Thank you for all the replies to my thread yesterday on the exit strategy from lockdown – lots of positive and constructive comments, and a few helpful suggestions for additional scenarios or varied assumptions. I’ve done some of the easy ones: (thread)
1)Higher vaccine effectiveness vs. hospitalisation and transmission, responding to the most recent Pfizer data from Israel
2)Lower vaccine take-up in the under-50s / non-vulnerable group
3)Higher starting immunity
4)Stronger seasonality effect
Please note that our starting point for all these sensitivities is my controlled scenario with a moderate “fourth wave” in the summer, based on an opening to near-normality at the end of May. (and yes, I know seasonality might squash that wave – we’ll come to that). Image
Since my thread yesterday, we’ve had a couple of updates on vaccine data from Israel: one suggesting 89% protection vs. transmission after 2 doses:
and the other with even higher numbers, including 99% vs. hospitalisation & death:
On transmission, we already know what higher protection does from the analysis I did yesterday. This was with 75% protection after 2 doses, so if it’s actually 90% that would kill off the fourth wave. But of course this data is Pfizer, we don’t really have a clear view on AZ yet. Image
On protection vs. severe disease, again I did that sensitivity but didn’t show you the graph, so here it is (with 100% protection vs. death & hospitalisation). The point to note here is that although things get better (a smaller fourth wave), this doesn’t completely... Image
... stop people dying or going to hospital, because we still have less than 100% take-up of the vaccine. We need very high take-up AND very high protection vs. severe disease if we want to kill off the fourth wave by this route.
2) Some people with way more public health and/or behavioural psychology experience than me have suggested that my assumption for vaccine take-up in the under-50s population (80% 1st dose/75% 2nd dose) is too high – and they may have a point
So I’ve run a new sensitivity, with only 50%/40% take-up in that group. This is deliberately extreme, hopefully it will be much better. And we get a big fourth wave, exceeding the size of the January (wave 3) peak. So we don’t want that. Image
3) Quite a few people asked what my model assumed for starting levels of immunity – this is ~20% at start of Jan, and ~25% today. Other models (e.g. MRC) have higher figures – e.g. 30% or more today. So let’s see what adding 5% more immunity does: Image
That one slightly surprised me, I thought we’d get a smaller wave – but no, it’s pretty much the same size, just later (in Nov/Dec). Ah, but we have this “near normal” period in the summer, and we’ve escaped that – so if I extend that period we do get a smaller wave: Image
And if I add even more immunity (+10%) that pretty much squashes the fourth wave entirely (with those ongoing near-normal controls) Image
But if I want to squash the 4th wave without any additional controls, I have to add a *lot* more immunity – more like +20% (so starting at ~40% immune in January – which I think we can be pretty confident isn’t the case).
4) One or two people suggested that my seasonality adjustments, with summer R ~80% or 67% of winter R, weren’t strong enough. Apparently – I’m told – other viruses can have seasonal swings in R by factors of 2 of 3. So let’s try that, making summer R ~half its winter value: Image
So we get rid of the 4th wave entirely – good news. I’m not 100% confident in my model in this case however, because R is >1 in the winter months, there’s just hardly any covid around (after a very strong suppression in the summer) for it to work with.
In reality we might have continuing ‘pockets’ of higher infection rates, or infections being seeded from overseas, or just stochastic (random) effects when cases are low, which could create the conditions for a fourth wave to grow in the winter.
Also as a reminder we now have 3 seasonality scenarios (as well as the base case): mild seasonality, which slightly squashes our 4th wave, and pushes it into the late autumn/winter: Image
And moderate seasonality (what I previously called ‘strong’) – which moves the wave even later (into spring 2022) but also makes it larger again. Image
And finally our new “very strong” seasonality scenario with no fourth wave at all. So let’s hope the reality is at one end or the other of that spectrum – I don’t much fancy the middle option (although we can moderate the wave by re-introducing controls on the upswing, if needed)
Overall, I’m slightly more optimistic than I was yesterday, as a result of the vaccine data emerging from Israel. That’s the key thing to watch – and particularly as we start to get real-life data published from studies in the UK, including the AZ vaccine as well. 🤞 /end

