Mike Honey

“harming memory and causing anxiety”

Hmm sounds just like the trolls and antivaxxers who’ve been so agitated lately …

zu klein ...

yeah no worries mate ...

So I interpret the results above as including a median reinfection rate of ~1-2 over their "Post-COVID" time period.

Populations in many other countries would have had higher reinfection rates. A few might be lower eg Japan, NZ, SE Asia.

There wasn't any data on COVID infection levels in China that period, but they did continue sharing genomic sequencing samples. From that, I assume they had a couple of significant waves: BA.2.86 (JN.1) "Pirola" then XDV.

NB.1.8.1.* also made a clean sweep in early 2025- usually means a wave.

Merci pour le coup de pouce!

Thanks for the feedback Amy, I‘m glad it is useful.

YMMV

Thanks so much for adding this context Dr Noor. It’s something I was definitely thinking about when I saw that chart, but I try to constrain myself to what the data says directly.

It’s also a hard reality to face, considering all those with CVD I’ve lost in recent years, and all those still at risk

Thanks Dr Noor. I really appreciate your feedback and support!

I’d guess that would be quite low, in China or anywhere else - perhaps under 10%?

We had a chance of a second year of lower transmission with weaker variants that would’ve given some respite, but now BA.3.2.* ”Cicada“ is looming …

I'm sure they will be OK, in the long run ...

h/t @ebharrington.bsky.social

Report Link:
mike-honey.github.io/covid-19-au-...
🧵ends

On a per-capita basis, Active Aged Care Staff Cases in South Australia have been higher than in other states, for a few weeks now.
🧵

Australian COVID-19 weekly stats update:

The risk estimate rose slightly, to 0.1% “Currently Infectious”, or 1-in-1,083.

That implies a 3% chance that someone is infectious in a group of 30.

#COVID19 #SARSCoV2 #Australia
🧵

Yes I have noticed that! A few seemed quite agitated, by BlueSky standards.

In the "All Patients" cohort (left chart), those selected Lymphocyte subsets were "only" about 9% below the baseline at the end of the study period. Changing by 9% at a rate of 3% per year would take a further 3 years.

What Im referring to is usually brief, along the lines of:

“I’m insanely angry about what you posted, I have nothing relevant to say or share to rebut you, but arrrggghhh!”
[with many typos, grammar errors etc]

I'm no fan of LLMs, but this seems harsh. The content I'm seeing is often unintelligible, borderline insane. I assume that only a human with broken cognitive and empathy systems could produce it.

Perhaps I'm naive about the capabilities of LLMs?

If they just dumped all their data, I would've faced a much greater challenge to correctly integrate it.

I do wish their format was a bit more open - tables in a Word doc usually need further processing to turn into data. But that's a routine chore.

I haven't seen any examples with full datasets.

But from my viewpoint, this paper has taken the right approach. They've shared the data that was shown in their charts/figures with a bit more context (e.g. IQRs, P-values etc). Their appendix is organised by Figure, so I could quickly understand it.

Thanks for the feedback Kolt! I really appreciate that.

* a further 3 years

So around 5 years total, for the cohort in that study.

It looks like the cardiovascular patient cohort was only ~2,000 or 5% of the total ~40,000. So some influence, but not major.

I only have access to the data shared publicly, in the Appendix Supplementary materials. It doesn't seem that detailed.

I was inspired by the discussions around this paper to integrate the data and try some alternative visualisations:
bsky.app/profile/mike...

I was inspired by the discussions around this paper to integrate the data and try some alternative visualisations:
bsky.app/profile/mike...

I was inspired by the discussions around this paper to integrate the data and try some alternative visualisations:
bsky.app/profile/mike...

I was inspired by the discussions around this paper to integrate the data and try some alternative visualisations. I rebuilt Figure 3 as a % change from the Baseline, which shows the drops across the subsets more clearly IMO.
bsky.app/profile/mike...

To be fair, the vibes on Xitter have also shifted lately - fewer sane posts and replies, more insane antivaxxers who have also fallen for every other insane conspiracy theory.

I expect they are energised by the current clown show that is US health policy.

* a further 3 years

So around 5 years in total.

Median figures across a population: YMMV