Off the Kuff Rotating Header Image

Presidio County

What happens when there’s no room for the sick people?

It’s already happening in some parts of Texas, mostly out west.

Sarah Vasquez for the Texas Tribune

Presidio and Brewster counties, home to Marfa and Big Bend, along with nearby Culberson County, lead the state in cases per 1,000 residents in the last two weeks, according to a Texas Tribune analysis. In fact, all of West Texas, including Jeff Davis, Hudspeth and El Paso counties, is ablaze with increasing COVID-19 cases and low on hospital beds.

Big Bend Regional Medical Center, the only hospital in Presidio, has just 25 acute care beds. Culberson County’s 2,200 residents have just Culberson Hospital, where there are 14 beds and two ventilators, but at least one doctor said she doesn’t feel adequately prepared to use them.

Patients in dire condition are often transferred from the small towns to regional hospitals in larger metropolitan areas. But those closest hospital systems in El PasoLubbock and Midland, which have more resources, are already struggling with their own influxes of local cases, leaving doctors and county officials worried a bump in cases from Thanksgiving gatherings will fill beds beyond capacity with nowhere left to send the sickest patients.

“It’s unlikely we’d be able to help them at this point,” said Ricardo Samaniego, the county judge of El Paso, where COVID-19 patients occupy more than 35% of hospital beds.

Without El Paso as an option to send patients, nearby doctors and officials are scrambling.

“It’s a scary feeling to have a critically ill patient with nowhere to go,” said Gilda Morales, a Culberson County commissioner and doctor at Culberson Hospital.

She said that in recent weeks, the county has sent struggling patients to hospitals in San Antonio — more than 400 miles away — including Culberson County Judge Carlos Urias, who’s been there for nearly four weeks.

If a flood of residents need to be hospitalized quickly, and cases in San Antonio and other metropolitan areas swell, Culberson might not have the resources to treat everyone in need, Morales said.

“We’re worried those beds will run out, and then what?” Morales said. “We’re all holding our breath because as much as we told people not to get together for Thanksgiving, the holidays and family give a false sense of security.”

Hospitals across the West Texas region are “bumping capacity and stretched absolutely to the limit,” said John Henderson, president of the Texas Organization of Rural and Community Hospitals. Administrators have struggled to find open beds, in some cases calling 15 or 20 facilities, he said.

“Everyone is headed the wrong direction,” he said. “Every week is a little worse than the last one.”

In Odessa and in neighboring Midland, the area’s three hospitals serve as “referral centers,” accepting patients from small-town facilities that are ill equipped to treat serious illnesses.

“All of our outlying facilities, they don’t have ICUs or ventilators that can take care of patients long term,” said Dr. Rohith Saravanan, chief medical officer of Odessa Regional Medical Center. The hospital in recent weeks added 34 beds for people with COVID-19, and, as of Tuesday, only four were still empty.

“If we see any more sharp rises, I don’t think our hospitals will be able to keep up with capacity,” Saravanan said.

Scenic Mountain Medical Center in Big Spring is one of those outlying community hospitals. The facility’s seven intensive care unit beds are full, as are 18 overflow beds that fill the hallways.

Just as a reminder, people still have heart attacks and get in car crashes and fall down stairs and get shot. They’re competing for increasingly scarce hospital resources with all of the COVID patients, too. I don’t have any answers for this, or at least I don’t have any answers beyond what I and many others have been saying for months – wear your face mask, avoid indoor gatherings, observe social distancing. More to the point, Greg Abbott doesn’t have any answers, either. That’s a lot more consequential.

So how did my simple projection work out?

Remember this? I divided the counties up by how much their voter rolls had grown or shrunk since 2012, then used the 2016 turnout levels and 2018 results to project final numbers for the Presidential election in 2020. Now that we have those numbers, how did my little toy do? Let’s take a look.

A couple of things to acknowledge first. The most up to date voter registration numbers show that the group of counties that looked to have lost voters since 2012 have actually gained them, at least in the aggregate. Second, the actual turnout we got so far exceeded past numbers that we literally couldn’t have nailed this, at least not at a quantitative level. So with that in mind, let’s move forward.

