Two Years of COVID, by state

[Mina]

Hello Mina,



I would expect population density to be a factor. Greater density would lead to greater spread.

For instance, NJ has a high population density. And the double whammy of being hit early on.

Yes. It's so hard to control for these things, because different factors interact. Like we would completely expect higher population density to mean higher infection rates, since that's just how communicable diseases work. Yet higher density areas generally elect more Democrats, so if Democratic rule pushes the other way (towards lower infection rates), it's hard to disaggregate that data. Also, while high-density would be expected to mean more infections per capita, it would also be expected to mean fewer deaths per infection, since people are closer to high-quality hospitals.

Some day, no doubt, epidemiologists will have worked through these numbers and will understand much better what, exactly, happened. For now, though, it's awfully tough to tease out the details, because the data is in such rough shape -- e.g., different states testing at vastly different rates, which makes it hard to tell what the infect rate was in each. Like right now Vermont is doing about 600 tests per 100k per day, while PA is doing 26.4/100k. Obviously, a given rate of reported cases is going to mean something very different if you got it by testing less than one-twentieth as much as some other state.

 

[PoliTalker]

Hello Mina,

Yes. It's so hard to control for these things, because different factors interact. Like we would completely expect higher population density to mean higher infection rates, since that's just how communicable diseases work. Yet higher density areas generally elect more Democrats, so if Democratic rule pushes the other way (towards lower infection rates), it's hard to disaggregate that data. Also, while high-density would be expected to mean more infections per capita, it would also be expected to mean fewer deaths per infection, since people are closer to high-quality hospitals.

Some day, no doubt, epidemiologists will have worked through these numbers and will understand much better what, exactly, happened. For now, though, it's awfully tough to tease out the details, because the data is in such rough shape -- e.g., different states testing at vastly different rates, which makes it hard to tell what the infect rate was in each. Like right now Vermont is doing about 600 tests per 100k per day, while PA is doing 26.4/100k. Obviously, a given rate of reported cases is going to mean something very different if you got it by testing less than one-twentieth as much as some other state.

I like what the Mayo Clinic has done with their analysis. By now, COVID has gotten to the point where all regions have been exposed to one extent or another and, as you say, the reporting varies so widely that no one data stream really gives a good complete picture.

That's why I like what you've done by simply looking at the overall deaths from any source and assuming a significant rise during COVID years is due to COVID.

So now we have a situation where everyone is familiar with the disease, it has peaked and ebbed numerous times in many areas, and mostly, the levels are low and vaccinated people are protected, BUT...

There are still regional surges and people need to have good accurate localized information to act accordingly.

That's where the Mayo Clinic website comes in very handy.

It gives up to date COVID-by-County information in the form of an active map which can be moved backward in time to see how things in any area are progressing. The data is collected from numerous credible sources, so it is as accurate as any compilation could be.

This gives any website visitor the power to zero in on their own region, or any other region, and see both the current infection levels and the recent history. You can pin-point hot spots.

Mayo Clinic COVID-by-County Active Map

Simply enter your State or any other State in the dialog box and presto - you're in the know about your own local COVID risk. You'll get a State map showing all the counties and the infection levels according to color shades.

 

[PoliTalker]

Mina, you may appreciate what I've done with the Corona Virus Peak Watch Thread.

I taken data from Worldometer, which acquires data from numerous sources given at their website, and recorded their reporting nearly daily for the last two years in a thread here at JPP. That data presented at Worldometer scrolls off regularly, so the historical data becomes unavailable there. The thread I created allows us to look back at that, at what was reported for the USA on almost any day of the pandemic.

It has been interesting to watch the parameters change over time. First, the New Cases rise. Then, the number of Serious and Critical Cases rise, finally followed by a rise on New Deaths.

It is possible to see very clearly that after the advent of the vaccines the numbers of deaths is reduced compared to the number of cases.

 

[Mina]

Hello Mina,



I like what the Mayo Clinic has done with their analysis. By now, COVID has gotten to the point where all regions have been exposed to one extent or another and, as you say, the reporting varies so widely that no one data stream really gives a good complete picture.

That's why I like what you've done by simply looking at the overall deaths from any source and assuming a significant rise during COVID years is due to COVID.

