The headlines from today’s case data are concerning, and it’s certainly not great news. But there are some glimmers of hope in the detail by age, so let’s have a dig in. The overview doesn’t look too bad, with case rates stable in the under-40s, and still falling in the 40+ 🧵
But that is a slightly lagged view of what’s going on, and obscures some useful detail. So I’ve built some new graphs which break down each of those lines into 5-year age groups, with no averaging, and using data up to specimen date 9th Nov – NB this date will get revised up.
Here’s the under-20s, to start with – we can see growth re-emerging in the 5-9s and 10-14s, but not so much in the 15-19s. The 0-4s were already bouncing around, close to stability – and that looks to be continuing here.
The difficult question to answer is how high that growth in the 5-9s and 10-14s goes, and for how long. I’m not going to make a confident prediction, other than to note that I’d be very surprised if we returned to the kind of growth rates we saw in mid/late September.
On the other hand, a repeat of the smaller surge we saw in early/mid-October is very possible – but fortunately now starting from a lower base. This is easier to imagine using the raw case data (here for the 10-14s).
Now stepping up the age groups to the young adults, we can see roughly stable cases overall – although the recent declines in the 35-39s have been cut back in the last few days.
That pattern extends into the 40-60s, which also have returned from falling cases to near-stability. My sense is that this is more of a post-half-term back-to-work effect (rather than a sign of more infections from child to parent, which you’d expect to take a few more days)
There is slightly better news in the older adults, where declining cases are continuing – except maybe in the 60-65s who are more impacted by the back-to-work effect, and who mostly haven’t had their boosters yet. It would be good to see that happening soon.
And finally in the elderly, case declines continue – and in fact the rate of decline looks to be continuing to accelerate. Go boosters!
So overall, it feels there’s a good chance that cases in the 60+ will continue to decline, even as we see growth in some of the younger age groups. That’s not ideal (as there will be some inevitable leakage between the swimming pool lanes, and I’d still rather that kids…
…got vaccinated before they were infected). But it's definitely better that way round, and it may mean that the impact on hospitalisation statistics is more muted. We’ve already seen some decent falls in admissions this week, and I’m hoping that will continue.
Finally, the best news today was in the booster vaccinations, which jumped up; while some of that is catch-up from the last 2 days, the weekly run-rate is now over 2m per week in England, which is getting close to the level it needs to be at. /end
When I wrote my thread before Christmas (linked below) I promised you a postscript on the interaction between vaccines and NPIs, so here it is. And it’s good news – the combined effect is more powerful than I expected. 🧵 1/25
Let’s start with what I expected. In an endemic model, with no vaccines, there is essentially a “required” rate of infection which is needed to keep immunity levels topped up at their equilibrium (herd immunity threshold) level. 2/25
NPIs can reduce this equilibrium level, and hence also the required rate of infection – although as we’ve seen in other threads, the % reduction in the infection rate is usually less than the % impact of the NPIs on transmission. 3/25
So Covid Twitter (and Twitter in general) seems to be dying… with just a few limbs still twitching. To be fair I haven’t been helping much this year, having held true to my New Year’s Resolution to spend time talking to my family rather than on Excel and Twitter. 🧵
So many thanks to those (including but not limited to @BristOliver@PaulMainwood@kallmemeg@john_actuary@chrischirp) who have kept things going this far. But I haven’t completely given up the modelling thing, and there’s a couple of new things I’d like to show you.
So for old times’ sake, and as an early Christmas present, here goes with probably my last ever Twitter thread (and yes, I know it would probably work better on Substack, and maybe I should replicate it on Mastodon &/or Post, but just for today, let’s remember Twitter as it was).
@TAH_Sci@i_petersen@karamballes@chrischirp@CathNoakes@MichaelSFuhrer@MichaelPlankNZ I agree our biggest concern right now should be booster take-up in 65+, but I’d be a bit more open to the case for “clean air” interventions. It’s possible that the business case for doing this in some settings actually does stack up, and imo we should be investigating this, …
@TAH_Sci@i_petersen@karamballes@chrischirp@CathNoakes@MichaelSFuhrer@MichaelPlankNZ … while being very realistic about the costs and benefits. If we’re happy to start with a basic model (and then refine it) then there’s really only three things we need to work out: 1) what % of transmission do we expect to be interrupted in the specific settings it is used?
Multiplying 1) and 2) gives us the overall % reduction in transmission. And then we need to convert that into a reduction in medium-term prevalence. @MichaelPlankNZ gives us the formula here:
really nice analysis from @Jean__Fisch here using the SIREN data to imply changing patterns in the amount of protection that previous infection is giving in each wave. A few points to note:
- infection seems to give strong protection through the autumn 2020 and the Alpha wave
- this reduces (through the combined effects of waning, immune escape and impact of vaccinations) for the Delta wave
- and for the first Omicron (BA.1) wave, there appears to be no benefit from prior infection. I don’t believe this is literally true: more likely there was a…
…small benefit but it may be offset by demographic confounders eg those more likely to be exposed in one wave are also more likely to be exposed in the next
- the good news is that the protection recovers in the later Omicron waves, suggesting that BA.1/BA.2 infection does…
I’ve been looking at this question the other way around, but it’s still very gently encouraging I think. The case curve is continuing with exponential growth (straight line on the log plot) for much longer than we would have liked. We might have expected it to curve over by now
…as the effect of growing immunity to the latest variant starts to bring the R number down. We’ve had a couple of false dawns already (what do we call these, they can’t be “dead cat bounces” because we’re still going up… so maybe “live cat slumps”?), but still it keeps rising.
I *think* what’s going on here is not that immunity has suddenly stopped working, but rather that the effect of growing immunity is being offset by something else. The obvious candidate (as explored in Oliver’s thread) is the upwards pressure from continued variant mix changes.
1. From a mathematical perspective, the arrival of new variants is a bit like waning host immunity, and has much the same effect (i.e. immunity gets lower). It arrives in a slightly different way (at the same time for everyone, rather than gradually across the population)
...which will affect the short-term dynamics, and mean that we’re more likely to get new peaks and troughs, rather than settling into a more stable equilibrium. But viewed over periods of several months or years, the impact on total infection rates will be similar.