The little Stalins who threw 65 million Brits under house arrest last year put their little heads together and have determined that their unprecedented power grab did an incredible amount of good.

In fact, the only thing they could find to fault themselves with was to not have grabbed all that power for themselves e-a-r-l-i-e-r, which would have done even more good:

The UK’s failure to do more to stop Covid spreading early in the pandemic was one of the country’s worst public health failures, a report by MPs says.

The government approach – backed by its scientists – was to try to manage the situation and in effect achieve herd immunity by infection, it said.

This led to a delay in introducing the first lockdown, costing thousands of lives, the MPs found.

The 150-page document, Coronavirus: Lessons learned to date, is from the Health and Social Care Committee and the Science and Technology Committee, and MPs from all parties.

If only Stalinism had come earlier! Thousands of lives more could have been saved!

This is expected but shameless revisionism. Actually, there is no evidence that British lockdown did anything. British deaths peaked on April 8th which means that infections had already peaked and were trending down *before* the lockdown was ever announced. 

If it can not be shown that lockdown turned the infection rates around, it certainly can not be shown that an earlier lockdown would have turned them around earlier.

And since it can not be shown that lockdown affected the infection curve at all, the only evidence-based conclusion that can be made is that it should have never been decreed at all.

Of course, that would have meant that the politico scum erred in grabbing and exercising power, rather than in not doing so sooner. Guess which works better for them.

None of this is new, Oxford guy, April 2020:

UKs Coronavirus Crisis Peaked Before Lockdown, Expert Argues Draconian Measures Unnecessary

 A leading expert at the University of Oxford has argued the peak was actually about a month ago, a week before lockdown started on March 23, and that the draconian measures people are now living with were unnecessary.

Professor Carl Heneghan claims data shows infection rates halved after the Government launched a public information campaign on March 16 urging people to wash their hands and keep two metres (6’6″) away from others.

He said ministers ‘lost sight’ of the evidence and rushed into a nationwide quarantine six days later after being instructed by scientific advisers who he claims have been ‘consistently wrong’ during the crisis.

Professor Heneghan hailed Sweden – which has not enforced a lockdown despite fierce criticism – for ‘holding its nerve’ and avoiding a ‘doomsday scenario’. The country has recorded just 392 new patients and 40 deaths today, approximately 10 per cent of the UK’s figures. Britain’s diagnoses have not been announced yet.

In separate research, the Oxford professor said he estimates that the true death rate among people who catch the virus is between 0.1 and 0.36 per cent, considerably lower than the 13 per cent currently playing out in the UK.

Professor Sir David Spiegelhalter, from the University of Cambridge, said: ‘This clearly shows we are in a steadily, but rather slowly, improving position since the peak of deaths 12 days ago on April 8th. 

‘But, judging from the experience in Italy, this could be a lengthy process.’

Professor Heneghan, who also works as a GP, told MailOnline: ‘The peak of deaths occurred on April 8, and if you understand that then you work backwards to find the peak of infections. That would be 21 days before then, right before the point of lockdown.’  

He refers to a delay in the time it takes for an infected person to fall seriously ill and die – three weeks on average.

He claims that if the Government accepts that deaths peaked on April 8, then it must mean that infections were at their highest around three weeks prior.

Data shows the rate of Britons with upper respiratory tract infections dropped from 20 per 100,000 people on March 15 to around 12 per 100,000 just six days later.

The figures do not relate solely to coronavirus but may be a good indicator because so few people were being tested for the deadly infection.

Explaining the logic behind his claim, Professor Heneghan said: ‘The UK Government keeps saying it is using the best science.

‘But it appears to be losing sight of what’s actually going on. We’ve been getting scientific advice that is consistently wrong.

‘It has failed to look at all the data and understand when the peak of infections actually occurred.’

He added: ‘Fifty per cent reductions in infections occurred on March 16, right when hand washing and social distancing was introduced.

‘If you go look at what’s happening in Sweden, they are holding their nerve and they haven’t had doomsday scenario. Our Government has got it completely the wrong way around.’

In Sweden most schools, shops, pubs and restaurants remain open, with the Swedes advised rather than forced to adopt social distancing measures.

There have been 14,777 coronavirus cases in Sweden, giving it a per capita infections rate of 140 per 100,000 people. With a total of 1,580 deaths, the nation has a fatality rate of 15 per 100,000 people.

By comparison, the UK has suffered 120,067 cases and 16,060 deaths, meaning 182 people per 100,000 catch the virus and 24 per 100,000 die from it.

On top of much lower death and infections rates, the virus appears to be wreaking less havoc on its economy compared to the UK.

Less than six per cent of Sweden’s workforce had filed claims for unemployment benefits – wheres a quarter of Britons (1.4 million people) have applied for universal credit.

University of Bristol, May 2020:

UK Covid-19 infection peak may have fallen before lockdown, new analysis shows

Simple statistical models can reliably infer the peak of infections and subsequent deaths from the virus, according to a Bristol statistician.

Professor Simon Wood used simple models with few assumptions, together with Imperial College’s estimate of the distribution of times from disease onset to death for fatal cases, to infer the time course of fatal infections from the subsequent death data.

By simply separating out weekly reporting variability, the long-term death rate profile becomes clear, and its peak can be located with confidence. Using the distribution of times from disease onset to death, it is possible to extend the model to infer the time course of fatal infections required to produce the later deaths.

Because of the wide variability in onset to death times, a quite sharply peaked infection curve produces a death curve that declines only slowly. The inferred infection curve peaks a few days before lockdown, with fatal infections now likely to be occurring at a much-reduced rate.

Professor Wood said: “Effective epidemic management requires sound statistical estimation of the epidemic’s course. This approach offers a substantial improvement on the running average smoothing often presented, without relying on complicated model assumptions. But statistically well-planned direct measurement would be even better.”

The paper is part of Professor Wood’s ongoing research program on smooth statistical regression models, covered in his book on the subject, and implemented in the mgcv package supplied with the R statistical software.

The Bayesian modelling used here also forms part of our third and fourth year undergraduate teaching, particularly in the module ‘Theory of Inference’.