The architect behind Britain’s covid lockdown has denied ever calling for the first national stay-at-home order.
The science behind Britain’s decision to lock down had been set out in a research paper submitted by Professor Neil Ferguson who was the Government’s leading epidemiology adviser, on March 16 2020.
Ferguson sat on the Scientific Advisory Group for Emergencies (SAGE), which had played a central role in advising the Government throughout the pandemic. He now admits that he ‘stepped outside’ his role of Government adviser
Ferguson’s terrifying models warned that some 500,000 Brits would die unless tougher action was taken to curb the spread of the coronavirus.
His ‘predictions’ as the UK’s key covid advisor, led the then prime minister Boris Johnson into adopting draconian restrictions that saw the country told they ‘must stay at home’.
The Mail Online reports: But Professor Ferguson, who quit his role as a SAGE adviser two months after being caught breaking social distancing rules to meet his married lover, today insisted he didn’t tell officials to plunge the country into a lockdown.
He told the UK Covid-19 Inquiry that the situation was ‘a lot more complex’.
The inquiry is in its second module, which is examining core UK decision-making and political governance.
Hugo Keith KC asked: ‘Do you feel that you did confine yourself to the provision of scientific advice, or did you become, despite your best endeavours, irrevocably involved in determination of policy?’
Imperial College London’s Professor Ferguson, nicknamed ‘Professor Lockdown’ for his infamous modelling, said it was a ‘difficult question to answer’.
He said: ‘I know I’m associated very much with a particular policy.
‘But as you’ll be aware from the evidence I’ve given in my statement and statements of evidence, the reality was a lot more complex.
‘I don’t think I stepped over that line to say “we need to do this now”.
‘What I tried to do was at times, which was stepping outside the scientific advisory role, to try and focus people’s minds on what was going to happen and the consequences of current trends.’
The epidemiologist, who today also apologised to the inquiry for breaking lockdown rules himself, drew heavy flak for his team’s modelling on the Covid pandemic.
Their work suggested 500,000 Brits would die if nothing was done to stop the spread of the virus and there would be 250,000 deaths if two-thirds caught Covid.
It spooked then-PM Mr Johnson into lockdown. It saw schools, shops and hospitality close, social distancing come into force and Brits only allowed to exercise outdoors once a day.
Experts largely accepted that the economically-crippling measures were vital to control the spread of the virus, as there was no vaccine to prevent severe illness and stunt hospital admissions at the time.
But other epidemiologists and public health scientists shared ‘grave concerns’ about the collateral damages of such policies on the NHS and other parts of society in future.
The wave ended up being much less severe than Professor Ferguson predicted, leading some to call the modelling ‘totally unreliable’.
Others insist that lockdown is why cases didn’t reach the eye-watering levels set out in Professor Ferguson’s models.
He made other gloomy models throughout the pandemic, and later accepted that some were ‘off’.
The UK has logged 230,000 fatalities that have Covid on the death certificate since the pandemic began. Not all of these will have been caused by the virus.
Some 55,500 were logged during the first three months of the pandemic, official figures show.
Despite his models suggesting the death toll would be much higher, Professor Ferguson told the inquiry that he was initially wary about the idea of imposing Covid curbs, such as closing down schools or full lockdowns — known as non-pharmaceutical interventions (NPIs).
Asked why he did not recommend such measures before mid-March 2020, he said: ‘In part because of my belief that it isn’t the role of scientific advisers to determine policy, but also because I was very conscious of the huge economic and social costs which would be entailed by long-term and intensive use of NPIs.