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
So if I haven’t joined @andrew_lilico in declaring the epidemic "over", it's not so much because we disagree majorly on what’s happening, but because I worry that language will be misinterpreted and lead people to think that covid has gone away and won’t impact on our lives. 4/n
Sadly, I don’t think that’s true. But it is true that we’re in a better place than we were this time last year, with high vaccine take-up, life nearly back to normal, hospital admissions declining, and the potential for NHS-overwhelming waves much smaller than it was. 5/n
Of course, we’ve seen cases grow over the last couple of weeks, led by the 10-14s, where rates are currently very high. And there are some signs of a “swimming pool effect” (© @BristOliver) with cases now leaking into their parents’ generation. 6/n
But my sense, confirmed by the model, is that this “schools wave” will burn out fairly quickly. I wouldn’t have chosen this route to adding immunity in younger teens, with vaccines coming along just too late, but it’s unlikely to cause massive waves of hospital admissions. 7/n
I’m also optimistic that the return of students to universities won’t have a big impact. Their vax rates and prior-infection rates are high, and they’re more isolated from older generations than schoolkids. So we might see outbreaks, but I doubt it will go much further. 8/n
So I’d expect hospital admissions to be mostly in decline in October. It’s harder to predict what happens after that, as we need to consider the effects of waning immunity, seasonality and changes to behaviour– as well as booster vaccinations. For that, we need the model. 9/n
I haven’t done a complete model re-fit, but I have updated the model from its last outing (below) with the latest case/admissions data, and a revised vaccination schedule including boosters for JCVI groups 1-9, and single doses for 12-15 year olds. 10/n
I’ve also tweaked my assumptions on immunity waning to match my sense of the latest data (although this is still not settled yet). My central assumption on waning of VE vs. infection is now 5% per month, down from 7% in the previous model iteration. 11/n
With those assumptions, I get the following outputs for hospital admissions in England over the next few months. As before I’ll advise you not to take the figures and dates too literally, this is more about predicting broad “shapes” than specific numbers. 12/n
You can see here the predicted decline in October, and something of a lull during November/December before a resurgence in early 2022. Note this is driven by the combination of waning immunity and seasonality – behaviour is assumed to remain at its current adjusted levels. 13/n
By the standards of 2020 and 2021, the admissions in that early-2022 peak are not immense – around 1000 per day at peak – but if added to a difficult flu season and the existing stress on the NHS, this could still be a very challenging experience for our doctors and nurses. 14/n
And I want to emphasise: there’s a lot of uncertainty still in those projections – that peak could be significantly higher, or lower. Taking the good news first, if boosted immunity wanes much more slowly (as @andrew_croxford assures me that it will!), the peak is lower: 15/n
And we could achieve a similar effect if we chose to continue the booster programme into the non-vulnerable 18-50s, delivering these on the same 2nd dose + 6 month schedule, extending into March 2022. (once again I am skipping over the ethical pros and cons of doing this). 16/n
But on the opposite side, if a fall in cases this autumn were to lead to our behaviour reverting gradually to its pre-pandemic norm over Nov/Dec/Jan, we could see a much stronger resurgence in the early part of 2022. I don’t think this is likely, but I can’t rule it out. 17/n
And if I’ve got my tweak to the waning assumptions wrong, and my earlier estimates of 7% per month waning of VE vs. infection were closer to the mark, then we could see a higher plateau of admissions in late 2021, and a bigger peak in early 2022. 18/n
So while we may be out of the pure epidemic phase, and the risks of catastrophe are massively reduced (barring a new worse-than-Delta variant), we could still see waves of cases/admissions that will feel quite epidemic-y (to coin another phrase) to those on the front line. 19/n
What does this all mean for policy? Well, in the short term, I think not much. We should continue to follow the track of living life in our (slightly adjusted) new-normal world, while keeping a close eye on how the covid stats evolve in the coming weeks and months. 20/n
There’s still a small risk we get a big peak – most likely in Q1 2022 – that would have us reaching for the govt’s “Plan B” of mild restrictions. But my best bet is that won’t be necessary, and while covid isn’t going away, we will be heading to full endemicity during 2022. 21/n
Predicting the dynamics of that longer-term state is a whole new ballgame, and depends on some variables we have little data on (eg. not just waning and boosters, but the severity level of multiple re-infection cycles). So I won’t attempt to do that– at least, not yet. /end

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More from @JamesWard73

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
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
9 Sep
Apologies to those of you who’ve been waiting for a model update: I’ve been slowed down a bit by work, start-of-term chaos with the kids, and by trying to organise an U13 girls rugby team. But it’s finally here in its glorious 25-tweet thread detail. Hope you enjoy…. 1/25
The July iteration of my model did an OK job of predicting (at least in “ballpark” terms) the level of hospital admissions over the last couple of months – in fact it’s almost spot-on right now, albeit maybe in the same way that a stopped clock is correct twice a day. 2/25
But that model won’t be a good guide to what happens over the autumn and winter, because it’s missing two significant drivers: waning immunity, and booster vaccinations. So I’ve upgraded the model to include those factors, and am ready to give you the results. 3/25
Read 25 tweets
9 Sep
I know, I’m meant to be doing that modelling thread (it will come later this evening!). But first I got distracted by today’s release of data from @PHE_uk – thanks to the amazing @kallmemeg and the team there. The main point of interest in today’s report has been …
… the release of data on cases, hospitalisations and deaths split by vaccine status. In particular Table 4 of the report has caused some consternation as it suggests case rates are higher in vaccinated groups than unvaccinated, for age groups 40-79.
There are some real reasons why we might expect vaccine effectiveness to have declined – including the impact of delta, and waning of immunity over time. But there are also a number of potential confounders and distortions here, including:
Read 12 tweets
30 Aug
I spent a bit of time yesterday building immunity waning into the model, which is one of those bits of code I hope no-one ever sees (because it’s a massive hack), but it seems to be working OK so 🤷‍♂️. Now all I need is some numbers to go in the waning rate assumptions! 🧵
And that’s where I could use some help. The way the model works is as follows: as well as the classic compartments for fully susceptible (S) and recovered and immune via prior infection (R), I also have states for immune by vaccination (V) and partially immune (P).
People in state P are able to get infected, and to pass the disease on, but are unable to get severe disease (so won’t be hospitalised, or die). So in terms of waning, I’ve set things up with three different waning processes: R to P, V to P, and P to S, as illustrated below:
Read 8 tweets

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