Lots of people asking: what does your model say about the delayed vaccine schedule? Can we still unlock on the planned dates?? So here goes with an emergency model update. Summary: don’t panic, it will be OK. 1/n
So just a reminder of my current model ‘base case’ (with R0 for the new variant now set to 4, following comparison with the Warwick/Imperial models). This has a relatively small ‘exit wave’ next winter, with ~10k deaths. 2/n
If we knock 10m doses out of the vaccine schedule in April (reducing my expected 4m per week estimate to 2m per week), we get a slightly stronger and earlier ‘exit wave’. But total deaths after March are not much higher at ~13k. 3/n
In reality I think it’s likely that a small dose of seasonality would knock that wave back into the autumn/winter, and that buys us time to vaccinate some more people (including teenagers) – and the exit wave is removed. 4/n
So that’s no big problem, and no reason to delay implementation of the roadmap on its current schedule – although it may make acceleration of the schedule less likely, as we’ve used up a lot of the ‘slack’ or contingency that previously existed. 5/n
OK, but what if April isn’t the end of it? What if vaccine supplies continue to be interrupted through May as well? Fine, let’s knock another 10m doses out of our schedule, so that 2m per week continues to early June: 6/n
So that’s maybe more of a problem, we now have an exit wave peaking not much lower than January’s crisis, with a total of ~25k deaths after March. That’s the sort of thing that might get the govt to think about delaying the unlocking roadmap. 7/n
But again, there’s a few ways to deal with this. A mild dose of seasonality, plus vaccinations of teenagers, still kills off the exit wave: 8/n
If you don’t want to rely on seasonality, you could keep some ‘baseline controls’ going over the summer (here we’re talking about TTI, masks, maybe limits on large indoor events). That should be enough to moderate the wave, and bring it inside NHS capacity, with ~11k deaths: 9/n
Or you could note that we also got some good news today from PHE’s summary of vaccine effectiveness, which showed VE of 72% / 85% against infection after 1 dose / 2 doses. I haven’t changed my central case for that yet because it was a study done in 10/n assets.publishing.service.gov.uk/government/upl…
...healthcare workers, who (I think) mostly got Pfizer. So it may not reflect what we get in the whole population, where AZ has been more common. But it’s a possible upside. And the impact would be enough, again, to squash most of the exit wave (~7k deaths) 11/n
So, even with a vaccine drought lasting through April and May, we still get only a moderate exit wave, which could be managed using moderate ‘baseline’ controls – and that’s if it doesn’t get squashed by seasonality, or slightly higher vaccine efficacy than I’ve assumed. 12/n
So in my view there's no reason to get depressed, no reason to abandon the ‘unlocking’ schedule, and every reason to stay positive, be patient, and take the vaccine as soon as it’s offered. We’ll beat this thing in the end. 13/n

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More from @JamesWard73

16 Mar
As an addendum to this earlier post, some have asked whether similar analysis is available for hospitalisations and deaths, and if so, does it show the same pattern? Happily, I looked at this at the weekend, and the answer is: yes and no. 1/10
To start with, a quick note on methods. To compare cases, deaths and hospitalisations on the same chart we are constrained to use age groups for which hospital data is readily available i.e. 18-64, 65-84 and 85+. So I’ve used the (mostly unvaccinated) 18-64 group... 2/10
… as a benchmark for the other two groups, creating deviation charts similar to my earlier ones for cases. See below for the new charts for cases, admissions and deaths. But it will be more useful to compare the different data for the same age group on the same chart 3/10 ImageImageImage
Read 11 tweets
15 Mar
Big cause to celebrate in my deviation graphs this evening: over-80s cases have fallen to *half* their January rate, over and above the effects of lockdown on all age groups. I think we can say confidently that vaccines have been the major driver of that additional fall. 1/10 Image
Another way of looking at this: in the second half of January, before vaccination effects started to bite, over-80s consistently accounted for 5.8% of total covid cases. In the 7 days to 12th March, they averaged 2.9% i.e. half their previous value. 2/10
As regular readers will know, there are reasons to believe that the actual vaccine effect could be larger than that 50% fall e.g. due to higher-risk behaviour by those who have been vaccinated, and due to the weaker impact of lockdown on cases in the over-80s. 3/10
Read 10 tweets
3 Mar
Another quick ‘model update’ thread: it’s good news on vaccine uptake, but I also take a look at the Warwick & Imperial models, and explore a scenario with higher R0 that generates a (small-ish) fourth wave next winter. 1/n
Starting with the good news, the real-life experience and polling data on vaccine update keeps getting better, so I’ve updated my model to reflect this: now assuming 95% take-up in all high-risk categories (JCVI 1-9) and 90% in other adults. 2/n
(note I’m still assuming 5% dropout on the second dose, which may be wrong – I’d welcome any insights or links to data on how this is going – but to be honest, it’s not that material to the outcomes) 3/n
Read 18 tweets
28 Feb
I think we can be confident now that cases in the 70-74 age group are on their way down to join their friends in 75-79 and 80+ (maybe not falling quite as quickly as 75-79 did - but there's more in the 70-74s so it will take a bit longer to vaccinate them) 1/5 Image
(also noting that 70-74s are in category 4 alongside the clinically extremely vulnerable, a total of ~4.4m people which is nearly double the ~2.3m in category 3, which was just the 75-79s) 2/5
Looking back at the 80+ in more detail, there's no real "new news" here - all progressing to plan 3/5 Image
Read 5 tweets
25 Feb
Model Update Klaxon: the good thing about publishing model results is that everyone tells me why they think the model is wrong – mostly constructively, and quite often I agree with them. So I’ve changed a few things, and it’s really good news. (thread)
Most of the updates today are to do with children, which hasn’t been a big focus of my modelling, as I was much more worried about what was going on with the over-50s. But it’s starting to become more relevant as we begin to ‘flirt’ with the herd immunity threshold (HIT). 3/n
Read 18 tweets
25 Feb
Although they don't change much day-to-day, I never get bored looking at these charts, because of the positive message behind them. and is that the first sign of the 70-74 line accelerating downwards? (just at the right time, 3 weeks after the peak vaccinations started) 1/n
and here's more boring data, with the sub-groups of 80+ all now consistently showing case rates (as a % of the all-ages total) >25% lower than they were in late January 2/n
some have asked me: why is the deviation not larger, when we know (from PHE/PHS published data) that the vaccines are more than 25% effective, and take-up has been nearly 100% in these age groups? And I think the answer is: 3/n
Read 5 tweets

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