2/
With overall number of cases 📉 quickly => important to look at % of positives that are B1.1.7
AND also the evolution of the absolute number of B1.1.7
Can do this based on Helix numbers,
or by multiplying % from Helix by overall number of cases reported by states and CDC
3/ CA: % of positives that are B117 now ~15-17%
Increase in absolute numbers of B117 is slower (compared to FL).
Still N of B117 is not decreasing, unlike the non-SGTF SARS-CoV-2 variants including B.1.429 & B.1.427 who are decreasing fast.
Note: Y-axis truncated in right 👇
4/ If you are curious about B.1.427 and B.1.429, the 2 variants of interest (NOT variants of concern), aka the 'CA' variant:
% of random (non-SGTF) sequences that are B.1.427 or B.1.429 has been relatively stable (60-70%) since mid-Jan in CA.
& absolute numbers 📉
5/ A few other states now have more than 10% of the positives that are B.1.1.7*
* based on combination of 1) % of positives that are SGTF (S-gene target failure) AND 2) % of SGTF sequenced that are B.1.1.7
Georgia is one example. Now ~20% of positives are B117.
- New dashboard: you can check all lineages now
Random ex: B.1.1.64 in 4 states (note: I don't know anything about this variant). public.tableau.com/profile/helix6…
- SGTF info up to Feb 15
- Seq info up to Jan 30
🧵 with more results
2/
Of the variants of concern, so far we only identified B.1.1.7 (666 times up to Jan 30). No B.1.351 and no P.1
We identified many B.1.429, a variant of interest. It represents about 20% of the sequences we do every day. But sampling is still biased for SGTF
3/
To assess fraction compared to non-SGTF sequenced, you can also get that info from the 2 files on Github with ALL of the data.