COVID thoughts on an autumnal London day. TL;DR the developed vaccinated world has some tricky navigation, but is probably entering some endemic-ish state; the developed unvaccinated world is a bit mad and needs help; the rest of the world needs vaccines.
Context: I am an expert in genetics/genomics and computational biology. I know experts in infectious epidemiology, viral genomics, clinical trials and immunology. I have COIs; I am long established consultant to Oxford Nanopore and I was on the Ox/Az clinical trial.
Reminder: SARS-CoV-2 is an airborne virus. The latest variant, now globally dominant, transmits rapidly and all variants causes a horrible disease in subset of people - older, more overweight, male. Left unchecked many people would die and healthcare systems overwhelmed.
Its global reach, fast transmission and presence in a number of animal resevoirs now means that SARS-CoV-2 has joined the other 4 human coronaviruses as endemic (ever present) viruses in humans. The question is how best to manage its transmission and disease causing properties.
Thankfully a number of vaccines (still growing! go human ingenuity!) primes the human immune system to both recognise SARS-CoV-2 and also not to overreact to an infection. Much of the COVID disease is an auto-immune like overreaction to infection, not infection itself per se.
The latest variant (Delta) has less of its transmission blunted by vaccines. This means that a large portion of double vaxd people in each population will have an infection, but a far far smaller percentage will end up in hospital due to vaccination. This is a very good thing.
Developed countries; the majority of Western Europe, some of Eastern Europe, largely speaking Japan have pretty high to very high vaccination levels. An exemplar is Denmark with high vaccination and now COVID is no longer "a disease of societal concern".
Working out the long term rhythm of this virus is complex; how much more infection "has" to happen on top of vax? How strong is the waning of the vaccination (expected, but fiddly to understand)? What general improvements to pushing down airborne infections should one have?
Booster vaccines on top of second doses for at risk people look sensible (it is harder than it looks to fully know) and vaccinating 12-15 also looks sensible (very frustratingly the UK agonised over this, missing a chance to do at least some of it in the summer).
Both modellers and health professionals are eyeing up the European winter with concern - we missed an entire influenza season last year due to generic anti-airborne disease measures (most extreme: lockdowns), but the childhood RSV has popped back up.
(A good UK account here by @BristOliver on what the UK's case levels might be, and the uncertainity of all the steps )
Germany, the best performing large country in Europe in COVID, is at the bottom of the league of vaccination - it is no way US like scary, but enough I think to keep German modellers and health professionals up at night. An issue is reporting timeliness (vaxs, cases).
Away from Europe (which I know best), the uneven vaccination plan in the US has had awful Delta wave consequences, and I am not sure it is out of it yet, although thankfully cases and hospitalisations are falling.
The utter madness of watching anti-vaxxer advocate for non-working drugs as a cure for COVID and not the vaccine honestly makes me want to .... weep that this sort of social dysfunction can take hold with such far reaching consequences.
One way to think about the US is that the US probably has to go through a similar "exit to endemicity" that UK/France/Germany is somewhere on the path of, *plus* process all the unvaccinated at risk individuals being infected which is (still) substantial.
Eastern Europe I think is closer to the US than Western Europe, with only partially successful vaccination campaigns. A strong Alpha wave means there is also natural infection but there are still many people at risk there are and proportionally how fragile hospital provision is.
I know even less about the rest of the world, but I know that the most powerful weapon we have - vaccines - is still supply limited. The sooner this is changed the better - for ethical reasons and for economic reasons.
This month I travelled twice on business outside of my home country; next month I will travel more, and I don't mind at all showing vaccination passports, wearing masks etc to enable all this. I think those too will fade but until we're out, helping keep on top of this is good.
School for my children is back; my daughter's class recently navigated a localised outbreak with plenty of testing; LFD testing is routine in this household and many others.
However, it is worth noting what the stable end state is - some sort of endemicity, probably similar to the other coronaviruses where a mix of newborns and waning immunity means SARS-CoV-2, probably the nastiest of now 5 human coronaviruses, will be with us for a very long time.
Ultimately this is not the nastiest pathogen we are grappling with as a species, but it is the new threat, quite horrible enough, with plenty of naive to it people are still around. The most important thing is to get vaccines into those people.

