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.