Rt Hon Lord Lilley

    Lord Lilley: I thank my noble friend. Does he realise that this rebuke from the statistics regulator is unprecedented, as is the unparalleled series of errors, dubious charts, outdated data and failed projections? It would be bad enough if those errors were random, but they all point in the same direction: alarmism justifying a lockdown. It is invariably a symptom of groupthink when sincere people—I have been there myself—become so wedded to a prediction or policy that they uncritically accept evidence that supports it and ignore facts that challenge it. Will he heed the warning of the great Professor Feynman: when you convert even the finest scientists into policy advocates, you risk ending up with what he called cargo cult science? Should we not leave advocacy to politicians and ask scientists for balanced advice?

    Lord Bethell:

    My Lords, we are grateful to the Office for Statistics Regulation for its challenge; its points were perfectly reasonable and we take them on board completely. However, I reject the characterisation made by my noble friend and his suggestion that the modelling is either political or erroneous in some way. I remind him that, in January, the modelling showed that the epidemic in China was considerably larger than anything reported at the time. In February and March, we used data from the “Diamond Princess” and elsewhere to show how the threat of Covid was much larger than had previously been understood. In March, we showed that the epidemic in the UK was doubling every three to four days, allowing us to make the difficult decision to lock down. Throughout the spring, the modelling demonstrated that half the UK had not been infected, as previously thought.

    In mid-September, the modelling showed that we were at the start of a second wave, despite those who said that there was no evidence of it. It also showed that the uptick in cases involving younger people would spread to older adults and, as a result, into healthcare. Most recently, the six-week projections of SPI-M that were produced throughout October, based on contemporary trends, have been remarkably accurate at assessing the trajectory of hospital admissions and deaths.

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