When Boris Johnson came out to address the nation on 23 March 2020, he locked the country down and said that because of COVID the UK was facing the worst crisis since World War Two.

Not quite, not even close. But a good catchphrase for any aspiring Churchill tribute act.

In terms of excess death, COVID 19 is the worst public health crisis since the flu outbreak in 2018 where 50,000 people died in the UK and on a par with 2013 and 2000 flu outbreaks.

Mr Johnson might be right in one way. The economic damage caused by lockdown may be the worst crisis in the UK since the war.

But we need to be clear that the economic damage was caused by the response to COVID, not COVID itself.

Sweden provides a counter-factual to lockdown. Sweden had no lockdown, a lower death rate, and comes out of this stage of the pandemic with a better economic outcome.

We don’t know what the effects of COVID will be on those who have recovered. Most viruses leave residual health effects on some who recover.

But in terms of death rate COVID-19 is on par with the flu whichever country you look at. The graphs are all the same. Lockdown or no lockdown. If anything the countries that locked down later did worse than those that did not lockdown at all.

That makes sense because the virus is more transmissible indoors than out.

How did the UK score such an own goal? How did the UK get it so wrong?

When you look at how good decisions are taken, two heuristics are useful:

1. Rely on real-time data not modelling predictions.

2. Rely on a diversity of opinion rather than groupthink.

When we set a forecast at work, we look at the data from the past year. We segment the data down into discrete groups, in our case, income streams, and look at data from each group. We then base our forecast for the coming year on what’s happened in the current year.

We don’t base our forecast on what we might think will happen. Our forecasts, like most well-run businesses, have foundations based on factual data not imagined fact.

Forecasting in business is not that hard. It’s a process. Look at the data. Extrapolate out from that.

If Dominic Cummings has one skill he knows the importance of data to decision making.

If you have the time to plough through Mr Cummings’ prolix musings (and I fully accept that your life may be too short) you can see that Mr Cummings makes some good points about the need to visualise data to arrive at better decisions.

Pity he did not take his own advice.

Boris Johnson and Dominic Cummings took the decision to lock down the UK based on Professor Ferguson’s data.

Problem was Professor Ferguson’s forecast and data was about as reliable as Madame Bull-Merde who styles herself as a Romany fortune teller at the end of Clacton Pier.

When the decision to lockdown was taken Professor Ferguson from Imperial College modelled an infection fatality rate of 0.9%, an infected population of 80% and 500,000 deaths from COVID if UK did not lockdown.

Leaving aside the flaws in the code used by Professor Ferguson, which are well documented (google Sue Denim Ferguson’s flawed model), the inputted variables were way out.

We will also have to leave aside Professor Ferguson’s poor track record of forecasting as well (but feel free to google Professor Ferguson foot and mouth, and Swine flu).

It does beg the question as to why super forecaster Cummings relied on Professor Ferguson who has such a terrible track record in forecasting. But hey ho. Let’s move on, perhaps one for the inevitable public enquiry.

Firstly the omissions. Ferguson’s model did not calculate the deaths caused by lock down. Cancelled diagnosis of medical treatment, cancelled treatment could lead to around 50,000 deaths.

When weighing up how many lives could be saved by lockdown should a government not also estimate how many deaths will be caused by lockdown? Professor Ferguson’s model did not input that as an estimate. This seems a basic omission. Negligent? You decide.

Failing to estimate reduced longevity caused by a lockdown induced recession is another omission in the model. Data is available for how recessions impact on longevity.

At the time Professor Ferguson drew up his model in mid to late March there was data available that could have informed his model.

Firstly Professor Ferguson inputted 80% of the population being infected and 500000 dying.

Data was available from The Diamond Princess cruise ship and other infection hotspots that showed that between 20% to 80% of cases of COVID cases were asymptomatic. Asymptomatic cases do not appear to feature in Professor Ferguson’s model.

Secondly, the implied fatality rate of 500,000 people in the UK in Professor Ferguson’s model is contrary to the data that was available to him at the time. On 16 March 2020 Oxford University Centre for Evidence-Based Medicine produced a review of the outbreaks around the world and estimated that the infection fatality rate was 0.27% based on the known data.

That’s quite a big difference to the 0.9% modelled by Professor Ferguson.

So in relying on modelled data rather than real-time data, Professor Ferguson’s model that forecast 500,00 deaths in the UK was pessimistic, by at least a factor of four, possibly a factor of 10, and possibly more if Professor Gupta is right. The model implied the UK annual average death rate of 500,000 deaths per year would double.

