I got a request from Henry to post all 50 states excess mortality numbers, both raw and percent above baseline for 2020 and 2021. This seemed a reasonable request, so I pulled it together. To note, data from the end of 2021 is still being compiled by some states. There were 7 that had notes that their data from the end of the year is likely still quite incomplete: Alaska, DC, North Carolina, Rhode Island, South Carolina, Utah and West Virginia. At least 2 of those states are currently showing a death drop, so that’s likely where that’s coming from.

The percent increase calculation changed slightly from my last post, so some of the numbers are slightly different – between 0-2% for 48 out of 54 districts, 3 or 4% for the other 6. Additionally, I used predicted deaths to try to compare in the last post, but here the 2021 numbers are actual reported. This means these numbers will only go up in subsequent weeks. I will probably redo this data in another month or two to see how the slow reporting states (and everyone else) changed.

With that out of the way, here’s the table. I bolded the data for the whole US, and highlighted any percent increase that was top 10 for the year. For 2021 it ended up being top 11 actually, as there was a 3 way tie for 9th. Data set was downloaded here this morning, and leave me any questions in the comments!

So my regular mortality data posting is going to be delayed, as unfortunately we’ve had two pretty close to home deaths within 10 days of each other. Neither were COVID related, but some deaths just make you feel like a light has gone out in the world. Both of these deaths were of that sort, and it’s going to be a dimmer Christmas without them.

Having lost two family members back to back, I’ve gotten the question a few times “was this expected?”. For one it certainly was, for the other not as much. But given that my stress response is often to look at numbers, I did get curious what the probability we were working with was at baseline.

I had posted the Social Security Administrations Actuarial table in one of my posts, so I turned there first. This pleasant little table is broken down by male/female and for each year of life gives you the chance you’ll die in the next year, the number of people (out of 100k) in your age cohort who are still alive, and the number of years you likely have left. All the data is for 2019, so COVID is not included here.

Graphing the probability of death in the next year, it looks like this:

Those seem like decent odds, especially since it’s not random. It is very likely that some chunk of the people in your age category who will die before their next birthday already know, or at least have some serious hints. Terminal cancer diagnoses, major medical events, etc, tend to give a little warning.

Do you want to get even more morbid while we learn about the power of compounding percentages? Good! Here’s the graph of how the death patterns will likely go for 100k people born the same year as you:

So if you are a man born in a particular year, you won’t lose your first 10k cohort members until you’re about 55. In the next decade by age 65, you’ll lose another 10k. The next 10k only take until 72, then 77, 81, 84, 87, 90, and at 94 there will be less than 10k left. For women those numbers are….why don’t I just put this in a table:

I’ve been talking a lot about excess mortality lately, so I wanted to post about something that’s much harder to quantify: the number of people being left with excess medical debt. While we know that nearly a million excess deaths have occurred in the past 2 years, what we don’t know is how many people required intensive/expensive medical care but didn’t end up dying.

Assuming that number is likely to be up as well, I’d like to point people to a great charity called RIP Medical Debt. They buy medical debt in bulk and pay it off for people, meaning your gift can go 10x as far as it usually would. They have a gift matching special going on today, and if this last 2 years has been good to you, please consider throwing something in. You never know who it could make a difference for.

Read more about them here.

Well hello there! Another month has flown right by, and it’s time for another US excess mortality update. I’ve actually spent my week arguing about Portugal’s death counts (substance use related, not COVID related), but that’s a story for another post.

It’s been quite the month, and I was interested to look back and realize that when I first started doing these posts in August, the estimates for excess mortality put us at between 595,688 and 758,749 excess deaths since 2/1/2020. As of the most recent data release earlier this week, the US is now somewhere between 791,202 and 962,125. The 1 million mark is getting pretty close. If you have questions about these numbers, see prior posts.

Excess Mortality in 20-50 year olds

After my last post, bluecat57 left me a few comments about the concerns about excess mortality specifically in the younger adult age ranges. These are concerning deaths because 1. They are on the rise and 2. There is debate where they are coming from. It will be a while until all the data is in, but here’s the US trend for deaths through the end of September:

So basically during the pandemic we gained about 600ish extra deaths in the 25-44 year old age range, with a sudden jump in July of this year that took us to about 1800 extra deaths every week over baseline.

