We don’t know if our model for estimating immigration into the United Kingdom works. It’s a long-standing dataset, produced by the Office for National Statistics – one of the best at what it does in the world. The model measures people entering and leaving the UK, something tracked at ports and airports. It’s a model of high political interest and concern. And despite all of that, we’re still not sure it’s good enough to be classed as a gold-standard ‘national statistic’.
In the modern era, almost any number we ‘know’ – be it population, immigration, unemployment, inflation, or GDP – is actually an estimate produced by complicated statistical modelling.
Coronavirus is no exception. The decisions currently being made by the UK government on our response to the virus, which have potentially seismic impacts, are being informed by advanced modelling.
Given we are dealing with a fast-moving disease, there are few other choices. But models can disagree, as we have seen very publicly: epidemiologists at Imperial College estimated up to 510,000 deaths in the UK if we did not take severe and immediate steps to curtail coronavirus, while theoretical modelling by an Oxford University team suggested potentially less severe scenarios.
And given the huge importance of the decisions being made based on these models, they have gone through very little of the normal scientific scrutiny: the peer review process, field testing, even opening up the working of the model to outside experts.
Neil Ferguson noted last month that Imperial’s coronavirus code is ‘all in my head, completely undocumented. Nobody would be able to use it’. To most of the world, including much of the expert world, the Imperial model is a black box: data goes in and their estimates come out, and we either trust them or we don’t.
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