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Two Years of COVID in 45 Seconds

Mina

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Since different states used different standards when deciding when to attribute deaths to COVID, using their self-reported numbers can be misleading. But where we can do a clear comparison is in terms of how much mortality was elevated in each place, during the pandemic. If, for example, in the five years before COVID an average of 1% of the population died per year, and then during COVID it was an average of 1.25%, that's a 25% elevation of mortality.

Using that method, I put together a visualizer that allows you to watch two years of COVID play out over 45 seconds, with the cumulative percentage of excess mortality for each state.

You can see that early on states like NJ, NY, and CT got hit hardest. Over time, though, other states wound up moving ahead. Eventually, looking at a two-year period from the start of April 2020 to the end of March 2022, AZ, MS, and TX wound up having the worst cumulative performance:

https://public.flourish.studio/visualisation/9658616/

<div class="flourish-embed flourish-bar-chart-race" data-src="visualisation/9658616"><script src="https://public.flourish.studio/resources/embed.js"></script></div>

It's most interesting when you go to the site and watch the full animated "race," so you can see different states rise and fall over time (as policy gradually and cumulatively trumped dumb luck), but here's a screen shot from the end, to give you a feel for it:

1651169668278.png
 
Since different states used different standards when deciding when to attribute deaths to COVID, using their self-reported numbers can be misleading. But where we can do a clear comparison is in terms of how much mortality was elevated in each place, during the pandemic. If, for example, in the five years before COVID an average of 1% of the population died per year, and then during COVID it was an average of 1.25%, that's a 25% elevation of mortality.

Using that method, I put together a visualizer that allows you to watch two years of COVID play out over 45 seconds, with the cumulative percentage of excess mortality for each state.

You can see that early on states like NJ, NY, and CT got hit hardest. Over time, though, other states wound up moving ahead. Eventually, looking at a two-year period from the start of April 2020 to the end of March 2022, AZ, MS, and TX wound up having the worst cumulative performance:

https://public.flourish.studio/visualisation/9658616/

<div class="flourish-embed flourish-bar-chart-race" data-src="visualisation/9658616"><script src="https://public.flourish.studio/resources/embed.js"></script></div>

It's most interesting when you go to the site and watch the full animated "race," so you can see different states rise and fall over time (as policy gradually and cumulatively trumped dumb luck), but here's a screen shot from the end, to give you a feel for it:

View attachment 67387936

Awesome work, Mina.

Thanks for this!
 
Since different states used different standards when deciding when to attribute deaths to COVID, using their self-reported numbers can be misleading. But where we can do a clear comparison is in terms of how much mortality was elevated in each place, during the pandemic. If, for example, in the five years before COVID an average of 1% of the population died per year, and then during COVID it was an average of 1.25%, that's a 25% elevation of mortality.

Using that method, I put together a visualizer that allows you to watch two years of COVID play out over 45 seconds, with the cumulative percentage of excess mortality for each state.

You can see that early on states like NJ, NY, and CT got hit hardest. Over time, though, other states wound up moving ahead. Eventually, looking at a two-year period from the start of April 2020 to the end of March 2022, AZ, MS, and TX wound up having the worst cumulative performance:

https://public.flourish.studio/visualisation/9658616/

<div class="flourish-embed flourish-bar-chart-race" data-src="visualisation/9658616"><script src="https://public.flourish.studio/resources/embed.js"></script></div>

It's most interesting when you go to the site and watch the full animated "race," so you can see different states rise and fall over time (as policy gradually and cumulatively trumped dumb luck), but here's a screen shot from the end, to give you a feel for it:

View attachment 67387936
Wonder how the red states are going to explain this one?
 
Awesome work, Mina.

Thanks for this!
My pleasure. I get a real kick out of data visualizations, when they help to reveal patterns that might not have otherwise been clear.

In this case, I think it's really helpful to see the way that certain highly-networked, densely populated states got thrashed early on, when the virus first showed up and we knew almost nothing about preventing infection (e.g., the focus was still on fomites, not airborne transmission), much less treatment (doctors had few medicines known to work). Those places got hit first and had no clue how to protect themselves, and their dense populations set them up for catastrophe. Gradually, though, as the virus saturated even the remote parts of the country, and as we had more knowledge and tools to prevent infection and help people recover, the states started to sort themselves by their partisan tendencies. Policy came to matter more than population density, age, or the luck of who got hit first.

