I facilitated an online workshop for @freetechproject tonight and it's the first time we tackled technology to fight #Covid (Co2 monitors, air purifiers, #HEPA, #CorsiRosenthal boxes, #NukitTempest, etc) as well as why this is important (what Covid is, how it spreads, etc) and the small (predominantly older) group was very open to the ideas, sincerely inquisitive about the topic, interested in reducing risk, aware of inclusion issues, and sensitive to my own experiences as carer for a partner disabled by Covid. I'm also realising that people genuinely refer to "Covid" in the past tense sometimes because they wrongly associate it with government policy, while at the same time they very clearly understand that #CovidIsNotOver. My point is, keep tackling the topic, and keep giving folks the benefit of the doubt -- humans are of course good at heart and state policies, and of course the establishment media, may very well indeed not, in fact, reflect people's actual concerns about Covid.
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#CovidIsNotOver
In regards to #longCovid
(please boost for reach)
Entering year 6 of the #COVID19 pandemic, to the best of your knowledge, you have been infected:
(please boost for reach)
#CovidIsNotOver
Hi!
I’m jdm2. I’ve been around for a while. Recently created the boriken.social Mastodon instance to facilitate the migration to the fediverse of the Puerto Rican online community.
I’m a software developer by trade, I collect books, listen to a bunch of music, love basketball and I’m very vocal about local and international politics.
And I’m covid conscious!
Bin keine Brillenträgerin. Aber eine Freundin möchte #Maske tragen um andere zu schützen, hat aber Probleme dass sie immer beschlägt.
Für Leute, die sonst keine und nicht gerne Maske tragen: was sind eure besten Empfehlungen? Darf nicht teuer sein, sollte gut sitzen, aber kein Kopfband.
I'm bringing copies of this to plaster to clinics' elevator, hallways & front entrance.
New server, new #Introduction
Greetings! I am a resident of the Pacific Northwest, USA. Currently surviving the mess in the US as best I can, so I occasionally drop an F-bomb. Sorry, not sorry.
Updated GISAID data early-mid January has FluQE31 KP.3.1.1 / MC and children down to under a third of all sequences.
FLiRT KS.1.1 / FLuQE KP.3.3 hybrid XEC now over two fifths.
JN.1 FLiRT descendant LF.7 is diversifying, while LP.8.1.1 / NY, MC.8.1, and XEQ (recombinant of FLiRT KS.1.1.2 and KP.3) all stand out.
❖ #ThisIsOurPolio #Covid #Covid19 #SARS2 #variants #CovidIsNotOver #CovidIsAirborne
![Chart: SARSCoV2 Variant Dashboard - USA | 30-DAY TRENDS
Source: NYITCOM Research Report (Raj Rajnarayanan)
Caption (in part): Circulating Variants in…following US States: All - Specimen Collected in…last 30 days | Updated on 1/31/2025 6:43:47 AM [GMT?] | Source (sequences): GISAID
Packed-bubble chart showing tallies of each identified variant for each state, for collection dates 1/5/2025 to 1/18/2025. Top subvariants: XEC (26.32%), KP.3.1.1 (8.61%), LP.8.1 (5.74%), XEC.2 (4.23%), MC.10.1 (4.18%).
Raj has standardized bubbles to violet (BA.2.86.*), aqua green (XBB.1.16.*), forest green (XEC, a recombinant of two B.2.86 strains), and yellow (LP.8.*). although some newer Pango aliases may still be getting unique colors assigned by Tableau.
Bubbles largest and most prominent for: XEC (forest) in Ohio (171), New York (85), Colorado (58), Minnesota (46), New Jersey, Iowa, Utah; KP.3.1.1 (violet) for Ohio (58), Minnesota, New York; MC.8.1 (violet) for Ohio (51); XEQ (aqua) for Colorado (34); LP.8.1 (yellow) for New York, Ohio.
Many dozens of bubbles of varying sizes representing over a hundred variants across various states.
