The epidemic always recedes well before herd immunity has been reached.
THE Government has been accused of over-relying on pandemic modelling and risking “catastrophe by computer”. Last week Boris Johnson published a cautious ‘roadmap‘ to normality after scientists warned him there could be 91,000 extra deaths if he scrapped curbs completely at the end of April.
These figures were based on Imperial College modelling that has since been challenged by Mark Harper, deputy chair of the Covid Recovery Group of MPs. He argued the model did not account for key factors shown to change the course of the pandemic such as the most up to date evidence on the protective effect of the vaccines as well as the “seasonal effect” as the country moves into summer. Modelling has driven much of the pandemic response. The initial reaction in the UK, the US and other European countries was shaped by the dramatic headlines in March last year, suggesting 550,000 deaths in the UK and 2.2 million in the US if mitigation measures were not put in place.
Some 8.8 million schoolchildren in the UK have experienced severe disruption to their education, with prolonged school closures and national exams cancelled for two consecutive years. School closures have been implemented internationally1 with insufficient evidence for their role in minimising covid-19 transmission and insufficient consideration of the harms to children.
Foot and mouth disease (FMD) is a major threat, not only to countries whose economies rely on agricultural exports, but also to industrialised countries that maintain a healthy domestic livestock industry by eliminating major infectious diseases from their livestock populations. Traditional methods of controlling diseases such as FMD require the rapid detection and slaughter of infected animals, and any susceptible animals with which they may have been in contact, either directly or indirectly. During the 2001 epidemic of FMD in the United Kingdom (UK), this approach was supplemented by a culling policy driven by unvalidated predictive models. The epidemic and its control resulted in the death of approximately ten million animals, public disgust with the magnitude of the slaughter, and political resolve to adopt alternative options, notably including vaccination, to control any future epidemics. The UK experience provides a salutary warning of how models can be abused in the interests of scientiﬁc opportunism.
This is a BMJ Rapid Response letter by Dr Janet Menage, Wales, UK, in response to Covid-19: Social murder, they wrote-elected, unaccountable, and unrepentant, by Kamran Abbasi. You can find the full response in the link below.
From a medical perspective, it was clear early on in the crisis that disregarding clinical acumen in favour of blind obedience to abnormal ventilation measures, reliance on an unsuitable laboratory test for diagnosis and management, and abandoning the duty of care to elderly hospitalised patients and those awaiting diagnosis and treatment of serious diseases, would create severe problems down the line.
Doctors who had empirically found effective pharmaceutical remedies and preventative treatments were ignored, or worse, denigrated or silenced. Information regarding helpful dietary supplements was suppressed.
One in five people in England may have had coronavirus, new modelling suggests, equivalent to 12.4 million people, rising to almost one in two in some areas.
It means that across the country as a whole the true number of people infected to date may be five times higher than the total number of known cases according to the government’s dashboard.
In some areas, however, the disparity may be even greater. Parts of London and the south are estimated to have had up to eight times as many cases as have been detected to date.
The analysis, by Edge Health, reveals that the true number of coronavirus infections in England could be as high as 12.4 million, equivalent to 22% of the population, as of 3 January.
- The ‘new strain’ of coronavirus that put London into Tier 4 was down to more computer modelling from Neil Ferguson.
- The government deliberately resorted to fear.
- The damage done to our standing in the world is permanent.
- The government is doing something it should not do and has no justification.
- The whole notion of the mutant strain is completely constructed.
- NERVTAG is full of psychologists who are experts in frightening people.
- If you don’t get angry, this will never go away.
- There is no evidence that this new variant is any more infection that the old one.
- Historically medical beliefs are often wrong.
- Fighting this thing is probably the most important thing we’ve ever done in our lives.
Wearing a used mask could be more dangerous than not wearing one at all when it comes to warding off COVID-19, a new study has found.
They found that wearing a mask “significantly slows down” airflow, reducing a mask’s efficacy and making a person more susceptible to inhaling aerosols into the nose — where SARS-CoV-2 likes to lurk.
“It is natural to think that wearing a mask, no matter new or old, should always be better than nothing. Our results show that this belief is only true for particles larger than 5 micrometers, but not for fine particles smaller than 2.5 micrometers,” said author Jinxiang Xi.
The researchers found that wearing a mask with low (less than 30%) filtration efficiency can be worse than without.
Results While model 1 found that lockdown was the most effective measure in the original 11 countries, model 2 showed that lockdown had little or no benefit as it was typically introduced at a point when the time-varying reproductive number was already very low. Model 3 found that the simple banning of public events was beneficial, while lockdown had no consistent impact. Based on Bayesian metrics, model 2 was better supported by the data than either model 1 or model 3 for both time horizons.
Conclusions Inferences on effects of NPIs are non-robust and highly sensitive to model specification. Claimed benefits of lockdown appear grossly exaggerated.