beadsland,

NCHS estimates of —based on Household Pulse Survey—provide for volatile projections.

Census Bureau released most recent data mid-Sept—next update due this Wed.

As more and more folk experience Long Covid, fewer & fewer have been staffing our hospitals.

This is first toot of a weekly thread, updated daily, providing various dataviz of ongoing [.]

Last week: https://mastodon.social/@beadsland/111168110227106446

beadsland,

Capacity Level has been elevated since independence from the virus was declared two summers ago—as fewer and fewer professionals have been available to staff hospital beds.

Critical Staffing Level, already at 2021 levels, has been further elevated for months now—with over one in nine reporting hospitals at critical shortage.

❖

beadsland,

Pediatric staffing never recovered to pre-omicron levels. Rather, near one in six pediatric beds reported May of 2022: now missing. (There's been a very slight recovery in recent weeks.)

PICU Capacity Level (not shown): 70%.

Weekly average ~140 PICU beds were covid patients.

We're failing our kids. The emergency is over.

❖

beadsland,

Some 238 (+2) counties have pediatric care near or over capacity (≥ 90%).

Of 268 (+3) counties reporting any PICU capacity, over one in five are near or over full.

So many places where there ain't enough staff for sick or injured kids to receive required care.

❖

beadsland,

Counties by pediatric capacity (darkest counties on map above):

⒈ Seminole, GA ≥150%
⒉ Kenai Peninsula Borough, AK ≥133⅓%
⒊ San Juan, UT ≥133⅓%

⒋ Fairfax, VA—114%

Idaho—114%

⒌ Shelby, TN—102%

⒍ Collin, TX—100%
⒎ Bonneville, ID—100%
⒏ Anoka, MN—100%
⒐ Onslow, NC—100%
⒑ Salem city, VA—100%

❖

beadsland,

Counties by pediatric ICU capacity (circle-hatched on map above—counties with four or fewer PICU patients omitted):

⒈ Garland, AR ≥150%

⒉ Dane, WI—145%

⒊ Monroe, NY—102%

⒋ Jefferson, TX—100%
⒌ Brazos, TX—100%
⒍ Florence, SC—100%

⒎ Fulton, GA—98%
⒏ Marion, FL—98%
⒐ Lee, FL—98%
⒑ Nueces, TX—97%

❖

beadsland,

Some 51 (+10) counties ≥ 100% capacity per HHS data.

Reporting ≥ 90%: 204 (+11)—near 8½% of those with any capacity. This includes surge and overflow beds: near full can mean E/Rs with day-long wait times.

For counties w/ ICUs—over one in six are full or near full.

❖

beadsland,

Counties by adult hospital capacity (darkest counties on map above):

⒈ Berkeley, SC ≥150%
⒉ Chatham, GA ≥150%
⒊ Seminole, GA ≥150%
⒋ Charleston, SC ≥150%
⒌ Marshall, KY ≥150%

⒍ Scott, TN—144%
⒎ Smyth, VA—131%

⒏ Buchanan, MO—115%

⒐ Yuma, AZ—105%
⒑ Harlan, KY—105%

❖

beadsland,

Counties by adult ICU capacity (circle-hatched on map above):

⒈ Marshall, KY ≥150%
⒉ Chatham, GA ≥150%

⒊ Linn, OR—111%
⒋ Tazewell, VA—106%
⒌ Montgomery, AL—104%
⒍ Santa Cruz, CA—104%
⒎ Campbell, KY—101%

⒏ Lynchburg city, VA—100%
⒐ Jackson, MS—100%
⒑ Muskegon. MI—100%

❖

beadsland,

Twenty-third week of post-Kraken soup, CDC breaks out Kraken dot70 scion GK.1.1 & Eris EG.5.1 scion HK.3.

Near half of CDC estimate are Hyperion-2 XBB.1.9.2/EG family—new wave next week.

For 3-week GISAID sequences, now over ⅖; Hyperion 1.9.1/FL down to ⅛. Arcturus XBB.1.16 family down to over ⅕.

