The ranking tables do reflect where COVID hit hard in 2020 — the spring 2020 wave in the northeast, and the summer 2020 wave along the south and southwest (Texas, in particular). No, Florida didn’t show its big COVID impact until January 2021, so it’s pretty far down on this ranking table.
This way, we can see if there are any geographic patterns. We did know the hot spots of NY, NJ, IL (mainly around Chicago), DC, TX, Louisiana (around New Orleans), Arizona. I had not been aware of Mississippi being so bad, but maybe that was spillover from New Orleans.
The numbers below each cause are the total number of finalized deaths in CDC Wonder as of 11 January 2022 for the completed calendar year 2020.
COVID deaths for under age 15 weren’t in the top 10 causes for those age groups, which is why they aren’t seen in the table. But you may be interested in those numbers: at #12 for ages 5-14, with 49 deaths at #12 for ages 1-4, with 19 deaths at #13 for infant mortality (<1 year), at 35 deaths
In general, other than the new cause of COVID, most of the causes of death were in the same rank order as in 2019, with a few switches for causes that tend to be close in numbers.
Productivity gains in consumer electronics have not been able to exceed the erosion of the currency’s value.
Bills such as Build Back Better are just a piece of the reason — we have more coming. We have a huge demographic issue, and a huge Social Security and Medicare bill not yet paid. Shoveling out more money and writing more IOUs will not help matters.
You may have heard statistics in the news that most of the people testing positive for COVID, currently, in a particular location, or most of the people hospitalized for COVID, or even most of the people dying of COVID were vaccinated! How can that be? Does that prove that the vaccines are ineffective? Using real-world data, the speaker, Mary Pat Campbell, will show how these statistics can both be true and misleading. Simpson’s Paradox is involved, which has to do with comparing differences between subgroups with very different sizes and average results. Simpson’s Paradox actually appears quite often in the insurance world.
I will embed a recording of the event, copies of the slides, the spreadsheets, and the links from the talk.
As noted earlier, the Hispanic excess mortality was about a level as the other non-White groups, but then spiked with Wave 2 and stayed very high.
The Asian group saw its excess mortality peak with Wave 3 — remember, that’s the large wave with the most COVID deaths. But they have been at about 30 – 35% excess mortality for the other waves.
The Black group looks like it’s slightly rising in excess mortality, but staying within a fairly narrow range of about 33% to 37% excess mortality.
The White group is definitely showing an increasing trend of excess mortality. Interesting.
Due to the White group’s increasing excess mortality, the overall population is showing an increasing trend — look, Whites have been the majority of deaths for a long time, as they’re the majority of old folks. That’s how that works.
And now you can see it — the blue curve for Hispanics has a summer 2020 peak much higher than that for whites, Blacks, and Asians.
I want to note the high peak for Asian deaths in winter 2020-2021.
See that there is a high spike for Asian, Hispanic, and Black in that first NYC-centered wave that we’ve known so well… but a little blip for White. And I want you to think about that a little. Because that really explains a lot of the disproportionate effects on minorities in the U.S. and it goes back to Charles Blow’s question at the top of this post.
The answer to all of this being geographic distribution.
Both Chicago Police and Chicago Fire plans have active-to-beneficiary ratios of about 90%, and have been at that level for some years. Chicago Police, specifically, had such a ratio starting in 2012.
So, there are more people taking police pensions than are active employees already. If I take the numbers given, and shift 38% from active to beneficiaries, that gives one an active-to-beneficiary ratio of 52% (assuming you don’t get new actives, which you would, but still… this is a point-in-time estimate).
I will put a few facts in front of you, and you think it through: – The population age 85+ in the U.S. in 2020 was 6.3 million – Through July 2021, there were a little over 180K COVID deaths for that group – That’s about 3% of the age 85+ population
Do you think only 3% of the age 85+ population is vulnerable to COVID?
Pretty much all of them are “vulnerable”. The mortality rate for people age 85 (much less older) was 7.3% for females and 9.5% for males in the most recently available tables. It only goes up from there.
There is a huge difference in mortality by age for just non-pandemic years, and it’s also true for COVID.
There may be a few hardy souls with a base risk similar to the middle-aged without vaccines, but the percentage is not high.
The vaccines have been having an effect in cutting risk.
One large benefit of a tile grid map is you can see the geographically small states, which are often more obscured when you a geographically accurate map.
When viewed in this way, with the states colored by their grades, you can see that there’s a Northeastern Rogue’s Gallery, in addition to the expected stinkers of Illinois, Kentucky, and California (also, Hawaii, but many people don’t expect that one.)
But I want to point out that a lot of “red” states, in the political sense, also have crappy finances.
Texas is a particularly bad offender here, with a taxpayer deficit of -$13,100 per taxpayer. It’s not just the “expected” states where pensions are grossly underfunded — mind you, pretty much every single taxpayer sinkhole here has grossly underfunded state-level pensions — but it is a widespread problem.
So, period life expectancy dropped about 12 – 13% in 1918 in the U.S., mainly due to the Spanish flu, because there was an outsized effect from young adults being the main group killed by the disease (also, period life expectancy was relatively short — under 60 years!). That was a drop of about 7 years.
But life expectancy dropped only about 1 year in 2020 due to COVID impacts, and that was a decrease of less than 3% compared to 2019.
So if you want to compare the effect of the Spanish flu vs. COVID-19 on the U.S. population, all of these rates —- percentage change in period life expectancy, age-adjusted death rates, or even crude death rate — are all more reasonable choices than simply number of people who died.
Through the mechanism of the Trust Fund, Congress can put off having to act on the fundamental demographic problem that they can’t do much about. They hope they can run the Magic Money Machine to cover all the goodies they want, and in 2034, the Boomers will mostly be over age 80. Maybe another pandemic will deal with them….
(and nobody cares about us Gen Xers. In 2034, I won’t even be eligible for Social Security old age benefits.)
Nobody expects the Social Security benefits to be cut in 2034, or whatever other magic date when the Trust Fund runs out. The only thing the current Trust Fund mechanism requires is cuts… only if Congress doesn’t actually pass legislation to “fix” the issue.
They have been doing ad hoc “fixes” to Medicare and other parts for years so as to avoid massive cuts.