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Jeffrey Barrett Profile picture
Jeffrey Barrett
@jcbarret
Chief Scientific Officer, Nightingale Health. Formerly led the Covid-19 genomics initiative @sangerinstitute.
6 subscribers
Sep 22, 2022 • 7 tweets • 2 min read
The goofy full name of the latest hot topic for Covid variant nerds, B.1.1.529.5.3.1.1.1.1.1.1, tells us something potentially important about the future evolution of the virus. All those dots mean it is on a deep branch of a branch of a branch... of the family tree. 🧵 This is the first time we've seen variant evolution go so far down one path away from the original 2019 virus: alpha, beta, gamma, delta, omicron were all pretty much unrelated evolutionary events from the same starting point. But all these recent sub-variants build on Omicron.
Feb 22, 2022 • 5 tweets • 2 min read
Interesting pre-print that finds 47 BA.2 re-infections after BA.1, using amazing surveillance infrastructure in 🇩🇰. Although this reminds us that getting #Omicron once doesn't confer total immunity, I think overall this is good news. 🧵 medrxiv.org/content/10.110… First, despite very good record linkage, only 0.1% of the huge number of recent cases in DK are confirmed recent re-infections (they are focusing on re-infection within 2 months, so there will presumably be a lot more if you count any prior infection).
Dec 8, 2021 • 10 tweets • 3 min read
In the past few days it has become clear that #Omicron can spread very quickly through highly vaccinated populations. 🧵with several pieces of evidence on this topic, and some thoughts on what next. Previous experiments predicted Omicron-like mutational complement to substantially evade antibodies (e.g. from vax). That's why we've been nervous since it appeared.
Dec 3, 2021 • 7 tweets • 3 min read
First @UKHSA Tech Briefing of the #Omicron era. A lot of scene setting, as it is very early days (I'd guess there's going to be a bit more info in next week's report, and loads more the week after that). But a few early things I think worth noting: 🧵 Annotated table of defining mutations is quite handy, and runs over six pages (this lineage has a lot of mutations).
Dec 3, 2021 • 5 tweets • 2 min read
I'm not sure who these virologists are, but the ones I hang out with are definitely not working their way to this conclusion. This whole thread is based on a rather enormous misunderstanding of phylogenetics. 🧵 The thread looks at one mutation (del69/70) that's in Omicron, Alpha and some Delta in plots from outbreak.info. It asserts older sequences with del69/70 may have been "misclassified" because "we didn't know about Omicron". But we don't look at one mutation at a time!
Nov 25, 2021 • 11 tweets • 3 min read
Took a look at the spike mutations in B.1.1.529 this evening, and colour coded them (details below)...there is...not much green.🧵 Image First the obviously bad stuff (red): nine mutations seen in previous VOCs. There's a lot of overlap already among VOCs (convergent evolution), but this variant has an unprecedented sampling from mutations previously seen in Alpha, Beta, Gamma and Delta separately.
Oct 19, 2021 • 6 tweets • 2 min read
Proportion of AY.4.2 (now on covid19.sanger.ac.uk) has been steadily increasing in England, which is a pattern that is quite different from other AY lineages. Several of them rose when there was still Alpha to displace, but none has had a consistent advantage vs other Delta. And it has grown all over the place between mid-July (L) and now (R). AY.4 did a similar thing, but it was not displacing other Delta, and given that it hasn't spread through the world, likely just had some epidemiological luck.
Oct 18, 2021 • 8 tweets • 4 min read
Technical pre-print up from me and @theosanderson on why G142D is not the world's most recurrent mutation: medrxiv.org/content/10.110… A short 🧵 with highlights, and a tidbit about AY.4.2 to tempt you to read it. People have noticed that S:G142D seems to appear and disappear on the Delta tree in a very weird fashion. @babarlelephant noted early on that this is due to an issue with the @NetworkArtic V3 primers, one of which is hit by a 6bp deletion in all Delta
Aug 19, 2021 • 11 tweets • 4 min read
Should I be worried about AY.3?

TLDR: No.

