Some further musings on our work with @carolilucas, @VogelsChantal, @InciYildirim11, @SaadOmer3,
& @VirusesImmunity. I'll start by nerding πŸ€“ out on some of the genetics and end with some thoughts πŸ€” about vaccination strategies (/gasp). (1/22)

One of the 😎 parts of our study is that we used virus isolates (not pseudovirsues) that represent much of the genetic diversity in our region. This allowed us to examine local effects and to dive into the genetic components of πŸ’‰neutralization (2/22)

These are the results that I want to spend some time with as there is a lot to unpack here. I know that I am a bit biased, but this is such a 😎 figure! (3/22)

The spike L452R and E484K mutations have received the most attention as they are associated with many VOC/VOIs and are known to impact neutralization from some antibodies (4/22)
From our panel of viruses, we estimate that L452R and E484K have the greatest negative impact on neutralization following 2x mRNA vaccination πŸ’‰. To my surprise, when considering the mutations independently, L452R > E484K. But of course its more complicated than that. (5/22)
Here the lineages are stacked by least to most reductions on neutralization titers. Even though we estimate that L452R has the single most impact on neutralization, lineages with this mutation are intermediate. This includes Delta (B.1.617.2). (6/22)
Lineages with the E484K mutation are found at the bottom, but also in the middle. This includes one (B.1.526+E484K) that didn't significantly reduce neutralization. So just having a L452R or E484K mutation is not enough to push a virus towards the lower end. (7/22)
Quick aside: I'd like to discuss B.1.526 (Iota) as this lineage is complex. 2 different clades contain SN77N (a+b in neut fig πŸ‘†, orange πŸ‘‡), 1 clade with E484K (c; yellow), & 1 clade with L452R (d; blue). Lineages + E484K were the most closely tracked by public health. (8/22)
With the power of hindsight, I don't really think that B.1.526+E484K was particularly important compared to the other 526s. From the freq plot πŸ‘†, the other versions were stably transmitted along side it. Also, we found that B.1.526+L452R (d) had greater impact on neut. (9/22)
The astute observers probably already saw me slow-play what the 5 isolates with greatest impact on neutralization have in common: E484K + N501Y/T. While I just spent several tweets explaining that we can't over-simply things, this combination is hard to deny. (10/22)
Adding E484K to B.1.1.7 (already with N501Y) moves this lineage from one extreme to the other in neutralization. While this isn't a particularly new finding, it's interesting to see this jump in the context of our large panel of isolates. (11/22)
Finally, we even included a B.1 lineage with E484K + N501T that has yet to be classified into a specific sub-lineage, let alone as a VOC/VOI, and it too is at the lower end of neutralization. The combination of these two sites appear to be quite important in this context. (12/22)
Thus my team will start tracking all viruses with E484K + N501Y/T in Connecticut and report them to the @CDPH, regardless of lineage. Locally, this combination never exceeded 19%, and is now being pushed out by Delta, but it's still important to watch. (13/22)
Another aside: What about L452R + E484K? A search on @DiseaseOutbreak shows that this combination has only been found in 63 of the >2.4 million sequenced viruses. So my guess is that they are antagonistic in terms of virus fitness, and isn't a major worry at this point. (14/22)
So what does this all mean for levels of protection and vaccination strategies? Our preprint, and subsequent twitter threads, have initiated a lot of discussion/speculation on this front. (15/22)

First, our work does NOT imply that natural infection is better than vaccination in terms of neutralization, as some commenters have suggested. And we are certainly not suggesting that people try to get infected as a way to boost their NAbs. (16/22)
What we are saying is that IF NAb titers are directly correlated with protection (which there is probably more to it than that), than a boosted immune response could help increase protection against the variants on the far end of the spectrum (e.g. Beta, Gamma). (17/22)
But real-world data still shows high efficacy to all variants from 2 doses of the mRNA vaccines. This is because, as suggested below, some reduction in neutralization is probably ok. (18/22)

In my mind the problem is that we don't yet know what NAb titers are still effective at (1) preventing infection and (2) preventing disease.

Beta and Gamma may be already pushing those limits for some vaccines. (19/22)
Also, the mRNA vaccines (and most others) are very effective against Delta, which is or will be dominant in most locations. We find that it leads to a low/mid reduction in neut. If that is the most important correlate, then immediate boosters are not likely needed for it. (20/22)
Finally, the **host has a far greater impact on neutralization than the variant**. Individuals with high neutralization to one typically have high neutralization to others, and vice versa. We have saw 2 that didn't produce NAbs to any of the tested viruses. (21/22)
Recap:
- E484K + N501Y/T πŸ“‰πŸ“‰ neutralization
- Delta low/moderate πŸ“‰ neutralization
- Boosting *may* help with Beta, Gamma
- Host >> variant
- Get VACCINATED!

Our study does not say if the CDC/FDA or Pfizer are correct regarding boosters. Way more goes into those decisions. /fin
**Caveat** There are others FAR more knowledgable about vaccines than I am. Please follow our partners @InciYildirim11, @SaadOmer3, & @VirusesImmunity for more coherent thoughts.

