A bit of a mixed bag in today’s case data. The good news is in children, where the trend of recent days (stalling growth) continues: Image
And if we look into the detail, we can see weekly growth rates heading very slightly negative in all three school-age groups (although that last day will get revised up a bit, it does suggest we’re about at the peak of cases). Image
I note that (as @BristOliver mentions here) there’s a risk that the Immensa problems in the South West are now causing the growth to appear lower than the true underlying trend – so we should watch this closely over the coming days.
But with half term about to start, I’d still expect some actual case reductions in those groups over the next week. If that does happen, I’d hope that case rates in 40-60s (which have been elevated) will also come down, as teens stop infecting their parents to the same extent.
The bad news is in the older age groups, where the 80+ seem to have found a new level, settling at about 10% weekly growth. That’s better than the 40% we had a week or so ago, but anything above zero is too high, as it will inevitably feed through into hospitalisations. Image
So if we want this to come down further, and to work into reducing cases in the 60-80s as well, we still need to get a booster rocket into that booster rollout. We are not out of these woods yet. /end

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More from @JamesWard73

10 Oct
I’m not liking the trend in over-60s case rates much at all – see chart of growth rates below. This will inevitably feed through into hospitalisations and deaths over the coming weeks, so boosters for this age group may be arriving not a moment too soon. 1/4
The more I look at this, the more I think I was wrong to nudge down the waning rates in the last model iteration. If I left the waning for vaccine effectiveness vs. infection at 7% a month (instead of reducing to 5% per month) I got this scenario: 2/4
Interestingly, if I take those assumptions and fit to the very latest data, I get a slightly different projection – which has the odd feature of a long, bumpy plateau through the winter. NB I’m not offering this as a forecast with any sense of confidence; 3/4
Read 4 tweets
3 Oct
Are you ready for Part 2 of the endemic “toy” model thread? I thought so. To pick up the story, we started yesterday (see thread below) with a non-seasonal model, and explored the effects of adding in controls and vaccines. Now we need to explore the impact of seasonality. 1/n
To start with, let’s see what happens if we inject some mild seasonality into the equilibrium model – here with a +10% variation in R during winter, and -10% in summer. (so about 20% overall peak-to-trough variation). With this, we get gentle oscillations in cases: 2/n
Now let’s dial up the seasonality a bit – to 20% either way. Unsurprisingly, the waves get bigger. 3/n
Read 31 tweets
2 Oct
I’m concerned that we haven’t quite got our heads round what the dynamics of the long-term endemic state for covid will feel like, and that some of the intuitions we built up in the epidemic phase won’t age well. I know I struggle with this at times. So, I built a model 😉 1/n
This time it’s just a “toy” model. Which means it’s not designed to forecast the endemic state in an accurate way – we don’t really have the data to do that yet. It’s just designed to illustrate the shapes and patterns that might arise. I hope it helps you, as it did me. 2/n
It’s just a very basic SIR model, for those of you familiar with that, and it covers a single sheet of Excel. In fact you can see it here – there’s more cells further down, but they’re just a copy of the earlier cells, extended further out into time. 3/n
Read 25 tweets
28 Sep
A few people have asked me what I think is going to happen next, so with the combination of a small model update and a bit of intuition and logic, here goes. TL;DR: I’m reasonably optimistic about the next 2-3 months, but a bit more worried about the early part of 2022. 1/n
It is clear that England has moved out of the pure epidemic phase, and into a transition that is neither wholly epidemic, nor full endemicity. The dynamics are becoming more endemic-ish (to borrow @ewanbirney’s phrase in his excellent thread) 2/n
…but that doesn’t mean we’ve entered (or are near) a long-term equilibrium – for one thing, we still have a lot of people who’ve never caught covid, and we’re only just completing the vaccine rollout. And there’s a lot we don’t know yet (e.g. on waning rates & boosters). 3/n
Read 22 tweets
24 Sep
OK, so here’s a question: why are case rates so persistently high in older age groups in the North of England? For simplicity here I’m just looking at the 50+, and using three super-regions: North inc Yorkshire, Midlands & East, and London & South. 1/4
You might think it’s just reflecting case rates in the whole population. But it’s not: look here at the same graph for the under-50s, it has quite a different pattern, with the North very similar to the Midlands through August (and to the South until the last few weeks). 2/4
One possible explanation is that it reflects lower immunity in the older Northern groups – but the vax rates have been good, and if we look at a longer time horizon, there’s not an obvious difference in attack rates (the January peak is lower, but the autumn one was higher). 3/4
Read 4 tweets
20 Sep
A few people have asked how we managed to have such a stable period in England during August, with cases apparently stuck around 25k per day, and R pretty close to 1. After all, case rates in an epidemic tend to go up and down in waves, not stay at roughly the same level. 1/10
One possible answer is that the growing immunity from vaccines and infections (which would normally be expected to pull R and cases down) was being offset by waning of the existing stock of immunity, causing case rates to stabilise in a sort of bumpy plateau. 2/10
If that is the case, then August could be seen as an early glimpse of what endemicity might look like, although I don’t think we’re near to finding a long-term equilibrium, and there are several good reasons why August isn’t a good predictor of what that will look like. 3/10
Read 10 tweets

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