We start with the counties that had seen growth of at least 10K voters on their rolls since 2012. There were 33 of these. Here are the numbers I had in my initial review, updated to include what happened this year.


Romney  3,270,387   Obama    2,792,800
Romney      53.9%   Obama        46.1%
Romney +  477,587

Trump   3,288,107   Clinton  3,394,436
Trump       49.2%   Clinton      50.8%
Trump  -  106,329

Cruz    3,022,932   Beto     3,585,385
Cruz        45.7%   Beto         54.3%
Cruz   -  562,453

Trump   4,119,402   Biden    4,579,144
Trump       47.4%   Biden        52.6%
Trump  -  459,742

Year  Total voters   Total votes   Turnout
==========================================
2012    10,442,191     6,157,687     59.0%
2016    11,760,590     7,029,306     59.8%
2018    12,403,704     6,662,143     53.7%
2020    13,296,048     8,765,774     65.9%

When I did the original post, there were 12,930,451 registered voters in these 33 counties. As you can see, and will see for the other groups, that increased between August and November, by quite a bit. As you can see, Trump did considerably worse than he had in 2016 with these counties, but better than Ted Cruz did in 2018. That says it all about why this race wasn’t as close as the Beto-Cruz race in 2018. My projection had assumed 2016-level turnout, but we obviously got more than that. Here’s what I had projected originally, and what we would have gotten if the 2020 results had been like the 2018 results from a partisan perspective:


Trump   3,533,711   Biden    4,198,699
Trump  -  664,988

Trump   3,975,236   Biden    4,723,310
Trump  -  748,074

Fair to say we missed the mark. We’ll see how much of a difference that would have made later. Now let’s look at the biggest group of counties, the 148 counties that gained some number of voters, from one to 9,999. Again, here are my projections, with the updated voter registration number:


Romney  1,117,383   Obama      415,647
Romney      72.9%   Obama        27.1%
Romney +  701,736

Trump   1,209,121   Clinton    393,004
Trump       75.5%   Clinton      24.5%
Trump  +  816,117

Cruz    1,075,232   Beto       381,010
Cruz        73.8%                26.2%
Cruz   +  694,222

Trump   1,496,148   Biden      501,234
Trump       74.0%   Biden        26.0%
Trump  +  994,914

Year  Total voters   Total votes   Turnout
==========================================
2012     2,686,872     1,551,613     57.7%
2016     2,829,110     1,653,858     58.5%
2018     2,884,466     1,466,446     50.8%
2020     3,112,474     2,022,490     65.0%

As discussed, there’s a whole lot of strong red counties in here – of the 148 counties in this group, Beto carried ten of them. They had 2,929,965 voters as of August. What had been my projection, and how’d it go here?


Trump   1,264,954   Biden      449,076
Trump  +  815,878

Trump   1,496,148   Biden      501,234
Trump  +  994,914

The margin is wider due to the higher turnout, but Biden actually did a little better by percentage than Clinton did, and was right in line with Beto. This is obviously an area of great need for improvement going forward, but the projection was more or less right on target, at least from a partisan performance perspective. But as you can see, even with the more optimistic projection for Biden, he’s already in the hole. Like I said, this is an area of urgent need for improvement going forward.

Now on to the last group, the 73 counties that had lost voters from 2012, at least going by the August numbers. As you can see, that turned out not to be fully true:


Romney     182,073   Obama      99,677
Romney       64.6%   Obama       35.4%
Romney +    82,396

Trump      187,819   Clinton    90,428
Trump        67.5%   Clinton     32.5%
Trump  +    97,391

Cruz       162,389   Beto       79,237
Cruz         67.2%   Beto        32.8%
Cruz   +    83,152

Trump      226,104   Biden     105,490
Trump        68.2%   Biden       31.8%
Trump  +   120,514

Year  Total voters   Total votes   Turnout
==========================================
2012       517,163       284,551     55.0%
2016       511,387       286,062     55.9%
2018       505,087       243,066     48.1%
2020       546,997       335,110     61.2%

As you can see, that decline in registrations has reversed, quite dramatically. I didn’t check each individual county – it seems likely that some of them are still at a net negative – but overall they are no longer in decline. Good for them. As you can also see, Biden performed a little worse than Clinton and Beto, but close enough for these purposes. Let’s compare the projection to the reality:


Trump      187,587   Biden      91,561
Trump +     96,026

Trump      226,104   Biden     105,490
Trump  +   120,514

Put the best-case scenario from the first group with what we got in the last two, and we could have had this:


Trump    5,697,488   Biden   5,330,034
Trump       51.67%   Biden      48.33%

Which is pretty close to what I had projected originally, just with a lot more voters now. The actual final result is 52.18% to 46.39%, so I’d say my method came closer to the real result than most of the polls did. Clearly, I missed my calling.

