How are the States handling this Virus so Far?

I want to try and get a notion, hopefully one that is data driven, on how to evaluate the response by individual States to the virus. As an initial matter, every State should be implementing at least three of the four epidemic containment steps recommended by the CDC. Failure to do that should be designated a failing overall.

But beyond that, what metrics should we use to evaluate State responses?

One area might be to review the mortality rate, on a per capita basis, and the confirmed case rate, on a per capita basis.

So, for example, Louisiana and Connecticut have deaths per millions which rank 2nd and 5th respectively. Their cases per million are 3rd and 5th respectively. That would be an example of a poor response.

On the other hand, California and Texas rank around 33 and 39th in terms of cases per million. And they rank around those points as well for deaths per million of population. That might be considered an example of a good response.

 

I was wondering if it was possible to do something along demographic lines too. We already have age and health metrics but what about income, education, and post codes as the measures to rank mortality?

That might give us an insight into whether population density is more important factor than income or education. OTOH does education matter more because those that know more take greater precautions than those who can afford to go to exotic ski resorts?

 

Deaths per million? That doesn't seems like a good metric since some states have populations less than a million, their rank would be artificially inflated with a single outbreak at a single location, like a nursing home. Not dogging on your general idea, just think a different metric would be needed. Not really sure what because its difficult to account for the vast disparities between states regarding population or density...

 

Dependance on mass transit could be a factor. I think New Orleans can be blamed on Mardi Gra.

 

It's an effort to normalize the data and it's really no different that making the data represented on a per capita basis, like how voters in Wyoming are much more important on a per capita basis than California or how the US pollutes more CO2 on a per capita basis than China.

 

One of things about this virus is that it does affect the poor and rich alike, but I think it is abundantly clear that social distancing is a bit of a luxury. It's real hard to tell the slums, where 6-7 people live in one room immediately next to a family of 5 that live in one room to "stay ~6 feet apart."

 

Absolutely agree on the point about social distancing. However do those living in Manhattan penthouses engage in the same degree of social distancing as do roommates who share the smaller apartments below them? Is it possible that the elite ignore them and still expect to be waited upon hand and foot without any regard to the fact that the person washing their hair or giving them a pedicure could be infected?

Granted these are hypotheticals but there is definitely a degree of arrogance that comes with wealth that makes them believe themselves to be immune in a similar way to those who went on Spring Break.

If nothing else this Pandemic is going to provide us with data that gives us an insight into how all parts of society reacted to an existential threat.

 

In general no state has handled this very well. There's been no strictly enforced quarantines with punishment for offenders to demonstrate seriousness. Many people are still oblivious to the threat to the public health.

I guess that's why the curve hasn't flattened but looks like Italy and Spain.

 

In addition, looks like a large percentage of Louisianans are not healthy.......

Select all causes of death per 100,000

Louisiana's map....mostly painted red, thus, high rate.

https://www.worldlifeexpectancy.com/usa/cause-of-death/diabetes-mellitus/by-state/

 

Everybody's map is mostly red. The disease isn't spread according to politics. Or did you have a different meaning I'm not understanding?

 

To what end? 50 case studies using the same criteria would give a better picture and highlight anomalies...

 

https://www.worldlifeexpectancy.com/louisiana-cause-of-death-by-age-and-gender

https://www.worldlifeexpectancy.com/usa-health-maps

 

I think you are exactly right.

LOOKING AT THIS MAP OF INFECTION DENSITY in the NYC metro area, I note that Manhattan looks considerably better than the surrounding area. I’m wondering if there’s a correlation between long subway or bus rides and higher rates of infection.

 

You'll never get the media to address this because it doesn't fit the PC climate control narrative.

 

Doesn't matter. Few believe the Fake News Media, they are known to lie constantly like the Chinese Communist Party.

 

Andy Cuomo and New York leads the country as the worst response. Lends a whole new meaning to they are #1.

https://www.corona.help/country/united-states

 

I live in Oregon and the infection rate here has been surprisingly low. Especially in Portland where I don't think there has been a single reported case. About the time the first case in Oregon was being reported, the governor was announcing stay at home guidelines, and social distancing. The mayor followed with more guidelines and the city came to a screeching halt.

It is eerily weird going out. The streets are mostly empty. Even at rush hour, the number of cars is small. No traffic jams anywhere. Perhaps the busiest ones are those delivering or picking up food from restaurants and grocery stores.

The stay at home order allows for jogging, bike riding, and walks in the parks, as long as everyone stays 6 feet apart. On sunny days, one sees families and individuals out on their bicycles, or jogging. You see children playing in their yards, their parents preparing their landscaping for the coming season.

Life seems mostly normal, except for the fact that everything is closed. Except the grocery, liquor, and pot stores, and they have lines taped or painted on the ground, enforcing the six foot rule. At some stores there are security guards to make sure everyone follows the rule. About half the people you see are wearing masks, and the numbers are growing.

