The study is based on >500,000 positives PCR tests. We test in all 50 US states, but it is not homogeneous. See map 👇
4/ In our initial search, we prioritized sequencing of samples with S gene target failure in PCR tests. As expected, we found B.1.1.7 in many states
The B.1.1.7 sequences were pretty classic. So far, no Eeek (S:E484K) mutation present. Credit to @AineToole for mut name
5/ By estimating the fraction of SGTFs that are B117s from the sequences done, & then by looking at fractions of positives that are SGTF, we estimate % of positives that are B117. And can look trend over time.
Trend is 📈 in US.
6/
To get the most recent numbers, you can check the @my_helix dashboard with the most recent SGTF and positives info. Last numbers from Feb 3. public.tableau.com/profile/helix6…
You will see that Florida is going up pretty fast recently. ~10% of positives are SGTF for Feb 1, 2 and 3.
7/
Based on the 5-day rolling average of % of positives that are B117, we fit logistic growth curves.
So far, curve in the US shows a doubling time of ~10 days. And an increased transmission of 35-45%.
B117 could be dominant at end of March in the US.
8/
We then tried to look if the sequences clustered based on geography (note: not all B.1.1.7s are the same. They all have core defining mutations. But they also have some additional ones).
A few clusters (clades) were seen. A very clear Florida cluster, 2 CA, and 1 GA.
9/
Therefore the most likely is that there were multiple introductions of B.1.1.7 in the US.
Then we could try to look at The Most Recent Common Ancestor (TMRCA). For FL and CA1 clade, the best estimate is that introduction was end of November.
10/
Discussion:
We will watch closely the evolution of % of positives that are B.1.1.7. Up to now, our study shows that B.1.1.7 has an increased growth rate compared to non-B.1.1.7 lineages.
Similar or perhaps slightly lower to what other countries have reported .
11/
If it is increasing slower (in CA or other states), it will be important to understand why.
- due to specific measures to prioritize contact tracing for SGTF positives?
- due to competition with other lineages more infectious
- other?
12/
Credit to everybody involved: see list of authors 👇
In FL, numbers 📈 & following growth curve. As of Feb 4, 5-day moving avg showed that 10% of positives were SGTF.
Based on seq results from Jan 20 & their trend, likely that >90% of these are B117.
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As far as I know, this is not a variant of concern.
In our sequences of SGTF samples, we also see this variant a lot in Florida. Following the fraction B1.1.7/B.1.375 in Florida over time will be informative to assess whether B.1.375 has any impact on transmissibility
Update on @my_helix SARS-CoV-2 variant surveillance program.
Data from testing with n positives & SGTF (S-gene target failure)
Stats on sequences (SGTF & non-SGTF)
Stats on B117
2/
First, the dashboard is still focused on B117. Because B117 is more infectious & had large impact in many UK, Ireland, Denmark...
But, looking for other variants is also super important. covariants.org
=> we are increasing sequencing of random positives. see map
3/ Back to SGTF & B117 analyses. Knowing there is a bias in selection, we estimate % of positives that are B117 by looking at 2 metrics:
- (n SGTF) / (n positives)
- (n B117) / n SGTF sequenced)
And all numbers are from positives with a N-gene Cq < 27.
Update. @my_helix launched a dashboard with our results re virus surveillance
So far, you can check trends in by states for:
- % of SGTF by positives
- Ns & % of B117
Update 🧵 on @my_helix study on the B.1.1.7 variant in the US.
Summary:
- we sequenced 31 samples with S-gene drop out in US
- 4 were B.1.1.7
- 3 from CA, 1 from FL
- Pursuing seq effort with @illumina , & work with @CDCgov
3/
Reminder:
- H69del/V70del variant present in B.1.1.7 likely leads to S gene drop out in RT-PCR assay.
- H69del/V70del is NOT unique to B.1.1.7. Frequent in other clusters (see pic. all of the green is NOT B1.1.7)
Need to sequence to know if S gene drop outs are B.1.1.7.