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More from @ewanbirney

19 Sep
In general the response I think to the announcement of a polygenic-risk-score informed embryo selection has been right - one where the science is wrong, the clinical harm/benefit therefore also wrong, and one where ethical/societal considerations have to be folded in. However...
There are some people who say "but even if this is wrong now, it might not in the future" (true) and also "if genetics works, then this should work" often with some handwaving towards farm animal genetics/breeding/selection. In this twitter thread I'd like to tackle this.
(Context: I am a geneticist/genomicist. My two favourite organisms to study humans and Japanese rice paddy fish. I'm on the experiments/practical data science side, but have a pretty good understanding of the theory/stats side, partly because I've coded it myself/in my group)
Read 23 tweets
18 Sep
So depressing rereading this thread of the first embryo selection by broad genomic profiling from healthy donors in the US
A reminder; in the UK this process would clearly fall under HFEA, and applications to do this would almost certainly be rejected on ethical / societal grounds, on clinical harm to benefit and underlying scientific validity
I’m very positive about the use of genomics in healthcare - many diverse uses and its growing - but I am firmly against this use on ethics, clinical (I’m not an expert) and science (I am an expert). Blogged on this in 2019 ewanbirney.com/2019/05/why-em…
Read 4 tweets
17 Sep
I think the imperial weights thing in the UK is silly (deeply silly) but I do think there was more method in "12" units (and for that matter, 60). 12 is a nice number for division (halves, thirds, quarters, sixths) and then the next nice number for division is 60 (fifths).
Of course the pounds to stone (14!) and then madness of Guineas (I still don't really understand) doesn't fit this. On historical numerology, I was reminded of the arcane voting system for the Dodge in Venice that involves 11, 13s and 17s as supposed "hard to game" prime numbers
As well as the measuring unit changing depending on what you were measuring (this is another moment of deep madness) I think this use of effectively base 12 might be more about early medieaval maths and plenty of mental arithmetic.
Read 4 tweets
17 Sep
After a great workshop in Paris (and hopefully, testing being ok, I will be returning next week) I've been thinking about my travel in the new normal, thinking about green (lowering carbon)
This has been informed by conversations with colleagues such as @embl's green officer, @BrenRouseHD, faculty colleagues such as @Alexbateman1, @PaulFlicek and Deltev Arendt (many thanks); these are currently my thoughts on this (insight from colleagues; missteps from me!)
First off pre-pandmic science travel was useful but often mad; flying for single meetings (sometimes in windowless rooms) with fast turn arounds. Not only was it carbon expensive but it was also bad for family life and just plain health.
Read 16 tweets
10 Sep
As we enter yet another period of COVID uncertainity over outcomes (due mainly to human behaviour - what does "baseline/new normal" contacts look like in an European Autumn/Winter) a reminder about models. There are at least 3 different types; explanatory, forecast and scenario.
Explanatory - usually retrospective data to fit an understanding of the world (say infection->hospitalistion/not->death/discharge) for time series. Examples: excess deaths attributable to COVID, vaccine efficacy models and biological properties of variants.
Forecast - fit an up to date time series to understand outcomes in the near future, sometimes just to understand "now" (hence "nowcasting"). Examples: R rate and near time extrapolation; hospitalisation capacity near term management (often not public).
Read 8 tweets
9 Sep
My annual reminder; if you propose doing large scale data gathering and analysis, just a *one sentence* power calculation, or "we have confidence this approach can provide robust results due to similar work of XXX in system YYY with similar sample sizes".
Why is this important in a grant? As a reviewer wont be able to fully check your power calculation (usually) but I do want to see that you are honest with *yourself* about whether the stats are going to work out. Too few samples, expected weak effects => it's never going to work
If your power calculation (which will always be pulling numbers out of the air for effect size etc; such is science) says its very unlikely you will find a credible result then... you need to reset your goals.
Read 6 tweets

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