What on earth is wrong with our ability to figure when a number is big and when it’s small…

I don’t want to dwell on the direct issues raised by Terry regarding the Oxford/AZ vaccine, but Tom Chivers at Unherd highlights a key problem that mainstream journalism has with basic numbers…

…a simple, but common, way, in which numbers go wrong in the news: the failure to ask “Is this a big number?” After all, 37 people getting sick sounds really bad, on its own. But is it more than we would expect? What do we need to know to understand that?

We need two more numbers: one, how many people have been given the Oxford vaccine; and two, how many blood clots we would expect to see in that many people, if we hadn’t given them the vaccine. Luckily, we know those two numbers fairly well.

About five million people have been given the Ox/AZ vaccine in Europe (about 17 million worldwide, according to AstraZeneca); and about one person in every 1,000 suffers a thrombosis every year.

So you’d expect to see about 5,000 blood clots among the five million recipients of the jab every year — 14 a day, nearly a hundred a week — even if that jab had nothing to do with blood clots whatsoever. Professor Sir David Spiegelhalter, the Cambridge statistician, goes into a bit more detail here if you’re interested.

On that basis, it’s hardly surprising that we might see 37 thromboses over a few weeks of vaccination. In fact, it’s surprising that there aren’t quite a lot more, although that’s probably because a lot of people had blood clots and didn’t associate them with the vaccine.

Asking that simple question — “is this a big number?” — and knowing how to answer it would have saved a lot of bother, for journalists and for policymakers. But it often doesn’t occur to people.

It’s part of a systemic failure to provide context for big number driven stories that would die a death if properly grounded. Indeed we’ve had two generations having big numbers thrown at us as reason we can’t use government to do anything.

Crunching them all and understanding why data flows matter may be boring, may not qualify as clickbait, but it is vital if we are to gain an understanding of how or newly complex world actually works.

An old friend from my few brief years working at the Daily Telegraph, Robert Colville has a pretty straightforward explanation for what worked and what didn’t in the UK government’s fight against Covid…

Something almost no one outside government appreciates is that the British state, like all its modern counterparts, is essentially a collection of databases. Throughout the pandemic, its policy successes have largely come where there are good databases, and its failures where there are not.

The furlough scheme worked because of PAYE. The expansion of universal credit relied on the existing benefits system. The “shielding list” of vulnerable patients was compiled by blending six data sets from NHS Digital.

Good data is also the secret sauce of the vaccination rollout. The jabbers could move seamlessly down the age and risk cohorts, because GPs had the appropriate patient lists. There have still been huge challenges in distributing the vaccines and tracking down the unregistered, but the data gave us an enormous head start.

The central problem with Test and Trace, by contrast, was that it didn’t have a database. When the pandemic hit, Apple and Google developed a joint framework for contact-tracing apps, which would ping you if someone you met later tested positive. But they wouldn’t let your phone share those details with the government — hence Matt Hancock’s abortive attempt to develop a homegrown alternative.

The trackers and tracers therefore had to map out the nation’s social network from a standing start, getting individual contact lists from every person who had tested positive to find out who else needed testing and quarantine. Public Health England even managed to lose 16,000 cases because it built its database with a stone-age version of Microsoft Excel and the file grew too large.

That’s not the only important aspect to the story, though when you think how much trouble generations of techies suffered from the slings and arrows of outraged tabloid columnists, it’s good to see that finally something in the data world worked.

On the Irish situation (which is perplexing to say the least) that Terry has talked about, I leave the final tweet to Ben Tonra, Professor of International Relations at UCD (ie, like myself, not a medic, but who has a moderate ability to count)…

Photo by councilcle is licensed under CC BY-NC-SA