Making mistakes in forecasts is understandable and forgivable.

What’s not understandable or forgivable is not listening to other eminent scientists who point out that Professor Ferguson’s model may be flawed and give data and justifications to support that the model is flawed.

As you will see from Cummings blog, (and yes I do realise that having come this far in the piece your life is a few minutes shorter) Cummings is all in favour of red teams, groups of people who challenge consensus and groupthink. Contrarians who come up with arguments against the prevailing consensus, come up with other suggestions, challenge assumptions, throw curveballs.

Pity Cummings did not take his own advice.

Red teams were out there. Eminent scientists were saying that lockdown was inappropriate for the severity of the disease. Here’s Professor Gupta stating that the IFR could be as low as 0.01%.

One such person, a potential red team member, who wrote to Professor Ferguson was Professor Michael Levitt. Levitt as well as being a numbers man is a Nobel prize winner in molecular biology.

Professor Levitt had been inputting the data from the various outbreaks of COVID since January 2020, spending 18 hours a day on this topic.

Here is Professor Levitt in February 2020 stating that the IFR for COVID would be around 0.1 to 0.2%.

Professor Levitt wrote to Professor Ferguson pointing out the model was flawed in March 2020. No response.

Professor Levitt wrote to the Royal Society pointing out the flaws in the model and stating that one month’s worth of deaths would be caused by COVID in the UK, not one year’s. The Royal Society replied but stuck to the UK guns of 500000 deaths.

Here’s Professor Levitt explaining what he did and pointing out that the epidemiologists had closed ranks and had ignored him.

In summary Professor Levitt’s key point was that COVID was linear and not exponential and that herd immunity would be reached at 15 to 20%.

The red team was not allowed into the game. The lockdown only team was the prevailing groupthink.

Cummings ignored his own advice of encouraging red teams.

Here’s CEBM warning of the dangers of groupthink.

A fatal combination of relying on forecast data, not actual data and then group think around defending the flawed forecast led to where we are.

The worst crisis since World War 2.

Not caused by the virus which is about as deadly as flu, but in overreacting to the virus.

The rationale for the lockdown was to preserve capacity in the NHS, to flatten the sombrero.

As it was the peak usage of ICU beds was around 50%.

Sweden shows that the sombrero flattens itself with or without lockdown.

And my previous post shows there is evidence that the date of peak infection in the UK was on or around 16 March 2020, well before lockdown.

You would have thought the UK constitution would have prevented such a mistake.

In the UK there are checks and balances on power.

Parliament keeps an eye on the government.

The media keep an eye on parliament and government.

The judiciary is the referee. If the executive steps over the line, the judiciary can rule it unlawful via judicial review.

The famous balance and separation of powers did not show up. Our constitution failed us, again.

Parliament did not get to scrutinise the Coronavirus Restriction Regulations. Mr Hancock issued them as a statutory instrument. The nation was being imprisoned. Without the nation’s MPs having a say.

The mainstream media have not done their job at questioning whether lockdown was an appropriate policy response to COVID. The groupthink in the media has been to support lockdown.

Even supposedly liberal newspapers like the Guardian who should tolerate and welcome diversity of thought have gone all-in on lockdown. People like Professor Levitt have not been heard to any great extent in their paper.

As the evidence mounts that COVID-19 does not kill as many people as forecast, the blind eye of the media, the government, and parliament is still being turned on the disproportionate policy response of lockdown.

The latest evidence is that T cell response may kill the virus in up to 80% of the population without causing any illness. That makes sense.

Covid-19 is part of the coronavirus family. Children pick up colds, runny noses and coughs regularly. Children’s T cell response is built up via the production of T cells in the Thymus gland. Those T cells kill the virus.

The old have fewer T cells as the gland stops producing the T cells with age. The immune-compromised have limited T cell functionality.

We all know COVID kills the old and the immune-compromised. The virus does not kill in any statistically significant numbers the young or those with working immune systems.

Sure protect the old and the immune vulnerable, that would have been the perfect policy response to the virus. Numbers out of Wuhan in January showed those who died from COVID were predominately old or with other medical conditions.

But locking up the fit and healthy, crushing the economy, condemning cancer and other patients to an early death through lack of available treatment, reducing longevity through a lockdown induced recession. That’s wholly disproportionate to the risks. The misjudged and poorly targeted policy response has caused the worst crisis since WW2 in the UK.

Readers come at me with your criticisms in the comments. What flaws are there in my reasoning?

In the meantime come on Johnson and Cummings, fix what you broke.