As Infections Plummet Following ‘Freedom Day’ the Models Predicting Catastrophe are Exposed as Fatally Flawed

As reported positive cases plummet following ‘Freedom Day’ – down to 24,950 across the U.K. on Monday, less than half the peak of 54,674 just nine days earlier – the damage limitation among the doomsters begins.

In the Spectator , Professor Oliver Johnson of Bristol University stepped up this morning to try to explain.

He starts by observing that “for the first time in 18 months, there’s been a fall in cases that can’t be easily explained by a national lockdown”. Yet the Spectator recently published an article by Professor Simon Wood showing that new infections peaked and fell before lockdown on all three occasions in England. Did the editors forget to bring it to Professor Johnson’s attention?

Next, Professor Johnson offers some reasons why it may yet be a false dawn.

Indeed it’s possible that the peak in cases, welcome though it is, could only be a local maximum with further rises to come. The rapid reversal in trajectory (from 40% increases between corresponding days of the week to 40% decreases) seems too sudden to be caused by a rapid gain in immunity. It seems more likely to be due to changes in behaviour, with school holidays, the end of the European Championship football and recent hot weather meaning that infected people have had fewer opportunities to spread the disease.

You could have made a similar argument about Covid peaking in Bolton, one of the first places hit by the Delta variant. There was plenty of talk of local herd immunity there. But it’s worth noticing that those falls were subsequently reversed.

And here’s the risk now: what behaviour gives, behaviour can take away. I don’t think anyone can be certain if and when Covid might start going up again. But Scotland gives us hope that sustained falls may be possible.

So far we haven’t even seen the effect of the July 19th reopening in the data, let alone people following now-deleted advice not to ‘cower’, plus there’s the return to schools and universities to come, seasonal effects coming back in the autumn and so on.

The argument that “what behaviour gives, behaviour can take away” is precisely why the models always predict exit waves. Yet the modellers don’t seem to have noticed that these exit waves never happen. There was no exit wave in the U.K. or Europe in summer 2020, nor in spring 2021 in the U.K. as restrictions were eased, nor in the U.S. as measures were lifted. Yet the myth of the exit wave persists.

Why Professor Johnson thinks the “rapid reversal in trajectory” should be taken as a sign of behaviour change rather than herd immunity is unclear. Rapid reversals are entirely normal in viral outbreaks, whether COVID-19 (visible in the U.K. winter outbreak, among many others around the world) or in seasonal flu outbreaks, which almost always have this pointy shape – clearly not the result of lockdowns or behaviour change. In fact, it is exactly what you would expect herd immunity to look like, especially with an overshoot, as the pool of susceptible people runs out. Conversely, there is no evidence that behaviour change causes this kind of abrupt decline of an outbreak. Can Professor Johnson point to any such evidence?

The recent double peak in Bolton may be a result of the outbreak there having two phases, the first focused on the British Asian communities first infected with the Indian variant and the second spread across the community more broadly. As Professor Johnson notes, the sustained decline in Scotland since the end of June suggests it may continue in England too.

Then there is Professor Johnson’s inconsistency in claiming that the school holidays, which began on July 21st-23rd in England, are reflected in the drop, whereas ‘Freedom Day’, which was July 19th, is not. In fact, the assertion that a reopening seven days ago would not yet be seen in the data is bizarre: the mean incubation period of the virus is four to five days.

In addition, Professor Johnson’s colleague, Professor Philip Thomas, leader of the Bristol modelling team, writing in the Spectator in June, was clear that he did not think the reopening would make a material difference. “The model shows that the virus is growing exponentially already,” he wrote. “The final step on the roadmap out of lockdown makes little difference. We are already mixing about as liberally as we would otherwise do on a full reopening.”

His team predicted “an enormous final wave” in which the virus “would quickly seek out the one-in-three Britons who are still susceptible: mainly the not-yet-vaccinated” and peak in the middle of July (he got that bit right) “at anywhere between two million and four million active infections“. According to the ONS, in the week ending July 17th (which PHE data suggests is the peak), around 741,700 people in England were infected, a long way short of two to four million.

This is more than just a curiosity, to be explained by half-baked explanations about football tournaments and hot weather (the peak by specimen date was July 15th, and there was no obvious change in the weather in the week prior to that).

It fundamentally challenges the validity of the models, Bristol’s as much as those used by SAGE, that keep wrongly predicting mass infection in the absence of restrictions because they mistakenly assume everyone is susceptible and the restrictions are working. This has been evident since at least the peaking of Sweden’s initial wave in spring 2020, and arguably earlier with the evidence from the Diamond Princess cruise ship. But now that infections have plummeted in England as restrictions are eased it is exposed to the world and the lessons must be learned.

The modellers of doom convinced Boris Johnson to delay ‘Freedom Day’ for a whole month because of worries about rising cases, only for the reopening to coincide with a steep drop. There’s a beautiful irony in that, but it’s important that Government ministers now see through the fraud that is being perpetrated against citizens by the flawed Covid modelling and grasp that they do not need to live in fear of this virus.

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