Massachusetts, for example, was the third-worst state, when viewed in late June 2020. But then it underwent such a long period of mortality actually being lower than normal that eventually it wound up the third-best state, considering the whole two-year period. And Texas went the other way -- starting out in pretty good shape, then winding up as one of the very worst when you took the two-year period as a whole.
 
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My pleasure. I get a real kick out of data visualizations, when they help to reveal patterns that might not have otherwise been clear.

In this case, I think it's really helpful to see the way that certain highly-networked, densely populated states got thrashed early on, when the virus first showed up and we knew almost nothing about preventing infection (e.g., the focus was still on fomites, not airborne transmission), much less treatment (doctors had few medicines known to work). Those places got hit first and had no clue how to protect themselves, and their dense populations set them up for catastrophe. Gradually, though, as the virus saturated even the remote parts of the country, and as we had more knowledge and tools to prevent infection and help people recover, the states started to sort themselves by their partisan tendencies. Policy came to matter more than population density, age, or the luck of who got hit first.

Massachusetts, for example, was the third-worst state, when viewed in late June 2020. But then it underwent such a long period of mortality actually being lower than normal that eventually it wound up the third-best state, considering the whole two-year period. And Texas went the other way -- starting out in pretty good shape, then winding up as one of the very worst when you too the two-year period as a whole.
This one is 10 years old (which means it is probably way worse now), but I think you'll enjoy it.
 
This one is 10 years old (which means it is probably way worse now), but I think you'll enjoy it.

I remember seeing that one a few years back. Very interesting.
 
Wonder how the red states are going to explain this one?
Well, they'll blame excess mortality on lockdowns. Suicide increase, lack of access to healthcare, etc. Which IMO is still covid-related but spinners gotta spin.
 
Well, they'll blame excess mortality on lockdowns. Suicide increase, lack of access to healthcare, etc. Which IMO is still covid-related but spinners gotta spin.
Except the states with the strictest lockdowns and mask mandates all settled to the bottom over time and the states that resisted lockdowns and mandates all floated to the top.
 
Since different states used different standards when deciding when to attribute deaths to COVID, using their self-reported numbers can be misleading. But where we can do a clear comparison is in terms of how much mortality was elevated in each place, during the pandemic. If, for example, in the five years before COVID an average of 1% of the population died per year, and then during COVID it was an average of 1.25%, that's a 25% elevation of mortality.

Using that method, I put together a visualizer that allows you to watch two years of COVID play out over 45 seconds, with the cumulative percentage of excess mortality for each state.

You can see that early on states like NJ, NY, and CT got hit hardest. Over time, though, other states wound up moving ahead. Eventually, looking at a two-year period from the start of April 2020 to the end of March 2022, AZ, MS, and TX wound up having the worst cumulative performance:

https://public.flourish.studio/visualisation/9658616/

It's most interesting when you go to the site and watch the full animated "race," so you can see different states rise and fall over time (as policy gradually and cumulatively trumped dumb luck), but here's a screen shot from the end, to give you a feel for it:
FASCINATING! It's easy to understand how and why the states with more foreign traffic, and higher population density, would spike early on in the pandemic. But the only explanation for them being eclipsed in mortality by the more rural states is that those states must be ineducable. The examples clearly existed for them to follow, and they just wouldn't learn.

Epidemiologists will be studying this for decades.
Thanks for that compilation, Mina.
 
Except the states with the strictest lockdowns and mask mandates all settled to the bottom over time and the states that resisted lockdowns and mandates all floated to the top.

I didn't say it made sense, I just noted that it might be one of their explanations.

I've also seen people dismiss excess deaths because many of the dead were old or sick and going to die soon anyway. Yikes.
 
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Interesting that NM was the highest blue state. Having AZ and TX for neighbors the cause?
 
Well, they'll blame excess mortality on lockdowns. Suicide increase, lack of access to healthcare, etc. Which IMO is still covid-related but spinners gotta spin.
The great thing about this data is that it's a reality check on that spin. If lockdowns were what was driving this, then we'd expect the worst states to be those that had the tightest COVID controls -- places like Hawaii and NY. And we'd expect that best states to be those that basically took a laissez-faire approach, like Texas. The data doesn't actually support that.

Moreover, suicide rates actually DECLINED in 2020, whereas if lockdowns were driving more suicide and suicide was driving the higher mortality, then of course we'd expect suicide to have been up in 2020, when lockdowns were tightest. Plus, when you dig into the data, the high suicide rates were in places like Wyoming and Alaska, not states with tight lockdowns.

