it's a while since I've given you the age breakdown of English cases (sorry, it's been a busy couple of weeks at work and at home). and it's looking OK I think: overall cases are pretty flat, maybe even slightly falling. and the falls continue where it matters most (in 60+) 🧵
digging into the detail, starting with the younger age groups: these now all look fairly stable, maybe just slightly over the peak. (and note I'm being cautious by truncating 3 days on the specimen date series - the next day looks slightly better again, on a sneak peek).
there's still a little bit of growth in the 20-40s, mostly from the 30-40s:
and the 40-60s look fairly stable overall, with (gentle) growth in the 40-50s balancing (gentle) falls in the 50-60s:
the 60-80s continue to fall - although it would be good to see some faster declines in the 60-64s as more boosters take effect:
I never like to see cases in 90+ growing, but I have to keep reminding myself how volatile/noisy that series is. 🤞 that if we can sustain case reductions in the younger ages, that might feed into bigger falls here also (since the older groups tend to be infected by younger)
and if we look at the raw case date for 90+, it doesn't look particularly dramatic / worrying - more just a bit of a plateau.
PS I haven't said much about omicron yet because there isn't much for me to say: others with much greater expertise in viruses and variants have done some helpful threads, which I will continue to RT as I find them. once we get a better handle on omicron's transmission...
...advantage vs. delta, and its likely degree of immune evasion vs. prior infection and vs. vaccines, as well as its severity profile, then it may be possible to say something about its potential impact in the UK. but we're a way from having that data, so I'll wait patiently.
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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.