[Srcs: https://covid.cdc.gov/covid-data-tracker/#variant-proportions

https://public.tableau.com/app/profile/raj.rajnarayanan/viz/USAVariantDB/VariantDashboard]

❖

Chart: SARSCoV2 Variant Dashboard - USA | 21-DAY TRENDS Source: NYITCOM Research Report (Raj Rajnarayanan) Caption (in part): Circulating Variants in…following US States: All - Specimen Collected in…last 21 days | Updated on 10/13/23 3:46:13 AM [GMT?] | Source (sequences): GISAID Bubble chart showing tallies of each identified variant for each state. Data has been filtered to show dozens of Pangolin subvariants of XBB.1.9, including parent. Top subvariants: Eris descendant HV.1 (22.76%), Fornax FL.1.5.1 (18.63%), Eris dot1 EG.5.1.1. (14.33%), Eris EG.5.1 (12.21%), Eris dot3 EG.5.1.3 (5.06%). Raj has standardized bubbles to pink (XBB.1.9.1*, incl. FL & HN), red (XBB.1.9.2*, incl. EG & HV), and grey (for other variants, here XBB.1.9.3+, incl. GD, and X* cross-variants), although some newer pango aliases may still be getting unique colors assigned by Tableau. Bubbles largest and most prominent for: FL.1.5.1 (pink) for New York (212), Florida and New Jersey; HV.1 (red) for New York (174), California (70), New Jersey and Virginia; EG.5.1.1 (red) for California (93), New York (75), Minnesota; EG.5.1 (red) for California (77) and New York (68); EG.5.1.4 (red) for New York; HK.3 (red with black text) for New York. Dozens of additional smaller bubbles for various variants and states. ALT-text by beadsland at ko-fi.

beadsland,

After 10 weeks, CDC has still no estimates for New Eng. and NW, drops Middle South again.

EG.5 near ³⁄₁₀ of samples in Mtn/Dakotas & SW; near ¼ in Gr Lks & Mid-Atlantic; around ⅕ in Lower Midwest, NY/NJ & Southeast.

HV.1 over ¼ in Mid-Atl; near ¼ L Midw. FL.1.5.1 near ¼ in NY/NJ.

[See toot above for variants CDC map color key & links to sources for charts.]

❖

Chart: SARSCoV2 Variant Dashboard - USA | 21-DAY TRENDS Source: NYITCOM Research Report (Raj Rajnarayanan) Caption (in part): Circulating Variants in…following US States: All - Specimen Collected in…last 21 days | Updated on 10/6/23 3:07:10 AM [GMT?] | Source (sequences): GISAID Bubble chart showing tallies of each identified variant for each state. Data has been filtered to show over twelve dozen Pangolin subvariants, excluding XBB.1.9.* lineages. Top subvariants: Arcturus dot6 XBB.1.16.6 (18.54%), Arcturus XBB.1.16 (5.55%), and Arcturus dot11 XBB.1.16.11 (5.26%). Raj has standardized bubbles to orange (Kraken XBB.1.5.

beadsland,

This week, added another two hundred lines to library—mostly refactoring stacked pie chart class hierarchy: functionality to later be utilized in a secondary variant proportions by HHS region reskin.

Refactoring and new features for area-chart capacity & levels choropleth dataviz still planned for the coming weeks, along with scripts for working with CDC Wonder mortality data, and resumption of work on the variants proportions reskin.

Chart: Annoplot Dataviz Library*: Project Profile Subtitle: 7.1K lines† across component modules and significant submodules. Multi-level pie chart organized into five major categories by color. Each outer wedge shows a tally of the number of lines for that sub-component. Green wedges for "devpie" and "variants" sub-components, together with blue "artists" wedge, largely exploded out from chart; grey wedges exploded out less so. A few other wedges are very slightly outward. Caption: * Pre-release development version 2023-10-14 † Python, Markdown, and C source files. Blank lines omitted form tallies. Exploded wedges reflect proportions of lines changed in last 30 days. Dotted areas represent non-blank comment lines and Markdown. Wedges: 🔴 levels 🧀 [blank wedge] - 474 🧀 hospitals - 280 🟣 chirp 🧀 [blank] - 284 🧀 audio - 241 🔵 annoplot 🧀 [blank] - 503 🧀 artist - 504 🧀 artist/text - 259 🧀 coord - 586 🧀 coord/base - 228 🧀 margin - 246 🧀 util - 424 🟢 tiop 🧀 [blank] - 188 🧀 bullseye - 321 🧀 capacity - 455 🧀 devpie - 416 🧀 devpie/slice - 201 🧀 variants - 86 🧀 variants/orchard - 330 🧀 variants/plot - 205 🧀 variants/tree - 380 ⚫ . [a period by itself] 🧀 [blank] - 291 🧀 [blank] - 244 TODO.md

beadsland,

Folk are dying at record numbers, of comorbidities of severe acute covid that are also implicated as post-acute sequelae of covid infection. ↺

Of course, ongoing hospital staffing attrition also contributes to elevated death tolls. Said attrition continues. ↺

[CDC ended excess death reporting Sep 27.]