This gets at a problem I have with the right-wing approach to things. They start with their conclusion (e.g., "lockdowns bad.") Then they assert things that they'd like to be true in order to support their starting conclusion (e.g., "lockdowns spiked suicide rates"), without even thinking of doing the research to see if that's actually true. It's exactly backwards. They should be going to the data first, to figure out what happened, then forming their beliefs based on that.
 
FASCINATING! It's easy to understand how and why the states with more foreign traffic, and higher population density, would spike early on in the pandemic. But the only explanation for them being eclipsed in mortality by the more rural states is that those states must be ineducable. The examples clearly existed for them to follow, and they just wouldn't learn.

Epidemiologists will be studying this for decades.
Thanks for that compilation, Mina.
Yes, my take on it is the same as yours. I think that early on, circumstance was the driving factor. But over time, we had more and more tools to deal with the virus, and so willingness to actually use those tools effectively became the driving factor. It wasn't the ONLY factor, of course, I'm sure epidemiologists will identify all sorts of interesting things over time. But I think there's a pretty compelling case that the states that took the virus more seriously eventually ended up saving a lot of lives.

One thing to stop and consider is just how many lives we're talking about there. Take Texas as an example. Based on pre-pandemic mortality rate averages, Texas should have suffered around 427,978 deaths during those two years. Instead, it was 539,228 (thus, about 26% excess deaths.) Now imagine if it had done as well as, say, Massachusetts -- about 9% excess deaths... not particularly great in global terms, but clearly achievable for a large and diverse US state, since it's what Massachusetts managed. Well, then, that would mean "only" 466,496 people would have died in Texas during those two years: 71,732 fewer than actually died.

As you can see, we're not talking about subtle differences of a few lives here or there. We're talking the equivalent of Texas suffering a 9/11-magnitude terrorist attack every single month for two years... just in terms of the extra deaths it endured above what it would have had with Massachusetts-like performance. To put it in brutally vulgar terms, the damage Greg Abbott did to Texas was about 24 times as bad as the damage Osama Bin Laden did to the US.
 
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Since different states used different standards when deciding when to attribute deaths to COVID, using their self-reported numbers can be misleading. But where we can do a clear comparison is in terms of how much mortality was elevated in each place, during the pandemic. If, for example, in the five years before COVID an average of 1% of the population died per year, and then during COVID it was an average of 1.25%, that's a 25% elevation of mortality.

Using that method, I put together a visualizer that allows you to watch two years of COVID play out over 45 seconds, with the cumulative percentage of excess mortality for each state.

You can see that early on states like NJ, NY, and CT got hit hardest. Over time, though, other states wound up moving ahead. Eventually, looking at a two-year period from the start of April 2020 to the end of March 2022, AZ, MS, and TX wound up having the worst cumulative performance:

https://public.flourish.studio/visualisation/9658616/

<div class="flourish-embed flourish-bar-chart-race" data-src="visualisation/9658616"><script src="https://public.flourish.studio/resources/embed.js"></script></div>

It's most interesting when you go to the site and watch the full animated "race," so you can see different states rise and fall over time (as policy gradually and cumulatively trumped dumb luck), but here's a screen shot from the end, to give you a feel for it:

View attachment 67387936
Interesting that my state "Pennsylvania" basically stayed in the middle lower middle.
 
Interesting that NM was the highest blue state. Having AZ and TX for neighbors the cause?
That surely factored in. Other possible contributing causes:

(1) It's poor for a blue state, meaning fewer resources to throw at the problem (though that didn't hurt some other poor blue states, like Maine).
(2) It has a very high Native American population (people with mostly Native-American ancestry seem to have been more susceptible to the virus).
(3) It has low humidity -- generally speaking low humidity is bad for controlling a respiratory illness, since droplets travel farther, and people are more likely to have small cracks in their sinuses.
 
Since different states used different standards when deciding when to attribute deaths to COVID, using their self-reported numbers can be misleading. But where we can do a clear comparison is in terms of how much mortality was elevated in each place, during the pandemic. If, for example, in the five years before COVID an average of 1% of the population died per year, and then during COVID it was an average of 1.25%, that's a 25% elevation of mortality.

Using that method, I put together a visualizer that allows you to watch two years of COVID play out over 45 seconds, with the cumulative percentage of excess mortality for each state.