All this was done as an exercise in frivolity – as I said at the time, I made all kinds of assumptions in making this projection, and the main one about turnout level was way wrong. The point of this, I think, is to show that while Dems have indeed improved greatly in performance in the biggest counties, they haven’t done as well everywhere else, and while the marginal difference from Obama 2012 to Clinton 2016 and Biden 2020 isn’t much, the overall direction is wrong (even as Biden improved somewhat on the middle group over Clinton), and we’re going to have a real problem making further progress if we can’t figure out a way to improve our performance in these smaller counties. There is room to grow in the big and growing counties – these include some fast-growing and very red places like Montgomery and Comal, for instance – but we’re going to reach diminishing marginal growth soon, if we’re not already there. We need to step it up everywhere else. I’ll be returning to this theme as we go forward. Let me know what you think.

So what happened in the Latino counties?

Let’s go to the data:


County       Trump  Clinton    Trump    Biden
=============================================
Bexar      240,333  319,550  303,871  440,823
Cameron     29,472   59,402   48,834   63,732
Dimmit         974    2,173    1,384    2,264
El Paso     55,512  147,843   81,235  168,801
Frio         1,856    2,444    2,812    2,421
Hidalgo     48,642  118,809   89,925  127,391
Jim Hogg       430    1,635      831    1,197
Jim Wells    5,420    6,694    7,077    5,094
Maverick     2,816   10,397    6,881    8,324
Nueces      50,766   49,198   64,467   60,749
Presidio       652    1,458      721    1,463
Starr        2,224    9,289    8,224    9,099
Webb        12,947   42,307   18,985   32,442
Willacy      1,547    3,422    2,437    3,097
Zapata       1,029    2,063    2,032    1,820
Zavala         694    2,636    1,490    2,864

Total      453,643  779,320  641,116  931,555

County      Trump% Clinton%   Trump%  Biden%
============================================
Bexar        42.9%    57.1%    40.8%   59.2%
Cameron      33.2%    66.8%    43.4%   56.6%
Dimmit       31.0%    69.0%    37.9%   62.1%
El Paso      27.3%    72.7%    32.5%   67.5%
Frio         43.2%    56.8%    53.7%   46.3%
Hidalgo      29.0%    71.0%    41.4%   58.6%
Jim Hogg     20.8%    79.2%    41.0%   59.0%
Jim Wells    44.7%    55.3%    58.1%   41.9%
Maverick     21.3%    78.7%    45.3%   54.7%
Nueces       50.8%    49.2%    51.5%   48.5%
Presidio     30.9%    69.1%    33.0%   67.0%
Starr        19.3%    81.7%    47.5%   52.5%
Webb         23.4%    76.6%    36.9%   63.1%
Willacy      31.1%    68.9%    44.0%   56.0%
Zapata       33.3%    66.7%    52.8%   47.2%
Zavala       20.8%    79.2%    34.2%   65.8%

Total        36.8%    63.2%    40.8%   59.2%

Webb County totals are early voting only – they have taken their sweet time getting those results. I have no prescriptions to offer, and even if I did, I’d be the wrong person to listen to for them. I’m just reporting what happened. As others have observed, in some counties Biden met or exceeded Hillary Clinton’s numbers from 2016, but Trump greatly increased his numbers from that election. You may recall that in the last NYT/Siena poll, Nate Cohn observed that higher turnout, at least beyond a certain point, didn’t actually benefit Biden, because sufficiently high Latino turnout wasn’t in his favor. Starr County was a particularly shocking example of that, but we see that in some larger counties like Hidalgo and Cameron, and to a lesser extent El Paso as well. In some counties – Maverick, Jim Hogg, Jim Wells, Willacy – it appears some Clinton voters may have switched to Trump, or not voted while non-participants from 2016 came in. Bexar County was the only clear improvement for Biden. If you had to pick only one county for that, Bexar would be the one, but there’s only so much it can do.