So now we have a situation where everyone is familiar with the disease, it has peaked and ebbed numerous times in many areas, and mostly, the levels are low and vaccinated people are protected, BUT...

There are still regional surges and people need to have good accurate localized information to act accordingly.

That's where the Mayo Clinic website comes in very handy.

It gives up to date COVID-by-County information in the form of an active map which can be moved backward in time to see how things in any area are progressing. The data is collected from numerous credible sources, so it is as accurate as any compilation could be.

This gives any website visitor the power to zero in on their own region, or any other region, and see both the current infection levels and the recent history. You can pin-point hot spots.

Mayo Clinic COVID-by-County Active Map

Simply enter your State or any other State in the dialog box and presto - you're in the know about your own local COVID risk. You'll get a State map showing all the counties and the infection levels according to color shades.

At one point I tried to come up with my own "Risk Index." The idea was to back-test reported data versus excess deaths, in order to figure out what's really going on under the surface.

Just to simplify, picture that there was an average three-week delay between testing positive for COVID and dying from it. Well, then, using excess death data by week and comparing it to positive tests three weeks earlier, you could figure out how many reported cases, average, equate to one statistical COVID death. Then, you could see how much each state is above or below that average (more or fewer excess deaths than we'd expect from the number of infections they report). Then I'd compare that to testing rates and positivity rates, to get an index.

The idea would be to allow you to look at a state's positive case count, testing rate, and positivity rate, and then use that to calculate a "true infection rate" (based on adjustments driven by those other factors). Like, for example, maybe NY and AZ are both reporting 40 cases/100k/day. But if NY is doing three times as many tests and has 1/2 the positivity rate for those tests, It's reasonable to think AZ actually has a lot more infections and just is catching and reporting fewer. Using the method I'm talking about, the idea would be that you could use historical patterns to "norm" that data. Maybe, for example, you'd expect that in reality NY is suffering 50 cases/100k/day, while AZ is suffering 100 cases/100k/day, meaning your true risk in NY is twice as high.

That would allow you to properly assess what the true risk is in given place in a given time (also within cities or counties). Unfortunately, though I messed around with the numbers for a while, I never found a formula I was confident about (one that would consistently predict excess deaths fairly accurately based on those other factors). Maybe I'll take another run at it, at some point, now that there's more historical data to work with.

 

[Althea]

Basically, they come at these things backwards. Rather than looking at the evidence and deciding on a policy based on that, they decide what policy they support first (government not taking any steps), and then they hop from one assertion to another, to try to support that policy.... even if it leads them from making one point to making nearly the opposite point. The evidence is beside the point, except to the extent they think it can be used as a talking point for the pre-ordained policy prescription.

And let's not forget what the lobbyists want, as well as the MAGA base.

No policy is decided based on what is best for the nation.

 

[Althea]

Hello Althea,



A completely accurate and appropriately ridiculing assessment.

The problem is that Trump has set the example of how being deplorable can get votes and now we have all these mini-Trumps running around trying to out-Trump Trump. The Republican Party has become deplorable.

Bingo

 

[LV426]

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>

Fascinating. Wondering if it could be broken out on a county level since a lot of the deaths in CA happened in the red parts of the state.

 

[LV426]

You might note, that two groups in AZ got hit hardest: Native Americans and Hispanics. I'd note that Native Americans also got hit very hard during the 1918 Spanish Influenza epidemic. The reason for that in their case is they live in relative isolation to the general population so have less exposure to herd immunity in general.

Except that once the vaccinations were made available, those parts of the state saw the highest vaxx #'s and consequently, lower case counts.

But again, that's AFTER the vaccines, not before them.

 

[LV426]

Since everyone likes to slam Florida I think we should look at blue states that did worse than Florida on a per capital rate.

Arizona
New Jersey
Michigan
Georgia
New Mexico
New York
Pennsylvania
Nevada

Per CAPITA, but that's misleading because NJ & NY were hit at the beginning.

 

[LV426]

I've spent a fair amount of time thinking about NM and NE, because they are outliers -- the only terribly performing Biden state and the only well-performing Trump state, respectively. I'm not sure there are many lessons we can learn from NM about what to avoid, since I think largely they suffered because of such a high Native American population. But I think there's probably more we can learn from NE, since they figured out how to do pretty well despite the usual right-wing opposition to vaccines, masking, and distancing, which makes me wonder what their "secret ingredient" was.