ALT-text by beadsland at ko-fi.](https://spaces.hcommons.social/media_attachments/files/113/925/598/052/682/439/original/4b72cd6231c464fe.png "Chart: SARSCoV2 Variant Dashboard - USA | 30-DAY TRENDS
Source: NYITCOM Research Report (Raj Rajnarayanan)
Caption (in part): Circulating Variants in…following US States: All - Specimen Collected in…last 30 days | Updated on 1/31/2025 6:43:47 AM [GMT?] | Source (sequences): GISAID
Packed-bubble chart showing tallies of each identified variant for each state, for collection dates 1/5/2025 to 1/18/2025. Top subvariants: XEC (26.32%), KP.3.1.1 (8.61%), LP.8.1 (5.74%), XEC.2 (4.23%), MC.10.1 (4.18%).
Raj has standardized bubbles to violet (BA.2.86.*), aqua green (XBB.1.16.*), forest green (XEC, a recombinant of two B.2.86 strains), and yellow (LP.8.*). although some newer Pango aliases may still be getting unique colors assigned by Tableau.
Bubbles largest and most prominent for: XEC (forest) in Ohio (171), New York (85), Colorado (58), Minnesota (46), New Jersey, Iowa, Utah; KP.3.1.1 (violet) for Ohio (58), Minnesota, New York; MC.8.1 (violet) for Ohio (51); XEQ (aqua) for Colorado (34); LP.8.1 (yellow) for New York, Ohio.
Many dozens of bubbles of varying sizes representing over a hundred variants across various states.
ALT-text by beadsland at ko-fi.")
![Chart: Variants by Pango-Designated Lineage: U.S. Jan 5 to 18
Source: GISAID (via Raj Rajnarayanan's COVID-19 Variant Dashboard, updated Jan 31)
[ beadsland on Ko-fi ]
Pie chart of major lineages, with lesser lineages bundled together by common alphanumeric initial character. Call-outs for each pie slice list number of variants counted and provide a percentage of pie.
Percentage is in a dull grey font, to which a dark backing has been applied to aid legibility.
Color key of pie slices aligns to that of latest "Estimated Variant Proportions by Common Name" (earlier in this thread), namely:
• Purples: JN.1.11
• Reds/Pinks: JN.1.11 + FLiRT
• Browns: JN.1.11 + FLiRT-LP
• Blues: XEC
• Greens: JN.1 + FLiRT
• Greys: Other
Reading clockwise from top:
- Multiple unlabeled slivers of grey and pink.
8.6% - KP.3.1.1 / MC [purple]
- Unlabeled purple sliver & grey sliver
2.2% - LB.1.3.1 (1 var) [green]
- Unlabeled green sliver
3.4% - LF.7 (10 variants) [green]
3.9% - LP.8.1.1 (1 var) [brown]
5.9% - LP.8.1 (2 variants) [brown]
- Unlabeled brown and grey silvers
5.2% - MC.1 (5 variants) [purple]
3.4% - MC.8.1 (2 variants) [purple]
4.2% - MC.10.1 (1 var) [purple]
- Two unlabeled purple slices
8.5% - other MC (22 variants) [purple]
- Unlabeled grey slice
1.4% - NL (4 variants) [green]
- Unlabeled grey slice
5.7% - XEC.2 (5 variants) [blue]
2.0% - XEC.2 (1 var) [blue]
34% - other XEC (10 variants) [blue]
1.6% - XEK (4 variants) [red orange]
3.0% - XEQ (1 var) [grey]
- Unlabeled grey slice](https://spaces.hcommons.social/media_attachments/files/113/925/598/461/876/410/original/409a1e8fa79e0fd6.png "Chart: Variants by Pango-Designated Lineage: U.S. Jan 5 to 18
Source: GISAID (via Raj Rajnarayanan's COVID-19 Variant Dashboard, updated Jan 31)
[ beadsland on Ko-fi ]
Pie chart of major lineages, with lesser lineages bundled together by common alphanumeric initial character. Call-outs for each pie slice list number of variants counted and provide a percentage of pie.
Percentage is in a dull grey font, to which a dark backing has been applied to aid legibility.
Color key of pie slices aligns to that of latest \"Estimated Variant Proportions by Common Name\" (earlier in this thread), namely:
• Purples: JN.1.11
• Reds/Pinks: JN.1.11 + FLiRT
• Browns: JN.1.11 + FLiRT-LP
• Blues: XEC
• Greens: JN.1 + FLiRT
• Greys: Other
Reading clockwise from top:
- Multiple unlabeled slivers of grey and pink.