Longer answer about this lineage, the challenges of cataloguing the current diversity of #SARSCoV2, the miracle of global open science, and handy questions to ask yourself when you see a new variant report follows in a 🧵. First off, summary and background on AY.3 and its cousins here:
Aug 18, 2021 • 6 tweets • 3 min read
Paper on within-host diversity (credits in Gerry’s tweet) is from the first wave of the pandemic, but the conclusions are timely, as the world wonders how the virus evolved and will evolve. In particular, I think the mutation spectrum is relevant to some interesting questions 🧵 This figure shows relative mutation rate: each colour is a type of mutation like C to A, with the bars showing the context of the bases to the left and right; below the line is the reverse complement (e.g. G to T for blue).Red C>U (C>T in DNA) mutations are by far the most common
Jun 14, 2021 • 5 tweets • 3 min read
Monday always means new data at covid19.sanger.ac.uk, but this week also brings new features! Overall picture should come as no surprise: Delta variant growing in proportion and absolute numbers. In fact, next week is likely to be our highest ever count of one lineage🧵 First new feature is "fade areas by uncertainty", or "nebulosity view", as I like to call it. We fade the colouring of local authorities on proportion view to give a visual hint that you shouldn't over-interpret an area with 100% Delta if it only has a handful of sequences.
Jun 8, 2021 • 11 tweets • 4 min read
The description of genomic analyses in this piece about the spread of the Delta variant in the UK has major inaccuracies, and hindsight bias. 🧵
theguardian.com/commentisfree/… Early on, the author, @chrischirp, notes that Pakistan and Bangladesh were red-listed on 9 April, but India wasn't until 23 April. There is a reasonable criticism to be made here, but it has nothing to do with variants. Cases and % positivity were already on the rise in India
May 31, 2021 • 4 tweets • 2 min read
We've pushed the weekly numbers update (thanks @theosanderson!) at covid19.sanger.ac.uk. As expected, in the most recent 2 week window, B.1.617.2 is the most common lineage in England. Still driven by local concentrations of high case numbers (L cases, R B.1.617.2): A couple of notes on the site. We have updated the text describing ascertainment: we are no longer excluding surge tests, which make up a large fraction of all tests in key areas in recent weeks. I think this provides least biased frequencies now. Feedback welcome.
May 24, 2021 • 16 tweets • 6 min read
It's clear that B.1.617.2 has been growing faster than B.1.1.7 in UK for a few weeks. Key question for policy, not yet fully answered, is how much due to:
1. vaccine efficacy
2. intrinsic transmissibility
3. human epidemiological factors

🧵of my current thoughts on the topic: Prelim. data show vaccines work somewhat less well against symptomatic infection w/B.1.617.2, so this makes a non-zero contribution to its recent growth. Good threads on vaccine efficacy data from PHE: &
May 10, 2021 • 7 tweets • 3 min read
Last week @PHE_uk designated B.1.617.2 a VOC (excellent summary from @kallmemeg below). Today we released another week's worth of surveillance genomes at covid19.sanger.ac.uk, and I'd like to walk through some of the features & findings. 🧵

First, headline result, as reported by others, is that B.1.617.2 has hit 6% in England in our 2-week rolling average (>10% in the most recent week). Other VOCs & VUIs steady.
Apr 22, 2021 • 8 tweets • 3 min read
Tons of new info about B.1.617 in @PHE_uk's latest technical briefing on covid #variants (which are rather excellent if I do say so). A 🧵on some key points. assets.publishing.service.gov.uk/government/upl… First off: what is the "India variant", well, it turns out that there are actually three clades of B.1.617, which have now been termed B.1.617.1, B.1.617.2 and B.1.617.3. All three clades appeared in India, likely descended from a common ancestor there some time ago.
Apr 18, 2021 • 12 tweets • 3 min read
A few thoughts on the B.1.617 variant, first seen in India in late 2020, recently seen in >100 cases in the UK, and very much in the news here. TLDR: we should watch carefully, but I don't think any of our best lines of evidence on variants are yet cause for concern. 🧵 In the "variant era", there are 4 kinds of evidence we can use to evaluate a new variant: (1) how fast it is spreading in different places, (2) pre-existing info about specific mutations it carries, (3) lab experiments (ACE2 binding, Ab evasion, etc), (4) real world vaccine data.
Feb 23, 2021 • 11 tweets • 3 min read
There was a scary story published today in the LA Times about the "California variant" of coronavirus, but the data behind the claims are not yet published. So here's a 🧵about this variant that does have some data in it. 1/N What's claimed in the newspaper? Well, it sounds pretty bad: "it not only spreads more readily than its predecessors, but also evades antibodies generated by COVID-19 vaccines or prior infection and is associated with severe illness and death" 2/N
Jan 8, 2021 • 5 tweets • 3 min read
In the latest @PHE_uk Technical Briefing we see the #b117 variant of concern continues to spread throughout England, get bigger numbers on the secondary attack rate analysis, and see a glimpse of planned virology experiments to come. 🧵assets.publishing.service.gov.uk/government/upl… Using the S-gene target failure (SGTF) as a proxy (details in previous reports, updated in this report) we can see that as of January, #b117 is more than half of new infections almost everywhere in England. Of all TaqPath tests in the UK in the past few days >75% are #b117.
Dec 31, 2020 • 10 tweets • 4 min read
Out today: two academic publications (not yet peer reviewed) that formally test whether the new B.1.1.7 variant is more transmissible. Both conclude yes, about 50% more. 🧵 First, a pre-print led by @erikmvolz and @neil_ferguson at Imperial, which applied a variety of different models using both genome sequence data and the S-gene dropout data I've mentioned before. imperial.ac.uk/mrc-global-inf…
Dec 30, 2020 • 4 tweets • 1 min read
MHRA approval document has some information on the basis for approving Oxford/AZ vaccine. Efficacy numbers are the same (pooled) as from the Lancet paper. assets.publishing.service.gov.uk/government/upl… There's no mention of 1/2 doses, but what's interesting is this table on antibody titres after doses 1 & 2. First of all, some effect after 1 dose, secondly way higher antibodies if second dose is >12 weeks after 1st.