You should check out what happened in the indigenous parts of the state after the vaccines became available, because I know that vaxx rates among Native Americans was substantially higher than among white people, so the case counts post-vaccine were probably almost all in the non-Native parts of the state.

American Indians have the highest Covid vaccination rate in the US
https://www.pbs.org/wgbh/nova/article/native-americans-highest-covid-vaccination-rate-us/

 

[Mina]

Fascinating. Wondering if it could be broken out on a county level since a lot of the deaths in CA happened in the red parts of the state.

I wish I had data for that. That's a big issue in the Northeast, too. Like there's a gigantic difference between between the Boston area and Western Mass, or upstate and downstate NY. Even within the states, you'd likely see the kind of pattern you see nationally, where the areas that got hit hard early on were often not those that ended up being worse when the pandemic was taken as a whole (e.g., Coastal Maine saw more early cases, but then Northern Maine wound up doing worse over the full time).

But the method I'm using probably breaks down at the county level, since deaths would tend to be concentrated wherever hospitals happen to be located. Like to take Massachusetts as an example, if you judged by place of death, you'd probably find a wildly disproportionate share of people in the state die in Boston, simply because they're taken there, to the hospitals, before being declared DOA. So, you'd instead need a system that compares where deceased people's residences were, not where they died, which I don't think is how the CDC collects that data.

 

[Mina]

Since everyone likes to slam Florida I think we should look at blue states that did worse than Florida on a per capital rate.

Arizona
New Jersey
Michigan
Georgia
New Mexico
New York
Pennsylvania
Nevada

First, using the method I'm talking about here (excess deaths, rather than just counting how many people the state feels like designating as having died of COVID), the only blue states that did worse than FL are NM, NV, CA, CO, and MI.

Second, Florida, Hawaii, Nevada, and maybe a few others are potentially misleading cases, because of the extreme role of tourism in those states. Consider:

https://www.clickorlando.com/news/florida/2021/02/16/florida-tourism-numbers-lowest-since-2010/

So, Florida had 86.714 million visitors to the state in 2020, versus 131.420 in 2019. Pre-pandemic, the average stay was about 5.0 days per visitor (weighted average for international plus domestic visitors).

https://s3.amazonaws.com/media.clov...lorida_Visitor_Study_-_Digital_Version_1_.pdf

So, in 2019, that would have been about about 657.1 million person-days of visits, versus 433.57 million in 2019. So, that's a difference of 223.53 million person-days, between the two years. Divide by 365, and you realize that's equivalent to the average population of the state at any given moment being 612,000 lower in 2020 than 2019, just from the hit tourism took. For a state with a population of 21.5 million at the time, that means the population shrunk by roughly 3% that year (not in terms of official residents, but in terms of actual average number of people in the state at any moment, which would be the relevant factor for mortality).

So, for example, if a state would ordinarily have had a population of 1 million, with 10,000 of them dying in a year, and instead 11,800 of them died, we'd at first see that as 18% excess mortality (up from 1% mortality to 1.18%). But what if the population also went down by 3%? Then it's like having almost 22% excess mortality. That is, previously mortality was 1% (10k/1M) and now it's about 1.216% (11,800/970k).

So, the huge dip in tourism, in 2020, would be expected, other things being equal, to result in Florida having significantly fewer deaths (e.g., fewer tourists dropping dead of heart attacks at the buffet, drowning at the pool, getting crushed in car accidents, and so on).

Hawaii and Nevada would have experienced the same thing, in terms of losing a lot more incoming people than outgoing people, when tourism was hit. A few others may also make the list, but most other states would go the other way since they ordinarily have more of their residents leave for tourism than they have outsiders arrive. All told, my "back of the napkin math," accounting both for 2020, with low tourism, and 2021, with thing returning to normal, tells me Florida's excess death rate accounting for tourism, as actually about two points higher than the graph suggests. Hawaii's is about four-points higher, since it's even more tourism-dependent. So, on my graph, if we did adjusted numbers, Hawaii would be at 7 (making it second best, rather than best), and Florida would be around 20.... still doing better than NM, and NV, among blue states, but maybe no others.

