Update on @my_helix SARS-CoV-2 surveillance program

- Dashboards here: public.tableau.com/profile/helix6…

Some analysis on 7 states where we (Helix) have most positive tests πŸ‘‡

Details in following tweets
(1 / n)
2/
How did I pick these 7 states?

- Each had >50 positives (Cq N gene <27) per day in recent Helix tests

- Alternative could be to use a threshold for % of positives in state coming from Helix
~5% of pos in these 7 states come from Helix

State Ns: covid.cdc.gov/covid-data-tra…
3/
California

Looking at absolute counts. Restricting graph to Feb 1st to March 23rd to better see the trend.

Note: in CA, majority of our tests are done in San Diego county.
4/
Florida

Overall cases starting to increase based on CDC. From what we see, it is mostly the counts of SGTF (~B.1.1.7) that is increasing.

Yet, this increase is not super fast (compared to some states). Note the difference in Y-axis πŸ‘‡
5/
Georgia

64% of positives are SGTF (~B.1.1.7). And importantly counts of SGTF are increasing right now.
6/
Massachusetts

It used to be the poster-child state to show that SGTF is not the same as B.1.1.7. For a long time MA, had 3-5% of positives that were SGTF and NOT B.1.1.7

Now, >90% of SGTF in MA are B.1.1.7. And SGTF counts increasing like in many states (still low numbers)
7/
Michigan

It is 1 of the states with fastest case πŸ“ˆ based on CDC. In our tests, we see fast πŸ“ˆ in counts of SGTF & also increase in non-SGTF.

Note: testing is from multiple places across state, done at a national retail pharmacy

Follow @LauringLab for experts in MI.
8/
North Carolina

Overall, 35% of positives are SGTF.

Counts definitely low, but looks to flatten, or even increase slightly.
9/
Pennsylvania

- a great example to visualize how B.1.1.7 is more transmissible than most other variants. non-SGTF counts are flat, but SGTF πŸ“ˆ

- Based on covid.cdc.gov/covid-data-tra… there were 15,103 positives in PA from 03/19-03/23.
& 1,043 in Helix with Cq<27 (~1,500 total)
10/
A question for the experts to end this series on B.1.1.7.

When does B.1.1.7 stops being a variant of concern because it is the dominant variant, and therefore becomes the reference?
Or this does not influence nomenclature?

@K_G_Andersen @dmaccannell
11/
1 more thought

Looking at the US & France (I am πŸ‡«πŸ‡·): the US have the big advantage of vaccines. Both supply and well orchestrated distribution.
I saw live a mass vaccination event in San Mateo. It was beautiful

=> Optimistic for US & I hope France copies πŸ‡ΊπŸ‡Έ re vaccines
Lastly, this program is result of big effort from many teams @my_helix (including lab and operations teams, engineering team, research etc.) as well as teams @illumina and many other partners including all the people involved in collecting testing samples

+ support from CDC.
Thread on variants of concerns (B.1.351, P.1, B.1.427, B.1.429)
& vars of interests (B.1.525, B.1.526) tomorrow.

but you can check some of these here: public.tableau.com/profile/helix6…

Tip: scroll over bars to see total counts & be careful with most recent day (usually incomplete)

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More from @alexbolze

20 Mar
Update on @my_helix SARS-CoV-2 surveillance

- Seq data up to Feb 26. >15,000 sequences since Jan 1.
- Check dashboard for stats on tests & variants of concerns in your state. public.tableau.com/profile/helix6…

Re B.1.1.7, Michigan πŸ“ˆ fast. MN too but we have less data.

