A few weeks ago, some asshole with a blog wrote this about the unknown risks of long COVID:

Regarding long COVID, for me, there’s a huge difference between a 0.01% outcome (1 in 10,000) of long COVID in a vaccinated person and a one percent outcome. I’m older GenX, and if the odds of long COVID were in fact 0.01%, then even if I were infected every year, I would still be far more likely to have a serious cardiac event* over the next quarter century than long COVID. If this were the case (we’ll get to that), I would change certain habits. I would likely still mask in work-related settings, the gym, and on mass transit (I like not getting colds, and I really don’t care what strangers think), but things like indoor dining would be far more likely: in the Before Times, I didn’t stop dining out due to influenza**.

On the other hand, if the odds of debilitating long COVID are around one to two percent in vaccinated people, plus or minus, which is what I, as well as former COVID czar Ashish Jha, have estimated, then the risk calculation for a non-immunocompromised person is (or should be) different. At that point, there’s a non-trivial chance of contracting long-term, possibly permanent, disability over a twenty-five year period.

But when you read these and other articles, there are no numbers offered. For four years, most of our COVID-related policy discussions have been based on vibes, instead of data. We wouldn’t accept that for any other policy area: could you imagine discussions about Social Security cuts that concluded “you get fewer benefits”? Well, is that one dollar or one thousand dollars? There’s a difference.

Unbeknownst to me, two days later Katherine Wu wrote a very nice Atlantic piece about all of the things we don’t know about long COVID, including how likely it is to occur in various subpopulations (vaccinated vs. unvaccinated and so on).

While many, perhaps most people, seem to be pretending that there’s no long-term risk at all if you’re vaccinated, an actual public health policy, not the Zients-driven policy we currently have, would assess this. Meanwhile, we still, after all this time, do not have a single instance (that I’m aware of) where a public health or elected official has been pressed on a specific estimate of the likelihood of long COVID.

This is an utter failure of journalism.

Whether we like it or not, policy requires numbers. We must be able to quantify the problem, or we don’t really have a chance to stop it, but it seems that’s not going to happen any time soon, if ever.