8.6% - KP.3.1.1 / MC [purple]
- Unlabeled purple sliver & grey sliver
2.2% - LB.1.3.1 (1 var) [green]
- Unlabeled green sliver
3.4% - LF.7 (10 variants) [green]
3.9% - LP.8.1.1 (1 var) [brown]
5.9% - LP.8.1 (2 variants) [brown]
- Unlabeled brown and grey silvers
5.2% - MC.1 (5 variants) [purple]
3.4% - MC.8.1 (2 variants) [purple]
4.2% - MC.10.1 (1 var) [purple]
- Two unlabeled purple slices
8.5% - other MC (22 variants) [purple]
- Unlabeled grey slice
1.4% - NL (4 variants) [green]
- Unlabeled grey slice
5.7% - XEC.2 (5 variants) [blue]
2.0% - XEC.2 (1 var) [blue]
34% - other XEC (10 variants) [blue]
1.6% - XEK (4 variants) [red orange]
3.0% - XEQ (1 var) [grey]
- Unlabeled grey slice")
A FLuQE wavelet opened September, becoming MC wave into November. December saw both FLiRT clans and JN.1.11 vie for dominance, only for JN.1 FLiRT to win out.
Although #CDC did update metadata today, data remains unchanged from two weeks ago.
At that time, FLiRT KS.1.1 / FLuQE KP.3.3 hybrid XEC family—never having reached majority—was being pressed by FLiRT LP.8.1.
New GISAID data from Raj.
❖ #ThisIsOurPolio #Covid #Covid19 #SARS2 #variants #CovidIsNotOver #CovidIsAirborne #dataviz #datavis
![Chart: Estimated U.S. Variant Proportions by Common Name
Sources: Centers for Disease Control, CoV-Lineages, NYITCOM Research, Daniele Focosi, World Health Network, others
[ beadsland on Ko-fi ]
Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC.
Five bar-style tree-charts, for fortnights through January 5–18. Legend of last fortnight, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart.
Essentially all WHO-Vaccine-Target JN.1. JN.1 + FLiRT accounts for well over half; XEC for near half.
For fortnight of 1/5–1/18, packed bubble charts fill single-variant tiles, indicating diversification of those variants (per GISAID) that wouldn't otherwise be apparent from CDC's Nowcast.
Legend:
XEC [blues]:
47% - XEC.2† & other XEC
3% - XEC.4
JN.1.11 [purples]:
23% - MC.10.1, MC.1, MC.19, MC.8.1† & other KP.3.1.1 / MC
1% - KP.3 & XEQ†
JN.1.11 + FLiRT-LP [browns]:
15% - LP.8.1.1 / NY† & other LP.8.1
⅛% - LP.1 & other KP.1.1.3 / LP
JN.1 + FLiRT [greens]:
4% - LF.7
2% - LB.1.3.1 / NL
1% - JN.1.18.6 / LY
⅒% - LB.1
JN.1.11 + FLiRT [reds]:
4% - XEK
⅒% - FDA-Vaccine-Target KP.2
⅑% - other KP.2.3
Other [greys]:
⅒% - other WHO-Vaccine-Target JN.1
⅒% - Other (not specified)
† Dagger variants are not broken out by CDC, yet represent a significant share of recent GISAID sequences.](https://spaces.hcommons.social/media_attachments/files/113/925/353/197/745/222/original/94093d6ec2405a9c.jpg "Chart: Estimated U.S. Variant Proportions by Common Name
Sources: Centers for Disease Control, CoV-Lineages, NYITCOM Research, Daniele Focosi, World Health Network, others
[ beadsland on Ko-fi ]
Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC.
Five bar-style tree-charts, for fortnights through January 5–18. Legend of last fortnight, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart.
Essentially all WHO-Vaccine-Target JN.1. JN.1 + FLiRT accounts for well over half; XEC for near half.
For fortnight of 1/5–1/18, packed bubble charts fill single-variant tiles, indicating diversification of those variants (per GISAID) that wouldn't otherwise be apparent from CDC's Nowcast.