You can look at this two ways. Hillary Clinton netted 346K votes, while Biden netted 290K. That’s not all that much, but there’s the ground we could have gained given the higher turnout as well as the ground we lost. If Biden had performed at exactly the same level as Clinton, he’d have netted 415K votes. Adjust the final score to account for that, and Biden would have lost by four and a half points, instead of almost six. Wouldn’t have mattered in this case, but it wouldn’t have taken much. Plus, you know, better to make your task easier rather than harder.

Like I said, I have no solutions to offer. Plenty of smart people have plenty of ideas, and quite a few of them were raising issues before the election. Might be a good idea to listen to them. All I’m saying is that whatever happened here, it wasn’t what we wanted. If we want to avoid a repeat, we better get to work.

A very simple projection of the November vote

In my earlier post about the current state of voter registrations, I noted that you could see the county-by-county totals in the contest details for the Senate runoff. What that also means is that if you have current (till now, anyway) voter registration totals, you can do a comparison across the counties of where voter registration totals have gone up the most, and how the vote has shifted in recent elections. In doing so, you can come up with a simple way to project what the 2020 vote might look like.

So, naturally, I did that. Let me walk you through the steps.

First, I used the 2020 runoff results data to get current registration totals per county. I put that into a spreadsheet with county-by-county results from the 2012 and 2016 Presidential elections and the 2018 Senate election to calculate total voter registration changes from each year to 2020. I then sorted by net change since 2012, and grouped the 254 counties into three buckets: Counties that had a net increase of at least 10,000 voters since 2012, counties that had a net increase of less than 10,000 voters since 2012, and counties that have lost voters since 2012. From there, I looked at the top race for each year.

First, here are the 2012 big gain counties. There were 33 of these counties, with a net gain of +2,488,260 registered voters as of July 2020.


Romney  3,270,387   Obama    2,792,800
Romney      53.9%   Obama        46.1%
Romney +  477,587

Trump   3,288,107   Clinton  3,394,436
Trump       49.2%   Clinton      50.8%
Trump  -  106,329

Cruz    3,022,932   Beto     3,585,385
Cruz        45.7%   Beto         54.3%
Cruz   -  562,453

Year  Total voters   Total votes   Turnout
==========================================
2012    10,442,191     6,157,687     59.0%
2016    11,760,590     7,029,306     59.8%
2018    12,403,704     6,662,143     53.7%
2020    12,930,451     

The shift in voting behavior here is obvious. Hillary Clinton did much better in the larger, growing counties in 2016 than Barack Obama had done in 2012, and Beto O’Rourke turbo-charged that pattern. I have made this point before, but it really bears repeating: In these growing counties, Ted Cruz did literally a million votes worse than Mitt Romney did. And please note, these aren’t just the big urban counties – there are only seven such counties, after all – nor are they all Democratic. This list contains such heavily Republican places as Montgomery, Comal, Parker, Smith, Lubbock, Ector, Midland, Randall, Ellis, Rockwall, and Kaufman. The thing to keep in mind is that while Beto still lost by a lot in those counties, he lost by less in them than Hillary Clinton did, and a lot less than Obama did. Beto uniformly received more votes in those counties than Clinton did, and Cruz received fewer than Trump and Romney.

Here’s where we do the projection part. Let’s assume that in 2020 these counties have 59.8% turnout at 2018 partisan percentages, which is to say Biden wins the two-party vote 54.3% to 45.7% for Trump. At 59.8% turnout there would be 7,732,410 voters, which gives us this result:


Trump   3,533,711   Biden    4,198,699
Trump  -  664,988

In other words, Biden gains 100K votes over what Beto did in 2018. If you’re now thinking “but Beto lost by 200K”, hold that thought.

