When Grant Shapps, the Transport Secretary, was asked by Julia Hartley-Brewer on TalkRadio if the cost-benefit analysis would be presented to MPs later in the week, before they vote on another new-variant lockdown, Shapps retorted with a killer answer. Not only has such analysis been done, apparently, but a “huge data dump of a lot of analysis” would be delivered. This great dump, he suggested, could be pored over by MPs and, after their foraging in the dump, they would be super-wise to make a decision.
Shapps’ answer says it all. Government policy, regardless of what it is, can be justified by obfuscation and lots of references to the bigness of the data. He made clear that data analysis would be part of the smoke and mirrors process to make sure that MPs were no wiser at all about the rationale for locking people down from meeting, drinking, eating and shopping before Christmas.
Shapps, apparently, got his big job back in government (after being side-lined by previous administrations) because he was seen to be a good media performer. But his past, littered with get-rich-quick schemes and dodgy pyramid-selling, has been all about saying one thing and meaning something else entirely. Much of his dealings with the media in the past have been about justifying behaviour that was incompatible with high public office.
But being good with the media seems, whatever form this takes, is all. The Shapps approach involves knowing just enough about “data” to be able to evade what the data mean – what story it tells.
However, the arguments against the lockdown-based Covid response of the government have been made very well by scientists and very effective number-crunchers outside of government – notably Ivor Cummins, Carl Heneghan and Michael Yeadon.
Between them, they have meticulously destroyed the arguments for lockdown based on claimed Covid threat (centred around the R number). Instead, they have argued that PCR tests result in high levels of false positives, that the pandemic is probably over (based on reduced hospital admissions and evidence indicating T-cell immunity in a large percentage of the population). They have also made compelling cases indicating that lockdowns just don’t work. Along the way they have used precise and relevant data – not data dumps – to provide evidence for their assertions. But the government ministers responsible for implementing policies that are increasingly seen as damaging can run away from empirical evidence and use arguments that are based, frankly, on mumbo jumbo or just plain obfuscation.
The cost-benefit analysis of lockdown is likely to be complex and is likely to require some considerable evidence. But the result that we are seeking is an answer to this question: Is continued lockdown justified if the result is massive economic destruction, huge curtailment of non-Covid related treatment in hospitals, and significant damage to our civil society – even if a few more people get infected with what is, for most, a mild disease or one that results in no symptoms. The answer cannot be a “huge data dump of a lot of analysis”. That’s just not good enough anymore.