 

[PostmodernProphet]

can you do the same thing sorted by age brackets?......

 

[LV426]

I don't hate government. I hate dishonesty and I hate inefficiency. As I see those things in government, I hate them. Do you ignore those things as you find them in life?

My thoughts on whether or not our leaders are lying thieves is based on the FACT that they are lying thieves.

Between 1999 and 2021, annual Federal Outlays increased by 400%. Over the same period, if the Feds had increased spending by only the rate of inflation that they have published, Federal outlays would have increased by 150%.

The difference annually, 62+% of all Federal Spending, was outright theft. Without the outrageous growth of spending since 1999 that is mostly theft by the lying thieves, we would have a $7 Trillion surplus instead of a $30 Trillion debt.

The major political parties are lie factories that produce liars, train them to lie and demand that they tell the lies that the zealots of the political parties prefer. They lie to gain office. Once in office, the lying thieves lie and steal.

Who is the particular politician that you believe is not a lying thief? A good piece of evidence is whether or not the lying thief you cite has refused all pay increases or any pay whatever during his time in office.

Another piece of evidence might be whether or not the lying thief you cite is constantly railing against increases of spending, the burden of taxation and complaining of government waste and corruption.

Who do you present?

Aside from that, the sky high prices paid compared to the middle of the pack quality of goods delivered are wildly out of balance. If you are not questioning the effectiveness of government spending, you just aren't watching what's happening.

https://www.cnn.com/2021/03/26/politics/justice-department-fraud-coronavirus-relief-fund/index.html

https://www.rasmussenreports.com/pu...te_the_government_you_re_not_paying_attention

https://www.taxpolicycenter.org/statistics/federal-receipt-and-outlay-summary

Of course government spending isn't going to work out when you cater that spending in the form of tax cuts and tax credits to big business instead of to workers.

We know that tax cuts don't ever deliver on any promise made of them.

Tax cuts haven't created a single job ever. EVER.

But they sure have cost a lot of jobs...

 

[LV426]

You sound like a fluu blown communist. If you live in the US, please get your ass out of here and head for Cuba. No China Virus allowed there.

You sound like a fucking idiot from 1955, screaming about "communism".

Fuck you fascist pig.

It's your virus because you and Trump couldn't fucking stop yourselves from lying about it.

That big, fat fuckin mouth of yours is what cost Trump the 2020 election.

It wasn't theft, it wasn't a conspiracy, it was because you couldn't shut the fuck up for 5 minutes. You just had to open your big, fat mouth all the live-long day.

So maybe shut the fuck up now, before you punch yourself in the dick again.

 

[Lionfish]

You sound like a fucking idiot from 1955, screaming about "communism".

Fuck you fascist pig.

It's your virus because you and Trump couldn't fucking stop yourselves from lying about it.

That big, fat fuckin mouth of yours is what cost Trump the 2020 election.

It wasn't theft, it wasn't a conspiracy, it was because you couldn't shut the fuck up for 5 minutes. You just had to open your big, fat mouth all the live-long day.

So maybe shut the fuck up now, before you punch yourself in the dick again.

I you 2. Big Hug.

 

[LV426]

Tiny gun for a tiny dick

 

[Lionfish]

You sound like a fucking idiot from 1955, screaming about "communism".

Fuck you fascist pig.

It's your virus because you and Trump couldn't fucking stop yourselves from lying about it.

That big, fat fuckin mouth of yours is what cost Trump the 2020 election.

It wasn't theft, it wasn't a conspiracy, it was because you couldn't shut the fuck up for 5 minutes. You just had to open your big, fat mouth all the live-long day.

So maybe shut the fuck up now, before you punch yourself in the dick again.

Back 2 U

BTW, you don't know your guns do you?

 

[LV426]

BTW, you don't know your guns do you?

I know that gun is very small which is probably why you chose it; your hands are too small to use a bigger gun.

And you know what they say about men with small hands...

 

[Lionfish]

I know that gun is very small which is probably why you chose it; your hands are too small to use a bigger gun.

And you know what they say about men with small hands...

As I said, you know very little about guns. Now is the time you shut your pie hole and do some research.