Legend:
XEC [blues]:
47% - XEC.2† & other XEC
3% - XEC.4
JN.1.11 [purples]:
23% - MC.10.1, MC.1, MC.19, MC.8.1† & other KP.3.1.1 / MC
1% - KP.3 & XEQ†
JN.1.11 + FLiRT-LP [browns]:
15% - LP.8.1.1 / NY† & other LP.8.1
⅛% - LP.1 & other KP.1.1.3 / LP
JN.1 + FLiRT [greens]:
4% - LF.7
2% - LB.1.3.1 / NL
1% - JN.1.18.6 / LY
⅒% - LB.1
JN.1.11 + FLiRT [reds]:
4% - XEK
⅒% - FDA-Vaccine-Target KP.2
⅑% - other KP.2.3
Other [greys]:
⅒% - other WHO-Vaccine-Target JN.1
⅒% - Other (not specified)
† Dagger variants are not broken out by CDC, yet represent a significant share of recent GISAID sequences.")
Oh, me?
Just sitting here, wondering how much GISAID data for the U.S. there will be from late January forward. (Raj's dashboard last shows data through the 17th.)
Aware that #CDC long ago would have preferred to stop publishing #covid variants estimates, am expecting to not see same updated this Friday.
They stopped publishing all other related data long before now, and still weren't publishing anything useful wrt #BirdFlu, as of close of last administration.
So now we wait to see how much compliance in advance impacts academic researchers submitting data to a global non-profit. (Let alone how much of U.S. GISAID data may be typically provided by gov't researchers.)
Yes, GISAID was founded in opposition to WHO's proprietary data practices. But also, GISAID's public domain ethos is close enough in spirit to F/OSS that it might just as readily be a target of isolationist fervor.
So, it's wait in see.
Last quote:
"This study's findings underscore the urgent need for treatments," Pollack said.
"ME/CFS can be caused by multiple triggers in addition to SARS-CoV-2, and it has been among the least funded illnesses for research, despite its severity."
More quotes:
"… some participants may have had undiagnosed ME/CFS before having COVID-19, which could be a limitation of the work. The questionnaire-based nature of the study presented another limitation, because participants may have struggled to remember whether their symptoms started before or after they had COVID-19.
Despite these limitations, the findings do suggest that COVID-19 raises the risk of ME/CFS."
"1 in 22 COVID survivors develop debilitating chronic syndrome"
"A study suggests that catching COVID-19 significantly raises the risk of developing ME/CFS…a typically lifelong condition that can be debilitating"
"By my rough calculations it is possible that over 7 million Americans may have developed ME/CFS following COVID"
New press release:
"Long COVID, Italian scientists discovered the molecular ‘fingerprint’ of the condition in children's blood"
https://www.eurekalert.org/news-releases/1071370
Hashtags:
@longcovid
#LongCovid #PASC #PwLC #postcovid #postcovid19 #LC #Covidlonghaulers #PostCovidSyndrome #longhaulers #COVIDBrain #NeuroPASC
@covid19 #Coronavirus
#COVID19 #COVID #COVID_19 #COVIDー19 #SARSCoV2 @novid@chirp.social #novid @novid@a.gup.pe #CovidIsNotOver
@auscovid19 #auscovid19
#LongCovidKids #LCKids
Updated GISAID data entering January has FluQE31 KP.3.1.1 / MC and children down to just over a third of all sequences.
FLiRT KS.1.1 / FLuQE KP.3.3 hybrid XEC now approaching two fifths.
JN.1 FLiRT descendant LF.7 is diversifying, while KP.1.1.3 / LP scion LP.8.1, and recombinant XEL—child of JN.1 and FLiRT KS.1.1.2—both stand out.
❖ #ThisIsOurPolio #Covid #Covid19 #SARS2 #variants #CovidIsNotOver #CovidIsAirborne
![Chart: SARSCoV2 Variant Dashboard - USA | 30-DAY TRENDS
Source: NYITCOM Research Report (Raj Rajnarayanan)
Caption (in part): Circulating Variants in…following US States: All - Specimen Collected in…last 30 days | Updated on 1/20/2025 6:14:21 AM [GMT?] | Source (sequences): GISAID
Packed-bubble chart showing tallies of each identified variant for each state, for collection dates 12/22/2024 to 1/4/2025. Top subvariants: XEC (30.71%), KP.3.1.1 (16.45%), LP.8.1 (8.11%), XEC.2 (4.60%), MC.10.1 (4.08%).
