James Ward Profile picture
Jul 7, 2021 7 tweets 3 min read Read on X
There’s plenty of bad news on the dashboard this evening, with hospitalisations and deaths joining cases in growing by over 40% week-on-week. But is it just me, or does that case curve look like it’s starting to curve over to the right?
Of course, this will be no surprise to anyone who’s been paying attention to the age-stratified growth rates over the last week. And the pattern here continues, with growth rates continuing to fall in the under-30s:
and in the 30-60s:
However the trend in the 60-90s is less good, with (on average) flat growth levels, still too high (c. 50% over 5 days) – and the growth in this group is now higher than in the under-60s. That’s not good news for the trend in admissions and deaths over the next 2-3 weeks
Also please note that we’re currently seeing high levels of late cases being reported. This means that the last 1-2 days of my graphs might be under-estimating growth. I don’t think it will change the direction, but it might just adjust the slope.
If we look at the overall (all ages) growth, there is a clear trend, and it’s possible to get excited: another week or so on that line and we’d be at R=1 (i.e. cases peaking). I think that’s probably too optimistic; the trend looks too strong to be a pure vaccine effect,
… and so there’s probably other factors involved – and there’s also still a lot of variation by age group and by region, all of which makes it hard to call whether growth continues down, finds a new level or bounces back up. But at least it’s going in the right direction. /end

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More from @JamesWard73

Dec 29, 2022
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
Read 26 tweets
Dec 19, 2022
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).
Read 46 tweets
Oct 11, 2022
@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?
@TAH_Sci @i_petersen @karamballes @chrischirp @CathNoakes @MichaelSFuhrer @MichaelPlankNZ 2) what % of overall transmission is accounted for by those specific settings?

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:
Read 9 tweets
Jul 26, 2022
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…
Read 5 tweets
Jun 30, 2022
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.
Read 8 tweets
Jun 14, 2022
This is important from @AdamJKucharski – and consistent with the maths I outlined in threads about endemicity late last year: (which will have been very familiar territory to Adam and other experts in this field). To draw out a couple of key implications:
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.
Read 9 tweets

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