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JWeiland Profile picture
@JPWeiland
Oct 17 • 5 tweets • 2 min read Twitter logo Read on Twitter
#JN.1 #Pirola is demonstrating strong growth in France, where its been found most frequently. At 2% by Oct 2.

These estimates tend to skew high early with a new variant.

To me it looks likely >100%/wk, which would make it more than twice as fast as anything else out there. Image
We are also seeing it outcompete the baseline BA.2.86.1 quickly in France. Now more than 50% of Pirola in France are JN.1, in just a few weeks.

If >100% holds, JN.1 could drive a wave in France as early as mid November.

More data can change that timeline. Image
This chart from @RajlabN shows it growing in various places. Take a look at the UK, also showing exceptionally fast growth
Image
Nick Rose @Asinickle1 has been doing a fantastic job keeping track of JN.1, and has also been estimating growth. We are arriving at close to the same numbers.

Some of us have been told that were focusing too much on Pirola vs other variants.

We thought from the early on that it was going to quickly optimize.

I think our focus has been warranted.

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More from @JPWeiland

JWeiland Profile picture
Sep 25
There's a new study claiming no increased risk of new any type infection after covid infection. I don't have a strong opinion on either side of this argument at this point. Let's take an objective look at what this study actually shows (TLDR, it's poor): academic.oup.com/cid/advance-ar…
Right off the bat there is a glaring issue. As @DGBassani points out, the control group (uninfected) has more than 3x the deaths as the covid infected group. And there's more, far more comorbidities and +5 years. That's a terrible control group.
Image
They also intentionally removed anyone with more than 1 covid infection from the data (?? You'd think they might be important to this study, no?)
One would think maybe those people were the most likely to have had some immune disfunction. But they were slashed from the results.
Read 5 tweets
JWeiland Profile picture
Sep 22
BA.2.86 Pirola's global growth advantage is becoming more clear. I excluded South Africa's data (way too messy), and the UK care home cluster.

Estimated weekly advantage is 74%, with a 50% CI of 56-96%.

If this holds, it would suggest Pirola outcompetes the strongest FLips. Image
The biggest uncertainty to me still lies in the randomness of sampling. It's unclear it some samples are being sequenced due to SGTF, or more importantly, if that has changed in the past month.

Data pulled from @Mike_Honey_ 's datavis app.powerbi.com/view?r=eyJrIjo…
I agree with @Asinickle1 estimate in Denmark. Just not convinced yet that Denmark will be representative of the world's varied immune history. We will see if it is or not in coming months.
Read 4 tweets
JWeiland Profile picture
Sep 14
September 14th US update:

Community spread of Covid still "high", but decreasing after the peak. Current estimates:

🔸650,000 new infections/day
🔸1 in every 510 new people were infected today
🔸1 in every 51 people currently infected Image
The decrease is mainly driven by the south, which is seeing a sharp decline in WW. Other areas of the country seeing stabilizing of cases.

Population infection estimates below: Image
This is consistent with about the mid to lower end of the forecast range (since hospitalizations lag about a week behind wastewater).

Read 4 tweets
JWeiland Profile picture
Sep 11
Forecast out to mid October:

Prediction is difficult at the moment with a lot of factors at play, so this is a range for now. Peaks are always hard to predict.

Lower model run peaks this week. FLip is growing, but not fast enough to peak later than late Sept. Image
FLip, and HV.1 with L452R (last seen in Delta and BA.5*) are growing, with HV.1 and HK.3 being the fastest at the moment. They probably won't come into play until late Oct/Nov, likely starting a new wave.

Still waiting to see how Ba.2.86 Pirola evolves and moves.
This range translates to a max of ~720-900k cases per day for this wave on the wastewater calibration curve. Image
Read 5 tweets
JWeiland Profile picture
Aug 28
One more week of data on hospitalizations to check the model accuracy. Out 5 weeks now.

Model date: Jul 18
Last Hosp data: Jul 8 (always 9-16 days behind current date)
Image
Going to post the couple models before that as well. Here's the results from the June 8th model (4-5 weeks):


Image
And here is the previous model from March that predicted out past 8 weeks.

Image
Read 4 tweets
JWeiland Profile picture
Aug 20
For sake of comparison, what happened with Omicron? A thread:

First, we had 3 highly mutated sequences from Botswana/South Africa. Within a few days we had enough data from SA to estimate growth advantage of 500%
1/
Then, we were able to see quick case growth in South Africa. The case growth roughly agreed with the advantage estimate. A couple days after this the Re increased to 3.6.
2/
A few days later I modeled how this might play out in the US. At this time there were only 3 sequences in the US. And it did play out as predicted.
3/
Read 7 tweets

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