Now let’s look at the 2012 small gain counties, the ones that gained anywhere from eight voters to 9,635 voters from 2012. There are a lot of these, 148 counties in all, but because their gains were modest the total change is +243,093 RVs in 2020. Here’s how those election results looked:


Romney  1,117,383   Obama      415,647
Romney      72.9%   Obama        27.1%
Romney +  701,736

Trump   1,209,121   Clinton    393,004
Trump       75.5%   Clinton      24.5%
Trump  +  816,117

Cruz    1,075,232   Beto       381,010
Cruz        73.8%                26.2%
Cruz   +  694,222

Year  Total voters   Total votes   Turnout
==========================================
2012     2,686,872     1,551,613     57.7%
2016     2,829,110     1,653,858     58.5%
2018     2,884,466     1,466,446     50.8%
2020     2,929,965     

Obviously, very red. Beto carried a grand total of ten of these 148 counties: Starr, Willacy, Reeves, Jim Wells, Zapata, Val Verde, Kleberg, La Salle, Dimmit, and Jim Hogg. This is a lot of rural turf, and as we can see Trump did better here than Romney did, both in terms of percentage and net margin. Ted Cruz was a tiny bit behind Romney on margin, but did slightly better in percentage. The overall decline in turnout held Cruz back.

Once again, we project. Assume 58.5% turnout at 2018 partisan percentages. That gives us 1,714,030 voters for the following result:


Trump   1,264,954   Biden      449,076
Trump  +  815,878

Trump winds up with the same margin as he did in 2016, as the 2018 partisan mix helps Biden not fall farther behind. Trump is now in the lead by about 150K votes.

Finally, the counties that have had a net loss of registered voters since 2012. There were 73 such counties, and a net -17,793 RVs in 2020.


Romney     182,073   Obama      99,677
Romney       64.6%   Obama       35.4%
Romney +    82,396

Trump      187,819   Clinton    90,428
Trump        67.5%   Clinton     32.5%
Trump +     97,391

Cruz       162,389   Beto       79,237
Cruz         67.2%   Beto        32.8%
Cruz +      83,152

Year  Total voters   Total votes   Turnout
==========================================
2012       517,163       284,551     55.0%
2016       511,387       286,062     55.9%
2018       505,087       243,066     48.1%
2020       499,370    

Again, mostly rural and again pretty red. The counties that Beto won were Culberson, Presidio, Jefferson (easily the biggest county in this group; Beto was just over 50% here, as Clinton had been, while Obama was just under 50%), Zavala, Duval, Brooks, and Frio.

Assume 55.9% turnout at 2018 partisan percentages, and for 277,148 voters we get:


Trump      187,587   Biden      91,561
Trump +     96,026

Again, basically what Trump did in 2016. Add it all up, and the result is:


Trump    5,012,802   Biden    4,770,351
Trump       51.24%   Biden       48.76%

That’s actually quite close to the Economist projection for Texas. If you’re now thinking “wait, you walked me through all these numbers to tell me that Trump’s gonna win Texas, why did we bother?”, let me remind you of the assumptions we made in making this projection:

1. Turnout levels would be equal to the 2016 election, while the partisan splits would be the same as 2018. There’s no reason why turnout can’t be higher in 2020 than it was in 2016, and there’s also no reason why the Democratic growth in those top 33 counties can’t continue apace.

2. Implicit in all this is that turnout in each individual county within their given bucket is the same. That’s obviously not how it works in real life, and it’s why GOTV efforts are so critical. If you recall my post about Harris County’s plans to make voting easier this November, County Clerk Chris Hollins suggests we could see up to 1.7 million votes cast here. That’s 360K more voters than there were in 2016, and 500K more than in 2018. It’s over 70% turnout in Harris County at current registration numbers. Had Beto had that level of turnout, at the same partisan percentages, he’d have netted an additional 85K votes in Harris. Obviously, other counties can and will try to boost turnout as well, and Republicans are going to vote in higher numbers, too. My point is, the potential is there for a lot more votes, in particular a lot more Democratic votes, to be cast.

Remember, this is all intended as a very simple projection of the vote. Lots of things that I haven’t taken into account can affect what happens. All this should give you some confidence in the polling results for Texas, and it should remind you of where the work needs to be done, and what the path to victory is.