One of the links went to a clip of someone speculating on the reasons for these deaths, with several possible explanations. One explanation is that this is COVID. One is that something else is killing young people. One was that the vaccines were killing younger adults. Now this was an interesting claim, as the timeframe doesn’t entirely match up. July was on the later side for most people getting vaccinated, but perhaps the claim is there’s a delay. I decided to take a look at my 3 states I go back to: Massachusetts, Arizona and Tennessee. These are interesting states because they are in 3 totally different areas of the country, and have very different vaccination rates. In Arizona, 53.7% of the population is fully vaccinated. In Massachusetts, 70.3% and in Tennessee it’s 48.8%. That’s of the total population (kids excluded until recently) so we can assume that translates in to a somewhat higher number for this slice of the population. So how are these states doing? Here you go:

Starting around May of 2020, Arizona and Tennessee show gains here, whereas Massachusetts does not. Per the state report, around 80% of 25-44 year olds in Massachusetts are vaccinated, and we do not see much of a gain (if any) in young person deaths. As someone in that age group, it is of course relieving to see that my risk of death is basically unchanged since 2019. In Arizona and Tennessee, there are points where your risk of death was 1.5-2x as likely.

It seems unlikely the vaccines are causing these deaths, when we see bigger spikes in more unvaccinated populations than in largely vaccinated ones. I wanted to compare these to the overall deaths in each state, so here is that:

Interesting that each spike in overall mortality correlates to a similar spike in 25-44 deaths except the initial Massachusetts spike. This backs up the theory that the very first COVID spike hit nursing homes hard, and that has not been as much of a problem since then. I was also interested to note that despite COVID appearing fairly seasonal, death rates for Arizona and Tennessee exceed those of Massachusetts last winter.

So basically, I think it’s unlikely that vaccines are playing a role. I would speculate many of these are COVID deaths, or something else potentially related to COVID. As far as I’m aware, Massachusetts had the toughest lockdowns/restrictions of the 3 states (though lockdowns have been done in MA for over a year, unless you count mask mandates as lockdowns) so I’d suspect it’s not lockdown related either. Let me know if you have evidence Tennessee or Arizona were tougher though, as I obviously know my own state better than those two.

Excess Mortality Over Average Updates

Okay, so here’s the visual:

Who moved the most this month? Not a lot of major changes

Of note, New York fell off the top ten list entirely, and currently sites at #17. It’s good to see the top states slowing down though, it’s been a tough go of it.

Most of the states with the biggest gains this month actually did not make the top 10. The top 5 gainers were Idaho (#32, +596), Puerto Rico (#31, +563), Montana (#13, +535), Kentucky (#12, +516) and Wyoming (#36, +500).

Excess Mortality Over Upper Bound by State

Graphical representation here:

Okay, here’s the top 10 list:

Again, not a lot of motion except for NY running off the list. This seems fairly consistent with a falling peak: states simply aren’t adding huge numbers at the moment. The biggest changes are again (mostly) coming in states that have actually had lower pandemic numbers up until now: Idaho (#29, +521), Puerto Rico (#40, +496), Kentucky (#15, +457), Montana (#23, +396), Tennessee (#8, +361).

Again, given the nature of COVIDs seasonal interaction here, I’m going to continue to keep this updated for at least Dec/Jan/Feb. With acquired immunity and vaccines going on, it’s hard to know if we’ll see a substantial 4th (or 5th, depending how you count) wave of deaths in the US. Stay healthy everyone!

I don’t often make New Year’s resolutions, but this year I’ve decided to join Gretchen Rubin (of happiness project fame) in resolving to go on a 20 minutes walk every day in 2020. Her theory is that if you aren’t getting much exercise, resolving to get a little bit daily will provide big benefits. She has research on her side on this one, and it doesn’t hurt that walking seems to be the only form of exercise that makes my migraines better rather than worse. We’ll see how this goes.

This got me thinking about New Year’s resolutions in general, and wondering what the most common ones were. there appears to be a lot of selection bias in the studies, but healthy eating/exercise/weight loss and saving money seem to be the most common in America.

I tried to find some from other countries, and it seems like Germans may put stress reduction and family time at the top of their list. My googling for other European and north and south American countries didn’t turn up much.

I did however, find this blog post from Duolingo, that had some really interesting insights about one particular New Year’s resolution. Duolingo is an app that helps you learn a second language, and they have a distinctive peak in sign ups and account usage just before the first of the year. They discovered that the countries their users normally came from changed a bit around the first of the year:

Apparently users who sign up around the first of the year actually are slightly more likely to continue using the app than those who sign up at other times.

Overall, I’ll admit I was a little surprised that I couldn’t find more research on the subject of New Year’s resolutions. It seems like this would be an interesting study in how priorities change across countries or time. If anyone knows of any good resources that I didn’t find, please let me know! In the meantime, happy new year everyone!