mikehoney.bsky.social
Data Visualisation and Data Integration specialist - Melbourne, Australia
https://linktr.ee/mike_honey_
Support my projects by sponsoring me on Github: https://github.com/sponsors/Mike-Honey
1,953 posts
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Getting Started
Active Commenter
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Hopeful signs of a peak already in the NB.1.8.1 "Nimbus" wave in NZ.
Further confirmation of that likelihood from wastewater data:
bsky.app/profile/thou...
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Confirms BA.3.2 as a big threat, should it pick up further mutations to improve it's fitness.
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Interactive mutation matching dataviz, code, acknowledgements and more info here:
github.com/Mike-Honey/s...
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With my tools I couldn't produce a log scale, but there are slider controls on the left and bottom axis, that effectively let you "zoom in" to a section of the scatter. That probably gives a better UX for that requirement.
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The chart compares the last 2 weeks, from the date range you select. In many places the most recent week of data will be too sparse, so you may have to use the date slicer to trim the end date. I show the sample sizes above the chart.
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The Variant Hunters gave me some great feedback on the early drafts – in particular @siamosolocani.bsky.social helped me with a list of BA.2 and JN.1 mutations to exclude (optionally). The default selection excludes those mutations.
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My version currently covers all the GISAID data back to Jan 2025, so it has a broader geographical scope. The mutations available are mostly the output of Nextclade, plus the GISAID "AA Substitutions" as an option.
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The most extreme recent example of this is the 3 "Doppelgänger" recombinants with identical spike mutations, which I described on this thread:
bsky.app/profile/mike...
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Many Variant Hunters & Trackers find the dynamics of mutations to be a useful lens for analysis of SARS-CoV-2. The phenomenon of "convergent evolution" regularly produces successful variants that arrive at similar sets of mutations by different pathways.
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The volume is a bit low to make sense of this picture, you have to try to spot the trends and ignore the spikiness.
I would say NB.1.8.1 is rising so that is the main factor. But LP.8.1.* and XEC.* are hanging on better than they have in other states.
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My analysis and trends:
bsky.app/profile/mike...
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The NB.1.8.1 "Nimbus" variant surged in May to 72% frequency for WA.
bsky.app/profile/mike...
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It looks like pertussis (whooping cough) has only been tracked on the NNDSS since Jan 2024. In WA, it has been growing pretty relentlessly since, with a brief respite over summer.
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Interactive genomic sequencing dataviz, code, acknowledgements and more info here:
github.com/Mike-Honey/c...
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Here are the recent International Traveller samples originating from Japan (arriving in the US). This confirms the recent dominance of the NB.1.8.1 "Nimbus" variant.
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Regrettably, the sample volumes from Japan shrank from April onwards, so the picture is uncertain.
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Interactive genomic sequencing dataviz, code, acknowledgements and more info here:
github.com/Mike-Honey/c...
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Here are the recent International Traveller samples originating from India. This confirms the recent dominance of the XFG.* variant.
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Sample data sharing from India came to a grinding halt in September, with just a handful of samples prior to the data shown above.
Although the volumes are low, the recent data from India has quite a good geographical spread. Perhaps a bit of a skew towards the southern states?
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Here are the most common individual variants for India. The FLiRT sub-variant is LF.7.9.1. That adds the ORF3a:G44E mutation and some nucleotide mutations.
The parent LF.7.9 was already moderately successful, benefiting from its Spike L441R, H445P and A475V mutations.
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Thanks Carlos - you too!
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Thanks Wei!
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Report link:
mike-honey.github.io/covid-19-gen...
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Singapore, Brazil and Japan have shared the most sample data recently. China is well down the list, especially considering its large size and relative wealth.
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XFG.* made up 100% of recent samples from Bangladesh. India is at 44%.
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The first reported wave of NB.1.8.1 "Nimbus" was in Hong Kong, rising to 100% frequency. It has also shown sustained growth in other countries across the region.
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For the "Global - Other" countries, the XFG.* variant is showing a growth advantage of 1.9% per day (13% per week) over the NB.1.8.1 "Nimbus" variant. Any crossover looks distant.
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This perspective excludes all the high-volume countries and regions that I routinely report on: Australia, NZ, Europe, Canada and the US. The remaining countries are aggregated into this report.
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Report link:
mike-honey.github.io/covid-19-gen...
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Here are the leading European countries reporting XFG.*. It has reached 50% among sparse samples from Belgium. Denmark, the Netherlands and Spain have each reported growth to around 30%.
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For Europe (excluding the UK), the XFG.* variant shows an accelerating growth advantage of 4.8% per day (34% per week) over LP.8.1.*. That now predicts a crossover in early June (the data routinely lags).
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mike-honey.github.io/covid-19-gen...
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For the UK, the XFG.* variant shows a slowing growth advantage of 3.5% per day (25% per week) over LP.8.1.*. That predicts a crossover in mid-June.
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mike-honey.github.io/covid-19-gen...
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For Canada, the NB.1.8.1 "Nimbus" variant shows a slowing growth advantage of 2.9% per day (20% per week) over LP.8.1.*, which predicts a crossover in mid-June.
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Report link:
mike-honey.github.io/covid-19-gen...
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NB.1.8.1 "Nimbus" has mainly been reported among the International Traveller samples, at around 20-40% frequency.
It has been dominant among patchy samples from Maryland.
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For the US, the NB.1.8.1 "Nimbus" variant shows a faster growth advantage of 7.2% per day (50% per week) over LP.8.1.*, which now predicts a crossover in early June (the data routinely lags).
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XFG.* has mainly been reported from New York state, rising to 33% frequency. It has also been very common among the International Traveller samples. It rose in Vermont to 20%.
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For the US, the XFG.* variant shows a strong growth advantage of 6.1% per day (43% per week) over LP.8.1.*, which predicts a crossover in late May (the data routinely lags).
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Report link:
mike-honey.github.io/covid-19-gen...
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