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More from @NathanGrubaugh

15 Jul
🧬7/15 Connecticut #SARSCoV2 variant surveillance
@CovidCT | @jacksonlab | @CTDPH | @YaleSPH | @YaleMed

Alpha (B.1.1.7) = 27% (πŸ“ˆ8%)
Delta (B.1.617.2) = 64% (πŸ“ˆ11%)

**Delta is now likely the dominant variant in CT**

short 🧡 | Report πŸ‘‰
covidtrackerct.com/variant-survei…
2/10 Our data combined with the CDC indicates that Delta was ~64% by 6/28 in Connecticut and may have been as high as 80% by 7/6 (remember that sequencing data always has a bit of a lag). Also, the rise in Delta is replacing almost all other variants. Image
3/10 In addition to B.1.617.2, we are also seeing the sub-lineages AY.1, AY.2, and AY.3, which are all classified as Delta. Some AY.1's have K417N and some AY.2's have V70F. AY.3 is defined by mutations outside of spike. The functional differences between these are unknown. Image
Read 10 tweets
1 Jul
🧬7/1 Connecticut #SARSCoV2 variant surveillance
@CovidCT | @jacksonlab | @CTDPH | @YaleSPH | @Yalemed

Alpha (B.1.1.7) = 50% (πŸ“‰9%)
Delta (B.1.617.2) = 13.6% (πŸ“ˆ11%)

short 🧡 | Report πŸ‘‰
covidtrackerct.com/variant-survei…
2/9 Last week when we reported that Delta was only 2.3% I said: "This is probably more of a reflection of noisy data when trying estimate frequencies from a small number of cases", and followed that up with an expectation that we will see Delta πŸ“ˆ.

3/9 This week we are seeing the expected πŸ“ˆ in Delta (B.1.617.2), but the caveat still remains that our estimates are noisy because of the low numbers of sequenced cases (a product of the low numbers of cases, which is a good problem to have πŸ‘)
Read 9 tweets
24 Jun
🧬6/24 Connecticut #SARSCoV2 variant surveillance
@CovidCT | @jacksonlab | @CTDPH | @YaleSPH | @Yalemed | @YNHH

Alpha (B.1.1.7) = 59% (πŸ“ˆ2%)
Gamma (P.1) = 4.5% (πŸ“‰6.4%)
Delta (B.1.617.2) = 2.3% (πŸ“‰4.2%)

short 🧡 | Report πŸ‘‰
covidtrackerct.com/variant-survei…
2/8 In Connecticut, the % of sequenced cases that are the Delta variant (B.1.617.2) decreased in recent weeks. This is probably more of a reflection of noisy data when trying estimate frequencies from a small number of cases vs an actual decline in delta.
3/8 Looking at our neighbors in Massachusetts and New York, delta is 10-20%, so we in Connecticut are probably pretty close to that. My guess is that we'll see a πŸ“ˆ in delta in the coming weeks to reflect the trends of our neighbors.
Read 9 tweets
11 Jun
🧬6/10 Connecticut #SARSCoV2 variant surveillance
@CovidCT | @jacksonlab | @CTDPH | @YaleSPH | @Yalemed | @YNHH

Alpha (B.1.1.7) = 57% (πŸ“‰11%)
Gamma (P.1) = 10.9% (πŸ“ˆ2.7%)
Delta (B.1.617.2) = 6.5% (πŸ“ˆ3.2%)

short 🧡 | Report πŸ‘‰
covidtrackerct.com/variant-survei…
2/7 Gamma (P.1) and Delta (B.1.617.2) continue rising in Connecticut, while Alpha (B.1.1.7) and others decline, following national trends (see next tweet).
3/7 Data from outbreak.info shows that in the US πŸ‡ΊπŸ‡Έ, Delta (B.1.617.2) is πŸ“ˆ exponentially, while Alpha (B.1.1.7) is on the πŸ“‰. Despite this, COVID-19 cases are still dropping (for now).
Read 8 tweets
27 May
🧬5/27 Connecticut #SARSCoV2 variant surveillance
@CovidCT | @jacksonlab | @CTDPH | @YaleSPH | @YaleWestCampus | @YNHH

- Continued πŸ“ˆ of B.1.617.2 (3%) and now B.1.617.1 (2%)
- Sudden πŸ“‰ in % B.1.1.7 (maybe due to small numbers)

short 🧡 | Report πŸ‘‰
covidtrackerct.com/variant-survei…
2/6 We now have 8 cases of B.1.617.2 (5 shown in the 🌲) and 2 of B.1.617.1. To my knowledge, none of these are associated with ✈️. Our phylo 🌲 shows that there are at least 4 independent transmission chains of these viruses, spanning at least 3 counties. Definately one to πŸ‘€
3/6 The πŸ“‰ in B.1.1.7 shown in tweet 1 is probably a combination of noisy data with few cases and the emergence of other lineages. The figure πŸ‘† 1 is from TaqPath SGTF data, which is a week ahead of the sequencing shown πŸ‘‡, where we don't yet see the sudden πŸ“‰.
Read 6 tweets
20 May
🧬 5/20 Connecticut #SARSCoV2 variant surveillance
@CovidCT | @jacksonlab | @CTDPH | @YaleSPH | @YaleWestCampus | @YNHH

- 2nd case of B.1.617.2 in CT
- B.1.1.7 >75% of all cases, but..
- COVID-19 cases lowest since early October πŸ₯³

short 🧡 | Report πŸ‘‰
covidtrackerct.com/variant-survei…
2/5 The second case of B.1.617.2 was from the same county as the first case (Fairfield), but they are unrelated (see tree πŸ‘‡). Neither cases are known to be linked to international travel.
3/5 B.1.1.7 is still πŸ“ˆ frequency not because the lineage is rapidly expanding, but because it is dying out slower than the non-B.1.1.7 lineages. So the total number of B.1.1.7 cases πŸ“‰ by 87% since late March.
Read 7 tweets

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