The ten worst Covid data failures

The ten worst Covid data failures

Throughout the pandemic, the government and its scientific advisers have made constant predictions, projections and illustrations regarding the behaviour of Covid-19. Their figures are never revisited as the Covid narrative unfolds, which means we are not given an idea of the error margin. A look back at the figures issued shows that the track record, eventually validated against the facts, is abysmal. This is important because major decisions continue to be taken on the strength of such data. There have been several noteworthy failings so far.

1) Overstating of the number of people who are going to die

This starts with the now-infamous Imperial College London (ICL) ‘Report 9’ that modelled 500,000 deaths if no action was taken at all, and 250,000 deaths if restrictions were not tightened. This set the train of lockdown restrictions in motion. Some argue that Imperial’s modelling may have come true had it not been for lockdown. But this does not explain Sweden. Academics there said its assumptions would mean 85,000 deaths if Sweden did not lock down. It did not – and deaths are just under 6,000.

2) Leaked SAGE papers

Next came a print paper written by SAGE members to support a two-week ‘circuit breaker’, leaked to the press. The reports were striking.‘With no social distancing measures in place from now until January, the virus could potentially spiral out of control and kill 217,000 people, hospitalise 316,000 and infect 20.7 million. But with a strict two-week lockdown the number of deaths could be reduced by 100,000, admissions by 139,000 and infections by 6 million.’

Understandably, this made headlines. But when the lead author was interviewed by the BBC, he said that he wished he ‘hadn’t put these numbers in the study’ because it was an extreme scenario only included ‘for illustration’.