More in🧡
2/
On Method:
- Numbers of positives, SGTF etc. are only reporting those with N gene Ct <27 (we use this threshold to select samples for sequencing).
- In Jan, we enriched sequences for SGTF to get grasp of % of SGTF that are B117. Now we don't enrich for SGTF anymore.
3/
Michigan.
SGTF (pretty much all of the ones we sequenced in MI were B117) represent now more than 60% of positives in MI.
And total cases in MI also on rise based on CDC tracker. πŸ‘‡
Read 7 tweets
10 Mar
Update on @my_helix SARS-CoV-2 surveillance program

Check public.tableau.com/profile/helix6…

~50% of cases in Florida, Georgia & Texas are B.1.1.7.

in FL: Overall cases continue to πŸ“‰ but 52.8% of pos were SGTF (S-gene target failure) on March 7.

=> We will track closely evolution
2/
In Georgia

54% of positives were SGTF on March 7.

While still ~90% of these are likely B.1.1.7, interesting to note that B.1.525 also sequenced several times in GA and also leads to SGTF

(note: B.1.525 is not a variant of concern)
3/
Texas

53% of positives were SGTF on March 7. Overall cases still going down. Again, we will keep testing, sequencing and tracking to see what happens as things reopen, and vaccinated population increases.
Read 4 tweets
6 Mar
Update from @my_helix SARS-CoV-2 surveillance program

Check public.tableau.com/profile/helix6…

🧡 with FL, TX, GA, CA & MA + results on identification of B.1.351 & P.1 !!

FL: B.1.1.7 is ~40% of positives. πŸ“ˆ about as predicted

Absolute numbers of B117 up despite overall πŸ“‰ in cases
2/
Texas

March 3: B117 were ~30% of positive tests.
26% with 5-day avg.

Absolute numbers of SGTF (a great proxy for B117 now) also going up despite big decrease in overall cases (as seen overall in US)

Note: this is only based on Helix data
3/
Georgia

March 3: B117 represents ~26% of positive tests.

Absolute numbers of SGTF (a great proxy for B117 now) also going up despite big decrease in overall cases (as seen overall in US)
Read 8 tweets
2 Mar
Data drop from @my_helix SARS-CoV-2 surveillance

Check any state public.tableau.com/profile/helix6…

Or download from github.com/myhelix/helix-…

To see if large vaccination effort can keep overall cases fromπŸ“ˆagain -> important to monitor FL

See @ScottGottliebMD for perspective
2/
With overall number of cases πŸ“‰ 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 πŸ‘‡
Read 6 tweets
1 Mar
Response to live-attenuated vaccines is a great way to study human response to infectious diseases.

Great paper from @casanova_lab studying 8 patients with life-threatening disease after live-attenuated yellow-fever vaccine.

rupress.org/jem/article-ab…
2/
Live-attenuated Yellow Fever vaccine is very safe & given to more than 600 million people.

But less than 1 in 100,000 have very severe disease after. And we know it is the same vaccine. So why?

Note: the COVID vaccines are NOT live attenuated vaccines.
3/
5 of 8 had defects in type 1 IFN response.

- 2 had autosomal recessive loss-of-function variants in IFNAR1 & IFNAR2.

- 3 others had auto-antibodies to type 1 IFN. At high concentration, plasma of patients inhibits addition of IFNa2 in cells and virus can grow. See πŸ‘‡
Read 4 tweets
24 Feb
SARS-CoV-2 surveillance data from @my_helix updated on Github and Tableau.

public.tableau.com/profile/helix6…

Last collection date:
- Feb 20 for testing
- Feb 7 for seq

Florida: >20% of positives are B117 πŸ“ˆ

🧡 with more results incl. B1429
2/
You can see the raw numbers for FL here: github.com/myhelix/helix-…

Screenshot with numbers.
- results based on many (>100 positives per day)
- clear that now ~100% of SGTF are B.1.1.7 in FL.

Rise of B.1.1.7 following what was shown in UK, Denmark & other places.
3/
B117 also on the rise in California.

~ all SGTF are B117
- On Feb 20 (not looking at Feb 21 that is incomplete data): 17% of positives are SGTF.
- 12.8% 5-day avg.
Read 7 tweets

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