I don't know if this matters or not, but in recent years, the state of Oregon, and the City of Portland have been engaging in planning for a possible natural disaster. Emergency preparedness. It is kind of weird. While other cities are in panic mode, here in Portland sits some of the best equiped hospital beds for treating the pandemic, yet they sit idle, in tense expectation for a flood that just hasn't been coming. Oregon even had enough spare ventilators on hand to send New York something like a hundred of them.

I think that Oregon and Portland acted as they did because they had spent a lot of time thinking about the possibility of such things, and preparing for them.

 

I think the data proves out that Oregon has done a very commendable job handling this virus.

This is the per capita (per million) tracker for the case count.


This is the per capita (per million) tracker for the death count.



I grouped the States in bunches of 10, ranked by the most cases to the least number of cases. This is the 21-30 bunch (Oregon was 29th at the time that I started tracking the data...it is currently 33rd).

 

Dude, this is an outstanding thread.

I am not the largest fan of calculating per capita, at least either birth or death rate within any category or subcategory.

And especially, vis-a-vis COVID-19, I thought long and hard about what metric would be the most effective.

As @Dispondent said, calculating the death rate per capita causes some really crazy values for places well under 1,000,000 people.

Also, since not all 331 milion Americans have been tested, there is no way to really know how many are or have been infected. It's really a shot in the dark.

The only metric that I think *can* be predictive, because it cannot mathematically be challenged, is the exact number of deaths / the exact number of cases.

Worldwide, we have seen the death rate, when measured according to this metric, rise from 3.73% on 02/27 to currently: 5.82%. This means that the more we test, the higher the death rate goes.

But it's not just the death rate that most be considered. It must also be the % of people who are still ill, meaning, they have not resolved the virus yet. And the longer that % stays high, say, more than 5 weeks, that can only mean that a certain number of people have been hanging on a machine for a good three weeks or longer and will most likely die. I mean that in no way disrespectfully, but it is a statistical fact.

So, if you just want to get a picture of how many people are likely to die or stay unresolved in any one state, that would be a way to start.

But I'm not sure if that tells us anything about how any one individual state is handling the crisis.

And frankly, it's a ******ned shame that we are having to think in terms of 50 states instead of one united Federal Government, but alas, because of the 10th amendment, we have 50 little dukedoms here in this catastrophe as well.

And then there is the issue that states with more large metropolises are likely to get hit harder. Great example: OHIO and INDIANA. In terms of general demographic, the two states are very similar, but Ohio has more large cities than Indiana and will likely take a far harder hit than Indiana.

Another way would be to divide this up per congressional district, for the CDs should theoretically have similar population levels.

 

U. of Mississippi Medical Center is making it's own McGyver ventilators:

https://www.clarionledger.com/story...ntilators-hardware-store-supplies/2963992001/

"Made with "primarily a garden hose, a lamp timer and electronic valve," the ventilator, named the Robertson Ventilator, for less than $100, can be assembled in approximately 20 to 30 minutes, meaning a dedicated team of four to five could produce nearly 100 in a day if needed, he said.

Demonstrating the functionality of the machine at a news conference Tuesday afternoon, Robertson turned on a ventilator hooked up to a mannequin. The mannequin's chest began to rise and fall.

'Not fancy, but it works'

"The brain behind the thing is actually a lamp timer," he said. "It's not fancy but it works. This would be available as a last resort if the numbers increase as we think they might."

If it's a garden hose down your trachea or almost certain death you have little to lose. Go for it, Doc.

 

New York’s Coronavirus Death Toll is Almost Certainly Far Higher Than Reported.

“Before the pandemic struck New York City, 20-25 people a day were dying at home according to the city medical examiner’s office. Now, that number is more than 200, raising questions about how many of those who die in their own beds actually died of coronavirus.”​

That’s troubling. Hospitals have almost certainly been overcounting COVID-19 deaths, but what else could account for such an increase in in-home deaths?

 

US coronavirus death toll prediction drops over 25% to 60,000

 

The State of Queensland, Australia. Almost total lock down. 3000 tested in the last 24 hours. Only 10 positive. 0.33? Curve is flattening. But the message still is.....STAY THE FUQ AT HOME.

 

You had over 30 confirmed cases by April 1.
https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Portland,_Oregon

How do you not know what’s going on in your own city?

 

While I agree with Stat that Congressional Districts might even things up a bit there is probably next to nothing in the way of data at that level. The closest would be by county and a lot of states are providing that information on their sites but it would a great deal of extra work unless it can be downloaded from the state data sites themselves.

If you did go by county you would have more accurate demographic data which could enable you to compare responses by income levels. Then if you grouped the counties by income you could compare them by quintile and see where the states allocated their resources in comparison to the number of deaths.

In addition you might even have population counts by county and that would be another way to group their data. How do densely populated counties compare to sparsely populated and then cross reference to income and see what that reveals.

On top of that you have states like TX that essentially allowed cities and counties to set their own rules when it came to social distancing, etc. You might be able to assign the 3 basic IHME categories to these counties and see how they performed in comparison to counties in states that applied the same IHME categories.

Hope that some of that might be helpful.