Marfa solar fight gets deferred

They will not be building that big solar farm out in Marfa at this time.

Citing a lack of investors, Houston-based Tessera Solar has scotched plans to erect at least 1,000 three-story mirrored satellite dishes — designed to convert the blisteringly bright desert sun into electricity — until further notice. The solar project had created a chasm in the community, dividing those who embraced the potential for new jobs and tax revenue and those who worried the silvery sun catchers would blight the barren desert landscape.

The construction was part of Tessera’s contract, now defunct, to provide solar power to CPS Energy, which supplies gas and electricity for San Antonio. “There’s no expected construction or completion date until these financial markets strengthen,” says Janette Coates, a Tessera spokeswoman. But she adds the company hasn’t given up on the project altogether. “We still plan on developing it and pursuing it,” she says.

And opponents of the project still plan on opposing it. “We’re not going to rest on our laurels,” says Melinda Beeman, an artist whose home is about a half-mile from the proposed site. Beeman, who moved to this desert spot for its tranquil beauty more than a decade ago, led the locals’ revolt against Tessera.

As I said before, I don’t know enough about this specific project to know who I’d want to root for. In general, I hope to see more of these solar farms get built, but I also want to see a better system for figuring out where they really belong, and for enabling those who would be directly affected by them to have a voice in the process.

The Marfa solar fight

A company wants to build a solar power plant in Marfa, and some residents there don’t like it.

In what she describes as an all-encompassing obsession, [Malinda] Beeman is fighting to preserve that lifestyle, which she and hundreds of other artists have discovered in the West Texas town of Marfa, by waging war with a company that has plans to erect at least 1,000 three-story mirrored satellite dishes — designed to harness the energy of the blisteringly bright desert sun and turn it into electrical power.

Presidio County Judge Jerry Agan and others in this tiny outpost find the opposition from the solar-fighters puzzling. Over the past two decades, creative spirits like Beeman have effectively transformed Marfa from a boarded-up dot on the map into a mecca for writers, painters and sculptors inspired by the desolate landscape. Most of the newcomers are the type you might expect to champion an investment in clean, alternative energy. “It’s astounding to me, because most of the people involved [in the opposition] are pro green power,” Agan says.

Tessera Solar, a London-based company with American headquarters in Houston, plans to install the solar power generation site — the first of its kind in Texas — on about 200 acres of land two miles east of Marfa. Power generated there will help keep the lights on and the air conditioning running some 400 miles east in San Antonio. The company plans to break ground on the project later this year. In its first phase, Tessera plans to install 1,080 of the huge mirrored discs — called SunCatchers — that will generate about 27 megawatts of power. CPS Energy, which supplies gas and electricity for San Antonio, will buy the energy from Tessera. Raul Cardenas, manager of renewable energy programs at CPS, says the initial phase will generate enough power for an average of about 4,000 homes. The project could eventually expand to include twice as many SunCatchers and take up some 600 acres, though Tessera says it’s unlikely the project would grow that large.

[…]

Agan and other longtime locals support the solar initiative; they support most anything that will bring jobs and tax revenue to an area that has long languished economically. But some residents of Antelope Hills — the rural neighborhood next door to the Tessera site — don’t view the project so positively. “The placement of this right here essentially is killing the subdivision,” Beeman says as she drives up to a freshly painted green gate that marks the private property where the solar plant will be erected. “People were going to build their little houses, they were going to add to the tax base, but now they see their property being worthless. It’s a horrible shock.”

There’s not enough information in the story for me to judge who’s “right”. Frankly, both sides may have valid points, and in the end it’ll be a simple matter of who has more juice. The one thing I do know is that if we’re going to get serious about green energy – and we clearly need to get serious about it – we’re going to see a lot more stories like this for the simple reason that as more wind and solar farms get built, more of them will be built near people who don’t want them as their neighbors. I can’t blame anyone for not wanting this in their back yard, and for all I know there is a better location for this one particular plant. But it’s not about this one plant. We did a lousy job as a society of giving people a say in where old-school, big-pollution power plants were located. We should do a better job of that with the next generation of such plants, without losing sight of the fact that we need to make it as reasonably easy as we can to get them built so we can usher out the old generation. Good luck with that.