Raj has standardized bubbles to violet (BA.2.86.*), aqua green (XBB.1.16.*), forest green (XEC, a recombinant of two B.2.86 strains), and yellow (LP.8.*). although some newer Pango aliases may still be getting unique colors assigned by Tableau.
Bubbles largest and most prominent for: XEC (forest) in Minnesota (83), Colorado (66), Ohio (65), New York (53), Utah (40), New Jersey (35), Nebraska (30), Pennsylvania, California, Arizona, Iowa, Illinois; KP.3.1.1 (violet) for Minnesota (52), Ohio (35), Colorado (29), California, New York, Iowa, Nebraska; LP.8.1 (yellow) for Minnesota, New York, California; XEC.2 (forest) for New York.
Dozens of bubbles of varying sizes representing a many dozens of variants across various states.
ALT-text by beadsland at ko-fi.](https://spaces.hcommons.social/media_attachments/files/113/871/405/556/703/116/original/9f948a436f03b135.png "Chart: SARSCoV2 Variant Dashboard - USA | 30-DAY TRENDS
Source: NYITCOM Research Report (Raj Rajnarayanan)
Caption (in part): Circulating Variants in…following US States: All - Specimen Collected in…last 30 days | Updated on 1/20/2025 6:14:21 AM [GMT?] | Source (sequences): GISAID
Packed-bubble chart showing tallies of each identified variant for each state, for collection dates 12/22/2024 to 1/4/2025. Top subvariants: XEC (30.71%), KP.3.1.1 (16.45%), LP.8.1 (8.11%), XEC.2 (4.60%), MC.10.1 (4.08%).
Raj has standardized bubbles to violet (BA.2.86.*), aqua green (XBB.1.16.*), forest green (XEC, a recombinant of two B.2.86 strains), and yellow (LP.8.*). although some newer Pango aliases may still be getting unique colors assigned by Tableau.
Bubbles largest and most prominent for: XEC (forest) in Minnesota (83), Colorado (66), Ohio (65), New York (53), Utah (40), New Jersey (35), Nebraska (30), Pennsylvania, California, Arizona, Iowa, Illinois; KP.3.1.1 (violet) for Minnesota (52), Ohio (35), Colorado (29), California, New York, Iowa, Nebraska; LP.8.1 (yellow) for Minnesota, New York, California; XEC.2 (forest) for New York.
Dozens of bubbles of varying sizes representing a many dozens of variants across various states.
ALT-text by beadsland at ko-fi.")
![Chart: Variants by Pango-Designated Lineage: U.S. Dec 22 to Jan 4
Source: GISAID (via Raj Rajnarayanan's COVID-19 Variant Dashboard, updated January 20)
[ beadsland on Ko-fi ]
Pie chart of major lineages, with lesser lineages bundled together by common alphanumeric initial character. Call-outs for each pie slice list number of variants counted and provide a percentage of pie.
Percentage is in a dull grey font, to which a dark backing has been applied to aid legibility.
Color key of pie slices aligns to that of latest "Estimated Variant Proportions by Common Name" (earlier in this thread), namely:
• Purples: JN.1.11
• Reds/Pinks: JN.1.11 + FLiRT
• Browns: JN.1.11 + FLiRT-LP
• Blues: XEC
• Greens: JN.1 + FLiRT
• Greys: Other
Reading clockwise from top:
- Mult. unlabeled slivers of grey & pink.
16.4% - KP.3.1.1 / MC [purple]
3.0% - other KP.3 (9 variants) [pink]
- Unlabeled sliver of grey.
2.2% - LB.1.3.1 (1 var.) [green]
- Unlabeled sliver of green.
4.0% - LF.7 (7 variants) [green]
8.1% - LP.8.1 (1 var.) [brown]
- Unlabeled slivers of brown, green, grey.
3.5% - MC.1 (2 variants) [purple]
4.1% - MC.10.1 (1 var.) [purple]
- Unlabeled sliver of purple.
