COVID thoughts from London as back to school and work looms for England. TL;DR Vaccines work; Delta is our hardest test; the real question is how fast can we vaccinate the planet but many developed countries are running serious, largely avoidable, risks now and coming months
Context: I am genetics and computational biology expert. I know experts in viral genomics, infectious disease epidemiology, clinical trials and immunology. I have some COIs: I am a long standing consultat to Oxford Nanopore and was on the Ox/Az vaccine trial.
Reminder: SARS-CoV-2 is a respiratory virus, distributed by both droplets and floating aerosols, which sometimes causes a delibating disease, COVID, mainly in older and overweight people. If left unchecked, many people would die and many more suffer long term health issues.
Thankfully a broad range of effective vaccines have been developed which dramatically (~20 to 50 fold) reduce the rate of getting the disease, and somewhat, depending on virus variant, reduce infection and onward transmission. These have transformed the pandemic.
The virus continues to evolve, and the most recent biologically different variant, "Delta" both transmits extremely well compared to earlier variants and also has less of an impact from vaccination on both infection and transmission. This has made the pandemic harder for all.
Given the power of these vaccines, the single most important thing is to have everyone on the planet vaccinated, starting with the most at risk (age main stratifier) and most exposed/transmission risk (health care workers).
This has been largely done in the developed world, with notable pockets and complications for completing vaccination (more later on this), and some questions around the age at which to stop. Broadly the developed world is, or should be, in far better place.
This step change in the impact of the virus on health via vaccination is unlikely to occur again in the short to mid-term. Leaving aside the complication of boosters (again, I will return to this later), developed countries are now transitioning to a new normal.
Before I give my view on the developed world landscape, I must stress that this step change has not been reached worldwide. This is the biggest change we can make; for equity; for removing human suffering; for our selfish health (preventing new variants) and economic reasons.
Vaccinating the world should be our #1 global priority.
Turning to the developed world, a key aspect which I think is hard to pick up in overall tables and rankings is the importance of vaccination reach by age (and other risk variables). We really want the risk-weighted unvaccinated numbers in each country.
Flo Débarre @flodebarre and others on twitter have been making accessible visualisations of this for the countries that provide age-stratified vaccination numbers. For example, here is France compared to England. Colours are vaccinated - grey unvaccinated Image
In this case France and England have overall similar proportions of vaccinated individuals, but France is running a higher risk with more older unvaccinated. These are the hard miles of vaccination of programs to close out the last 15, 10, 5% of people.
France might be running a somewhat higher risk than the UK but the developed country running the biggest risk is the US, with both some communities (eg, African American) coming forward less to be vaccinated and others being adamantly against vaccination.
This large gap in vaccination numbers is in my view why the US South at the moment is having such a horrible 4th wave, and this is likely to repeat throughout all areas with significant numbers of unvaccinated, at risk individuals.
Delta has made this far more complex because Delta's transmission is far less blunted than Alpha (or other, earlier) variants. This means that a significant number of people who are vaccinated will be infected before there is a large suppression on transmission, indeed >>
<< this easily could be the start of the normal "endemicity" (fancy way of saying living with) of us and SARS-CoV-2, where a combination of waning immunity and new births means it circulates forever, hopefully, due to vaccination, not producing too much serious disease.
Wrapped up in this are questions of waning immunity. This seems low from natural infection but higher from vaccination, in particular Pfzier/BioNTech, seen in English and Israeli data. Israel is a striking example of a country that had suppressed under Alpha but not Delta.
(Please note: Natural infection when not vaccinated carries huge risks of severe disease - if old, of full blown COVID, if younger, of LongCOVID which we are still trying to understand)
This leads you to boosters, in particular for at risk people. Israel has already implemented a booster campaign and it seems to work; the UK is running a RCT on boosters, including smaller doses, which would be great if these work as well as smaller doses (expected).
The reason why is that it is far to easy to be caught up in the developed world concerns when still the main benefit per dose of vaccine comes when at risk unvaccinated, uninfected people get the vaccines - most of these people live in Africa, South America and Asia now.
The main thing here is to improve vaccine production rates (we will not regret having more vaccine production in the mid to long term) and then equitable supply - what the @gavi alliance focuses on.
Across Europe, the countries I know and understand the best, Western Europe is largely looking on course to navigate the next steps; arguably England+Scotland have made big steps back to a new normality; Denmark's flagged transition to living with the virus on September 10th.
Central and Eastern Europe, which in many places had a very hard 2020 winter still have some large vaccination gaps (far far bigger than the French example above) and will need to plug those as more people come inside during the winter.
The new normal is still a bit unclear; there are low impact transmission preventions, probably #1 good ventilation inside and #2 mask wearing in risky transmission situations which we need to get used to for a longer time.
We need to have good testing for a variety of viruses, SARS-CoV-2 and couple this to genomics, and then international data sharing (something which @emblebi, which I am a director of, facilitates along side other partners worldwide).
But above all, for the next 6 to 12 months we need to vaccinate the world - at the very least, the at risk of severe disease portion of the world. Everything else is minor compared to our progress on this.