You can see that early on states like NJ, NY, and CT got hit hardest. Over time, though, other states wound up moving ahead. Eventually, looking at a two-year period from the start of April 2020 to the end of March 2022, AZ, MS, and TX wound up having the worst cumulative performance:

https://public.flourish.studio/visualisation/9658616/

<div class="flourish-embed flourish-bar-chart-race" data-src="visualisation/9658616"><script src="https://public.flourish.studio/resources/embed.js"></script></div>

It's most interesting when you go to the site and watch the full animated "race," so you can see different states rise and fall over time (as policy gradually and cumulatively trumped dumb luck), but here's a screen shot from the end, to give you a feel for it:

View attachment 67387936
Also interesting that in the beginning blue states were fairing much worse, but as it progresses red states were doing worse.
 
Interesting that my state "Pennsylvania" basically stayed in the middle lower middle.
I find that kind of surprising. I would have expected average performance. I think of PA as really "average," in the sense that it's near the border between red and blue states, in voting terms (e.g., it went for Trump once and against him once). It's kind of the Arlen Specter of states. And it's also pretty average in terms of how urban or rural it is -- with some big cities and also really rural areas. It's pretty average in terms of income, and how white it is, and education level, and so on. But when it comes to performance during the pandemic, it clearly ranks among the better states.... not alongside the elite, but a lot better than the national average.
 
Also interesting that in the beginning blue states were fairing much worse, but as it progresses red states were doing worse.
You especially see the switch after vaccines started to be widely available. Generally, the blue states had the challenge of higher population density, which makes blocking transmission harder (like how do you avoid exposure if you're in NYC and you need to be in elevators half the day just to get around?) But once the vaccines came along, they gave everyone a tool to use to protect their people, and the blue states used that tool in higher rates, and it ended up mattering a lot more than population density.
 
I find that kind of surprising. I would have expected average performance. I think of PA as really "average," in the sense that it's near the border between red and blue states, in voting terms (e.g., it went for Trump once and against him once). It's kind of the Arlen Specter of states. And it's also pretty average in terms of how urban or rural it is -- with some big cities and also really rural areas. It's pretty average in terms of income, and how white it is, and education level, and so on. But when it comes to performance during the pandemic, it clearly ranks among the better states.... not alongside the elite, but a lot better than the national average.
I can only speak with the area I live in, but I don't see a ton of militant Republicans or militant Democrats. There does seem to be a level of open-mindedness where I live. Now, to be honest, where I live, and where I grew up (both in the state), you would RARELY see a President EVER come to us, so there is a level of "they don't care about us, why should we care about them"
 
What is particularly damning is that a lot of the states that performed poorly have low population densities.
 
My pleasure. I get a real kick out of data visualizations, when they help to reveal patterns that might not have otherwise been clear.

In this case, I think it's really helpful to see the way that certain highly-networked, densely populated states got thrashed early on, when the virus first showed up and we knew almost nothing about preventing infection (e.g., the focus was still on fomites, not airborne transmission), much less treatment (doctors had few medicines known to work). Those places got hit first and had no clue how to protect themselves, and their dense populations set them up for catastrophe. Gradually, though, as the virus saturated even the remote parts of the country, and as we had more knowledge and tools to prevent infection and help people recover, the states started to sort themselves by their partisan tendencies. Policy came to matter more than population density, age, or the luck of who got hit first.

Massachusetts, for example, was the third-worst state, when viewed in late June 2020. But then it underwent such a long period of mortality actually being lower than normal that eventually it wound up the third-best state, considering the whole two-year period. And Texas went the other way -- starting out in pretty good shape, then winding up as one of the very worst when you took the two-year period as a whole.

Agreed.

The states that caught the latter waves had already benefited from the knowledge & protections gained from the initial infections.

Which is why it's a poor reflection those latter states still suffered much the same fate as the earlier states. In fact, despite their sometimes incompetence it might be argued the latter states simply got 'lucky'!
 
Agreed.

The states that caught the latter waves had already benefited from the knowledge & protections gained from the initial infections.

Which is why it's a poor reflection those latter states still suffered much the same fate as the earlier states. In fact, despite their sometimes incompetence it might be argued the latter states simply got 'lucky'!
Yep. You can see it abroad, too. Like it's hard to blame Italy for how badly things went at first. It got nailed first in Europe, and had to figure things out on the fly. Of course things were going to go badly for them. But by the time significant numbers of cases were showing up in Northern Europe, a lot more was known about COVID, giving them the tools to protect themselves. Some used those tools wisely, like Norway and Finland, and did really well. Others used it as an opportunity for political posturing and doomed their people to high excess rates of death, like Sweden.
 
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