❖

Chart: Elevated Non-Circulatory Causes of Death: Annualized Dev. from 2015-2019 Avg Data: CDC, Census. Reflects death certs that do not identify covid as underlying cause. [ beadsland on Ko-fi ] Dashed lines 2015–20; solid dots for annualized Jan 2021–June 2023. [Six weeks incomplete data omitted.] Dotted lines for trends from Jan 2020 forward, for each disease category. Dash-dot line for sepsis trend had concerted effort at reduction in 2019 not occurred. Legend: • Diabetes (+10K more annualized deaths vs. 2019) • Alzheimers and dementia (+18K) • Renal failure (+5K) • Sepsis (+4K) • Malignant neoplasms (+14K) • Projected U.S. 65+ population Caption: After spiking in first year of the pandemic, annualized Alzheimer disease and dementia mortality dropped just as swiftly, thereafter remaining near or below historical trend. Diabetes mortality has not been so quick to recover from first year spike, only beginning to decline in the second half of last year, though still well above pre-pandemic trend. Deaths by sepsis were markedly down in 2019, following a coordinated national effort by hospitals. Despite this, sepsis mortality has been climbing at a rate well above even pre-2019’s relatively flat trendline, for over three years now. Renal failure deaths didn’t see an appreciable climb until the latter part of 2021, peaking only months ago. Meanwhile, malignant neoplasm (cancer) deaths, slower to manifest, have been suggestively creeping above trend for well over a year.

beadsland,

Given evidence linking covid infection to sudden onset liver damage, recent increased liver disease mortality is hardly surprising.

Final mortality data for 2020—released on Friday—reveals spike in accidental deaths driven by poisonings & exposure to noxious substances.

[CDC data for 2021 due this year.]

❖

Chart: Causes of Accidental Deaths: Reported Annual Data Data: National Center for Health Statistics [ beadsland on Ko-fi ] Dashed lines for annual data for years 2015 through 2020. Chart is blank 2021 to 2022. Legend: • Accidental poisoning and exposure to noxious substances (up 32.9% btw. 2019 & 2020) [~87K total in 2020] • Motor vehicle accidents (up 8.4%) [42K] • Falls (up 6.8%) [42K] • Accidental hanging, strangulation, and suffocation (down -4.1%) [7K] • Accidental drowning and submersion (up 13.1%) [4K] • Accidental exposure to smoke, fire, and flames (up 9.6%) [3K] • Accidental discharge of firearms (up 10.1%) [½K] • All other unintentional injuries (down -1.2%) [15K] [A table below the legend ranks these items by rate of change.] Captions: Historically, U.S. health authorities have published “Final Data”—detailed tables and demographic analysis of causes of mortality—about eighteen months, give or take, from the close of each calendar year. It took nearly thirty-three months to release final data for 2020. Data for 2021 remains significantly overdue. ---- Despite popular conjecture, the observed sharp increase in accidental deaths between 2019 and 2020 was not due to motor vehicle accidents. Rather, accidental poisonings—up by a third over the prior year—account for nearly all the increase in elevated deaths by accidental causes.

beadsland,

Per WHO, every 12 minutes four people die of acute covid. Three of those deaths are in the United States.

Entering April, for every three covid deaths, U.S. saw another excess death not attributed to covid.

The emergency is over—covid is not done with us.

[Share of deaths stalls again with low reporting.]

❖

Chart: U.S. Share of 28-Day Covid Deaths Data: WHO (via Our World in Data), NCHS (via CDC), official srcs (via Wikipedia) [ beadsland on Ko-fi ] Shows covid 28-day mortality as reported for the U.S. as share of G8, G20, and global 28-day mortality, for 3 years through Sept. 24, 2023, this being the most recent date on which at least 50% of world population was represented in weekly reporting (see note regarding ◇ data points, below). Share of population for each comparison is provided for reference. With the end of PHE aggregate tracking, U.S. ceased reporting covid deaths to WHO. After 5/14/23, chart uses provisional covid deaths from NCHS. ◇ data points represent sum population (via Wikipedia) of those countries that reported at least one death in prior week, as percentage of world pop. [Down to near 60% as of July. Was 90% last August.] 7-day avg of U.S. share of G8 covid deaths at 85.4%, on an upward trajectory, well exceeding share of pop. (~38%). Same date last year, share of G8 covid deaths was 43.1%, jaggedly climbing toward winter. Avg. U.S. share of G20 covid deaths now 64.9% (vs. ~7% of G20 population). Same date last year: 25.4%. U.S. share of global parallels: now 65.0% (vs. ~4% of pop.). This date last year, U.S. share of global covid deaths was 23.6%. All three metrics were near or below respective populations roughly May–Aug 2021; thereafter have been profoundly higher than population but for few troughs, including a data dump by China in May 2023.

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