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More from @ewanbirney

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
5 Sep
COVID thoughts from London, after a yesterday's day of slow cricket; TL;DR - the pandemic is reasonably predictable except for human behaviour on contacts; Europe will be likely navigating a complex winter; US (still) needs to vaccinate; The world needs more vaccines.
Context: I am an expert in genetics and computational biology. I know experts in viral genomics, infectious epidemiology, immunology and clinical trials. I have some COIs - I am a longestablished consultant to Oxford Nanopore and was on the Ox/Az vaccine trial.
Reminder: SARS-CoV-2 is a respiratory human virus where a subset of people infected get a horrible disease, COVID, often leading to death. Left unchecked many people would die and healthcare systems would have overflowed.
Read 25 tweets
8 Aug
Dear journalists / editors covering COVID / this delta wave. Some of you are ... great (genuinely) - its not easy out there crafting a path thru information, speculation+ crankiness. But others... time to up your game. Here are some rookie mistakes in describing what is going on:
1. Please please stop with the % vaccinated in hospital. This is genuinely a meaningless statistic. It is just bonkers wrong to quote it. Trivially if a population is 100% vaccinated then 100% of the people in that population's hospital will be vaccinated.
What you want is something surprisingly tricky to calculate; the counterfactual of how many people should be in hospital if no vaccine. Thankfully there is an easy way of doing this which is referring back to the Alpha wave (wave 2/3 depending on counting system in each country)
Read 17 tweets
5 Aug
Had another moment of "well, yes, but people *are* different" and "you geneticists use continental groups in your analysis" as we skirted around discussions of ethnicity / race in health impacts. TL;DR Partially correct but the underlying mindset that ethnicity=genetics is wrong
Let's deal with the correct things first. Yes, people are different partly (sometimes mainly) due to genetics. Visibly, eg height, weight, hair colour, skin colour, smoking habits + invisibly, eg cholesterol levels, heart trabeculation levels, likelihood of getting breast cancer
Some of these visible differences we integrate into the gestalt assessment of ourselves and others for ethnicity, as represented by self identified ethnicity boxes which people tick, eg "Black British, White English, British Indian, British xxx", gloriously variable by society
Read 26 tweets
4 Aug
Ah. I love the smell of freshly baked data/analysis, well controlled false discovery rate (QQ plot) and just ... so many results. Which of the thousands of beautiful stars in the sky does one pull out to discuss? Biology is so endless and wonderful in its detail...
... to alter (butcher?) a passage from a far far wiser and more thoughtful man than me....
It is interesting to contemplate a tangled set of genetic results, associated to both well known genes and entirely anonymous regions of the genome, stories from physiology of old and hints of new insights, and to reflect ...
Read 5 tweets

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