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More from @JamesWard73

23 Feb
Just updating the deviation graphs that I posted a few days ago: no major changes in trend, but good to see the cases in 75-79s continuing to head strongly downward under the influence of the vaccine, following the 80+: (short thread) Image
(to be clear on method, these figures are the cases in each age group expressed as a % of the total, and then indexed to 100% on 25th Jan so that we can see the deviation in each group on the same scale) 2/n
here's the chart for each of the subgroups within the 80+, you can see the 85-89s falling furthest, but the 90+ now working to catch up. 3/n Image
Read 7 tweets
23 Feb
Now the kids are in bed, I can focus on updating my model to deal with the many events of today. These include 1) Boris’s plan 2) recent case trends 3) news on vaccine effectiveness vs. serious disease, and vs. transmission. Results below: mostly good news. (thread)
1) Boris’s plan is not very different from some other scenarios we have already looked at – and just a few weeks slower to unlock than our base case. Regular readers will be able to predict that it pushes the “4th wave” peak into the autumn – but no real change to outcomes. Image
Note I’ve assumed that the final unlocking on June 21 goes into a “near normal” state with some continuing social-distancing requirements e.g. masks in crowded spaces, limits on large indoor events, ongoing WFH etc. – which lasts until 31 Dec.
Read 16 tweets
21 Feb
OK, I think I’m ready to call this as a new trend in the 75-79s (cases as a % of total, for England). The timing fits for this to be a vaccine effect; we know vaccination of this group started in earnest from 25th Jan (although some may have had it slightly before then) 1/5 Image
and the deviation is from 9th Feb i.e. 15 days later. Data from Phase 3 trials and from Israel was suggesting a delay of 14-19 days, perhaps longer in the older age groups. This is the link showing over-70s started booking from Monday 25th Jan:… 2/5
And this NHS data shows that 83% of 75-79yos were vaccinated by Sunday 31st Jan – so we should be getting the full effect of that over the next few days of data.…
Read 6 tweets
20 Feb
Since the question of how far, and how fast, we can relax our current lockdown restrictions is very much current, I have updated my “vax & release” model with the latest data. And it’s mostly good news: we should be able to unlock faster than I previously thought, 1/8
returning to near-normality in June, without causing the many tens or hundreds of thousands of further deaths that were predicted by the Warwick and Imperial models. (I’m sure their modelling is much better than mine – it's just their assumptions are out-of-date). 2/8
However, there is a sting in the tail: there is still a strong risk of a further (fourth) wave in the summer or autumn, with maybe another ~20-30k deaths. To avoid that wave causing a peak of hospitalisations that would overwhelm the NHS, it may be necessary to continue 3/8
Read 9 tweets
31 Jan
I've had a lot of positive comments on this theory, and some helpful challenges. The most common of which was: surely a single-day effect wouldn't be big enough to cause the 'twist' in the data that we're seeing in those age groups? So I set out to find out if it was (thread)
This is one of those university / job interview 'order of magnitude' estimation problems. So feel free to disagree with any or all steps on my logic chain, and please explain why - it will help improve / refine (or falsify) the analysis.
So let's focus on the primary-school-age kids as that's where the effect is strongest. We have 3.5m 5-9 year-olds in England. I don't know how many were in school on 4th Jan - we know some regions (London / Kent etc.) didn't go back, and a lot of schools had INSET days etc
Read 19 tweets
31 Jan
I have updated my analysis of potential vaccine effects in over-80s cases with today’s latest dashboard data. I am increasingly confident that this does show an actual impact of vaccines, for the following reasons: (THREAD)
1) The trend is continuing to follow a clear quadratic curve, as per @BristOliver's prediction
2) The implied rate of rate of protection from that curve matches almost exactly with the NHS vaccination data, if you assume a 2-week lag to protection, and a 50% rate of protection from the first dose: both come to ~0.6% of the over-80s age group getting protection per day
Read 16 tweets

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