When shaping policy to protect us from Covid-19, the government relies on data from the Office for National Statistics (ONS) to provide the scientific basis for its actions. The weekly ONS coronavirus survey is supposed to be the information gold standard — and in particular it underpinned Boris Johnson's controversial announcement at the end of October to put England back into national lockdown.
No other course of action seemed sensible, given that the ONS survey on 30 October showed the incidence of coronavirus in the community in England had surged from 4.3 per 10,000 people on 3 October to 9.52 on 17 October, the latest date for data then available.
This was a terrifyingly fast doubling rate.
So the advice from the government's chief scientific adviser Patrick Vallance, and chief medical officer Chris Whitty to the PM was unambiguous: lockdown was the only reasonable course of action.
Guess my surprise — indeed shock would better describe it — when I saw in the latest ONS survey, dated 4 December, that the national statistician has downgraded its estimate of coronavirus in England on 17 October to just 4.89 people per 10,000.
And it now says the incidence of coronavirus in England barely increased until after the start of lockdown — and even during lockdown it says the prevalence never got above 6.62 per 10,000 (on 12 November).
Just to be clear, I am not saying national lockdown was a mistake — I don't know whether it was.
What I am saying is that it is hard to make momentous decisions, like whether to go into national lockdown, in a rational way if the data informing those decisions is subject to such massive after-the-event revisions. And just in case you think I have gone mad or am making this stuff up, see the below screenshots of the ONS's data spreadsheets for coronavirus incidence per 10,000 people for 30 October and 4 December. I have highlighted the 17 October rate in both cases.