1.4% - MC.19 (1 var.) [purple]
7.5% - other MC (19 variants) [purple]
- Unlabeled slice of grey.
2.4% - NL (6 variants) [green]
- Unlabeled slice of grey.
4.6% - XEC.2 (1 var.) [blue]
- Unlabeled slice of blue.
32.2% - other XEC (5 variants) [blue]
- Unlabeled slice of pink.
2.2% - XEL (1 var.) [grey]
- Unlabeled slice of grey](https://spaces.hcommons.social/media_attachments/files/113/871/406/386/336/746/original/68c398d78fe1b42a.png "Chart: Variants by Pango-Designated Lineage: U.S. Dec 22 to Jan 4
Source: GISAID (via Raj Rajnarayanan's COVID-19 Variant Dashboard, updated January 20)
[ beadsland on Ko-fi ]
Pie chart of major lineages, with lesser lineages bundled together by common alphanumeric initial character. Call-outs for each pie slice list number of variants counted and provide a percentage of pie.
Percentage is in a dull grey font, to which a dark backing has been applied to aid legibility.
Color key of pie slices aligns to that of latest \"Estimated Variant Proportions by Common Name\" (earlier in this thread), namely:
• Purples: JN.1.11
• Reds/Pinks: JN.1.11 + FLiRT
• Browns: JN.1.11 + FLiRT-LP
• Blues: XEC
• Greens: JN.1 + FLiRT
• Greys: Other
Reading clockwise from top:
- Mult. unlabeled slivers of grey & pink.
16.4% - KP.3.1.1 / MC [purple]
3.0% - other KP.3 (9 variants) [pink]
- Unlabeled sliver of grey.
2.2% - LB.1.3.1 (1 var.) [green]
- Unlabeled sliver of green.
4.0% - LF.7 (7 variants) [green]
8.1% - LP.8.1 (1 var.) [brown]
- Unlabeled slivers of brown, green, grey.
3.5% - MC.1 (2 variants) [purple]
4.1% - MC.10.1 (1 var.) [purple]
- Unlabeled sliver of purple.
1.4% - MC.19 (1 var.) [purple]
7.5% - other MC (19 variants) [purple]
- Unlabeled slice of grey.
2.4% - NL (6 variants) [green]
- Unlabeled slice of grey.
4.6% - XEC.2 (1 var.) [blue]
- Unlabeled slice of blue.
32.2% - other XEC (5 variants) [blue]
- Unlabeled slice of pink.
2.2% - XEL (1 var.) [grey]
- Unlabeled slice of grey")
A FLuQE wavelet opened September, becoming MC wave into November. December saw both FLiRT clans and JN.1.11 vie for dominance, only for JN.1 FLiRT to win out.
After skipping update two weeks prior, #CDC broke out XEC.4, as FLiRT KS.1.1 / FLuQE KP.3.3 hybrid XEC family—never having reached majority—being pressed by FLiRT LP.8.1.
New dashboard from Raj givs us more recent GISAID data.
❖ #ThisIsOurPolio #Covid #Covid19 #SARS2 #variants #CovidIsNotOver #CovidIsAirborne #dataviz #datavis
![Chart: Estimated U.S. Variant Proportions by Common Name
Sources: Centers for Disease Control, CoV-Lineages, NYITCOM Research, Daniele Focosi, World Health Network, others
[ beadsland on Ko-fi ]
Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC.
Five bar-style tree-charts, for fortnights through January 5–18. Legend of last fortnight, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart.
Essentially all WHO-Vaccine-Target JN.1. JN.1 + FLiRT accounts for well over half; XEC for near half.
For fortnight of 12/22–1/4, packed bubble charts fill single-variant tiles, indicating diversification of those variants (per GISAID) that wouldn't otherwise be apparent from CDC's Nowcast.
