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10 Oct, 4 tweets, 2 min read
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
I just think it’s interesting that with a plausible set of assumptions, one feasible outcome is that case rates (and hence hospitalisations & deaths) continue to fluctuate in a narrow range. What –if anything- we choose to do about that is another debate, of course. /end

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More from @JamesWard73

James Ward Profile picture
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
James Ward Profile picture
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
James Ward Profile picture
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
James Ward Profile picture
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
James Ward Profile picture
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
James Ward Profile picture
12 Sep
One of the questions I often get in response to my modelling threads (such as last Thursday’s below) is: what does this imply for levels of hospital occupancy with covid? Unfortunately I don’t have a good model of hospital stay dynamics, but helpfully...
…I know a man who does, and @nicfreeman1209 very generously offered to convert my various scenarios for weekly admissions into a corresponding occupancy forecast. So what follows is very much a collaboration on the analysis, but the policy commentary is all mine.
Essentially, Nic’s model uses the known data for hospital admissions and occupancy to estimate a distribution of how long people stay in hospital with covid – here’s some discussion on an earlier version:
Read 13 tweets

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