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
…and it’s even more useful if we align the data – so I’ve brought the admissions data forward by 8 days, and the deaths by 20 days to (roughly) align them with cases. (feel free to tell me I’ve got the lags wrong – all suggestions welcome, particularly with data). 4/10
Here’s the 85+ on that basis: it looks like admissions are tracking cases fairly closely, until the last week or so when they’ve pulled up a bit. Deaths, on the other hand, seem to be coming down faster and earlier than cases or hospital admissions. 5/10
And here’s the 65-84, with a similar-ish pattern. Again, hospitalisations are tracking cases pretty closely, although without the recent pull-up in this group. And deaths are showing more benefit, ahead of cases and admissions. 6/10
One obvious question is: why are we not seeing more overall benefit? Surely the 85+ were nearly all vaccinated by 7th Feb, so by end of Feb we should be seeing 80%+ protection vs. hospitalisation and death? Well, we don’t have data for deaths coming out that far yet, 7/10
…and I also believe that the case data is being distorted by the weaker effect of lockdown on older age groups – which may be pushing up the over-80s cases (as a % of the total) as it did in Lockdown 2 in November, thereby diluting the vaccine effect. 8/n
Still, that doesn’t really explain why we aren’t seeing bigger benefits in hospital admissions. Others have suggested reasons for this e.g. it could be that when hospitals were full in January, there was greater rationing of healthcare for the over-85s than for other groups, 9/n
…which has then unwound during Feb/March, creating an apparent (relative) rise in hospital admissions in that group. Alternatively, proportionately more infections could be being acquired in hospital, which might create a similar effect. Other ideas very welcome. /end
@ThatRyanChap this may be interesting - I've changed the presentation a bit since you last saw this, adjusting for the usual time lags, which gives a closer fit between cases and admissions - but there's still that uplift in the 85+ to explain
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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
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
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
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
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
(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
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)
A few links to previous threads here for anyone who's wondering what I'm talking about:
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
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