Legend:
XEC [blues]:
47% - XEC.2† & other XEC
3% - XEC.4
JN.1.11 [purples]:
1% - KP.3
23% - MC.10.1, MC.1, MC.19 & other KP.3.1.1 / MC
JN.1.11 + FLiRT-LP [browns]:
15% - LP.8.1
⅛% - LP.1 & other KP.1.1.3 / LP
JN.1 + FLiRT [greens]:
4% - LF.7
2% - LB.1.3.1 / NL
1% - JN.1.18.6 / LY
⅒% - LB.1
JN.1.11 + FLiRT [reds]:
4% - XEK
⅒% - FDA-Vaccine-Target KP.2
⅑% - other KP.2.3
Other [greys]:
⅒% - other WHO-Vaccine-Target JN.1
⅒% - Other (not specified)
† Dagger variant is not broken out by CDC, yet represent a significant share of recent GISAID sequences.](https://spaces.hcommons.social/media_attachments/files/113/871/149/086/456/148/original/ab960ae7a01a0789.jpg "Chart: Estimated U.S. Variant Proportions by Common Name
Sources: Centers for Disease Control, CoV-Lineages, NYITCOM Research, Daniele Focosi, World Health Network, others
[ beadsland on Ko-fi ]
Reskin of CDC's Variants Nowcast, and any significant variants in GISAID not broken out by CDC.
Five bar-style tree-charts, for fortnights through January 5–18. Legend of last fortnight, organized by subheadings of color-grouped families and convergent clusters. Percentages overlay each color key, reflecting share as of most recent tree-chart.
Essentially all WHO-Vaccine-Target JN.1. JN.1 + FLiRT accounts for well over half; XEC for near half.
For fortnight of 12/22–1/4, packed bubble charts fill single-variant tiles, indicating diversification of those variants (per GISAID) that wouldn't otherwise be apparent from CDC's Nowcast.
Legend:
XEC [blues]:
47% - XEC.2† & other XEC
3% - XEC.4
JN.1.11 [purples]:
1% - KP.3
23% - MC.10.1, MC.1, MC.19 & other KP.3.1.1 / MC
JN.1.11 + FLiRT-LP [browns]:
15% - LP.8.1
⅛% - LP.1 & other KP.1.1.3 / LP
JN.1 + FLiRT [greens]:
4% - LF.7
2% - LB.1.3.1 / NL
1% - JN.1.18.6 / LY
⅒% - LB.1
JN.1.11 + FLiRT [reds]:
4% - XEK
⅒% - FDA-Vaccine-Target KP.2
⅑% - other KP.2.3
Other [greys]:
⅒% - other WHO-Vaccine-Target JN.1
⅒% - Other (not specified)
† Dagger variant is not broken out by CDC, yet represent a significant share of recent GISAID sequences.")
NCHS estimates of #LongCovid—based on Household Pulse Survey.
Have been holding off refreshing this thread, as Census was due to relaunch HPS as HTOPS in January:
https://hcommons.social/@beadsland/113728679706939484
Word of a moratorium on government communications, makes this seem unlikely:
https://zeroes.ca/@maleve/113869675383946385
Nonetheless HPS reporting was suspended, despite ongoing data collection, in October of the prior administration.
#ThisIsOurPolio #CountLongCovid #CovidIsNotOver #MassDisablingEvent
[This is first toot of periodically refreshed thread, providing various dataviz of ongoing #pandemic.]
Last period:
https://hcommons.social/@beadsland/113608415072830510
![Chart: Estimates of Long Covid: Extrapolated to Entire U.S. Population
Data: Census Bureau, Nat'l Cntr for Health Stats, Dept of Health & Human Svcs, Bureau of Labor Stats (via FRED), CDC
[ beadsland on Ko-fi ]
Line chart, from Apr 2022 to date, of:
• Ever Experienced Long Covid for 3+ Months (60.3M as of Sep 16)
• Reported Staffed Hospital Beds (2.1K per Million) [Was 2.3K Apr '22]
• Population 16+ With a Disability — Labor Stats (34.8M) [Apr '22: 32.7M]
• Now Living with LC (17.9M)
• Current Activity Limitations from LC (14.8M)
• Significant Limitations (4.4M)
Caption (in part):
Household Pulse Survey (HPS)…an Internet questionnaire…by…Census Bureau…includes questions regarding “any symptoms lasting 3 months or longer that you did not have prior to having coronavirus or COVID-19.” [Note] that the list of long-term symptoms, provided for this question, may not reflect all sequelae of covid infection, e.g., systemic organ damage or increased susceptibility to subsequent infections and other adverse health outcomes.
