James Ward Profile picture
Nov 13, 2021 9 tweets 3 min read Read on X
Honestly not a big fan of the case trends in the last couple of days. Here’s the overview: with the kids still driving the growth, but other groups also starting to pick up. (and I wouldn’t take too much cope from the flattening on the last day – that will get revised up) 🧵
Looking in more detail at the under-20s, we can see the power coming from the 5-9s, but with 0-4 and 10-14 not far behind, and even 15-19s now back into positive territory (i.e. cases growing)
In the 20-40s, cases now also (gently) growing:
A very consistent trend in the middle-aged groups, with increasing rates of growth:
And we now see 60-64 returning to growth, and 65-69 looking like it will get there soon. We really need to get more boosters in those arms, and fast. Fortunately 70-79s (where booster rates are already high) are looking OK, with cases still declining.
But what’s going on here, with 85-89 and 90+ both back in growth. They've already have good rates of boosters, so is it spreading in the unboosted?
It’s not a big shift (as you can see in the raw case data here for the 85-89), and some of it could just be noise, but it does look like the downward trend has been interrupted. And that’s not great news for hospitalisations next week.
Still, as the bunny says, we should probably wait a few days before jumping to conclusions. I'm going back to watching the rugby now (go England!), but I'll be keeping a close eye on this too over the next few days. /end
sorry, managed to break the thread here:

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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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