NCHS uses HPS responses to estimate incidence of [LC] in adult population. With [retraction & new studies] now assume U.S. under 18 population (22% of total) meet criteria for [LC] at same rate as adults.
Census…was due to relaunch Household Pulse Survey (HPS) as Household Trends and Outlook Pulse Survey (HTOPS)…January 2025….had been no relaunch as of [Jan 20].…now is word of a general moratorium on…executive branch agencies communicating with the public….](https://spaces.hcommons.social/media_attachments/files/113/870/658/138/972/137/original/930a3c6e6582500e.png "Chart: Estimates of Long Covid: Extrapolated to Entire U.S. Population
Data: Census Bureau, Nat'l Cntr for Health Stats, Dept of Health & Human Svcs, Bureau of Labor Stats (via FRED), CDC
[ beadsland on Ko-fi ]
Line chart, from Apr 2022 to date, of:
• Ever Experienced Long Covid for 3+ Months (60.3M as of Sep 16)
• Reported Staffed Hospital Beds (2.1K per Million) [Was 2.3K Apr '22]
• Population 16+ With a Disability — Labor Stats (34.8M) [Apr '22: 32.7M]
• Now Living with LC (17.9M)
• Current Activity Limitations from LC (14.8M)
• Significant Limitations (4.4M)
Caption (in part):
Household Pulse Survey (HPS)…an Internet questionnaire…by…Census Bureau…includes questions regarding “any symptoms lasting 3 months or longer that you did not have prior to having coronavirus or COVID-19.” [Note] that the list of long-term symptoms, provided for this question, may not reflect all sequelae of covid infection, e.g., systemic organ damage or increased susceptibility to subsequent infections and other adverse health outcomes.
NCHS uses HPS responses to estimate incidence of [LC] in adult population. With [retraction & new studies] now assume U.S. under 18 population (22% of total) meet criteria for [LC] at same rate as adults.
Census…was due to relaunch Household Pulse Survey (HPS) as Household Trends and Outlook Pulse Survey (HTOPS)…January 2025….had been no relaunch as of [Jan 20].…now is word of a general moratorium on…executive branch agencies communicating with the public….")
Those fuckers..
#maga #gop #usa #news #canada #cdnpoli #uspol #trump
https://www.washingtonpost.com/health/2025/01/21/trump-hhs-cdc-fda-communication-pause/
#covidisnotover #covidisairborne #sarscov2 #pandemic #longcovid #publichealth #eugenics #H5N1 #birdflu #uspoli https://zeroes.ca/@broadwaybabyto/113870230633066841
La bonne idée que de refaire son #introduction entre les nouvelleaux et les gens se mettent à me suivre parce que je shitpost sur la CAF
Je suis Zeph, je suis l'humain de Joy qui est mon compagnon depuis toujours (2021). Il aime les brocolis et prendre toute la place sur le lit. (et moi, il m'aime beaucoup, il chante quand je reviens à la maison)
J'écris des nouvelles, des novellas ; j'ai arrêté d'écrire des romans parce que c'est difficile avec ma façon de fonctionner et ma santé
Vous pouvez en trouver un peu ici :
https://zephdangles.wordpress.com/
ou ici en audio : https://radiopoivron.lithio.fr/podcast/entre-les-ecailles-eclot-lespoir/
J'aime bidouiller les choses avec mes mains, mais je sais pas toujours les remonter, alors je fais des bijoux avec des vieux trucs à la place de me lancer dans l'informatique
Je brode, je couds, je fais des colliers en chaine de bricolage des fois
J'aime beaucoup les corvidés (ici un corbeau freux), même les geais, et les oiseaux de façon générale. Le violet est ma couleur préférée, comme la lathrée clandestine, ma plante préférée.
Je parle beaucoup de handicap et de folie (vous pouvez notamment aller lire les trois articles sur la série Takin over the Asylum : https://zephdangles.wordpress.com/2024/01/15/takin-over-the-asylum-1-tracer-la-limite-entre-la-folie-et-les-sains-desprit/ ), des fois de covid (parce que c'est pas terminé et vous n'avez encore rien vu) parce que je bénévole chez @arra et vous pouvez retrouver une partie des trucs que j'y fais là :
https://associationarra.wordpress.com/ressources-rdr/
