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New Kaiser Health News data adds political dimension to Covid-19 crisis

[Note: The third data column in the table about a half-dozen paragraphs down was mislabeled when this was initially posted.  It has now been corrected thanks to a good catch by alert reader Denese Whitney.  Trouble in God’s Country appreciates the help.]

Last Thursday I posted a piece suggesting that Covid-19 might constitute a perfect storm for rural Georgia — that old age and poor health status could combine with a frail healthcare delivery system to put rural areas in particular jeopardy.  Since then a couple of reports have come out that support that view and bring certain healthcare and political realities into sharp focus.

First was a report Saturday from Kaiser Health News (KHN) that documented the number of ICU beds available in virtually every U.S. county and compared those numbers with the population of people 60 and older in each of those counties.  That’s not a perfect measure of an older person’s access to critical care, of course; just because there’s not an ICU bed in your home county doesn’t mean there’s not one in the next county or a nearby city.  But it’s not a bad measure of the magnitude of the healthcare challenge taking shape.

The second was a report in today’s Washington Post.  Philip Bump, one of the nation’s top data journalists, took the KHN data and laid it over county-level data from the 2016 presidential election between Donald Trump and Hillary Clinton.

“Comparing the county-level data from Kaiser Health News to 2016 presidential election data,” Bump wrote,  “we discovered a remarkable bit of data: About 8.3 million people who voted for Trump in 2016 live in counties where there are no ICU beds or no hospitals. That amounts to about 13 percent of the total votes Trump earned in that election, or one out of every eight votes.

“Those counties are also home to about 3.8 million people who voted for Hillary Clinton, a figure which makes up only about 5 percent of her total. Most of the counties voted for Trump by wide margins; he won them by an average of 41 points. He won 10 times as many counties with no ICU beds as did Clinton.”

This afternoon I’ve pulled Kaiser’s Georgia data and combined it with data from Georgia’s 2018 gubernatorial election and today’s Georgia Department of Public Health report on the number of people in the state who have tested positive for Covid-19.  (As of mid-day today, that number was up to 600 people from 59 counties; 38 of the “positives” were from “unknown” counties.)

Overall, the situation here in Georgia is a microcosm of the national picture Bump found — and if the primary goal in this situation is to try to meet the healthcare needs of the entire state, state politics, as always, hovers not very far in the background and imposes a set of difficult strictures on the process.

In the 2018 gubernatorial election, Brian Kemp, the Republican nominee who ultimately won and is now governor, largely swept rural Georgia, carrying 130 counties.  Of those, 83 don’t have a single ICU bed (indeed, most don’t even have hospitals).  Combined, those counties have a population of 1.7 million, more than 380,000 of whom (22 percent) are over 60.  So far, only 47 of the state’s 600 confirmed Covid-19 cases hail from those counties, but it seems likely those numbers will rise as testing becomes more available in rural areas.

In contrast, the Democratic nominee, Stacey Abrams, dominated the state’s urban areas, which has a much younger population and much more robust healthcare delivery systems.  Twelve of the 29 counties she carried were indeed rural (including a half-dozen southwest Georgia counties that are now in the orbit of the Covid-19 hotspot erupting in and around Albany) and also boast no ICU beds of their own.  But the overwhelming majority of her support came from urban and suburban areas that are home to large healthcare systems with a good number of ICU beds.

This table illustrates the contrast.

Kemp Abrams ICU Bed Table

The 130 counties Kemp carried are home to right at 52 percent of the state’s 60-plus population but have fewer than a third of the state’s ICU beds.

To use Philip Bump’s Washington Post framework, more than a half-million Georgians who voted for Kemp — about 25 percent of his total — reside in counties without a single ICU bed.  That’s true of only about 10 percent of Abrams’s voters.

Again, rural Georgians who fall victim to Covid-19 may well be able to get access to an ICU bed in Metro Atlanta or another major city if they need it, but the current pandemic does seem to put a sharp new focus on a problem that has bedeviled the state’s Republicans since they took power at the turn of the century — how to provide healthcare to rural areas that constitute their political base.

For a decade now, the state’s GOP leaders have steadfastly refused to take advantage of billions of dollars in Medicaid Expansion funds and presided over a steady stream of rural hospital failures.

I’ll try to do more with this over the next couple of days.  For now, here’s a complete list of Georgia counties with all the data discussed in this post.

County # !CU Beds # Covid-19 Cases Confirmed by DPH 3/22/20 Brian Kemp’s % of 2018 General Election Vote Stacey Abrams’s % of the 2018 General Election Vote Population Aged 60+ Percent Population Aged 60+
Appling 3 0 79.7% 19.9% 4208 22.8%
Atkinson 0 0 74.4% 25.2% 1451 17.5%
Bacon 4 0 86.7% 12.7% 2329 20.6%
Baker 0 0 58.2% 41.4% 919 28.3%
Baldwin 12 2 49.5% 49.8% 9287 20.4%
Banks 0 0 89.8% 9.4% 4207 22.9%
Barrow 6 1 73.6% 25.2% 12454 16.6%
Bartow 21 57 76.1% 22.8% 18389 17.9%
Ben Hill 5 0 63.9% 35.6% 3982 23.1%
Berrien 0 0 85.0% 14.4% 4266 22.4%
Bibb 117 1 38.4% 61.0% 31993 20.8%
Bleckley 0 0 78.6% 20.5% 2860 22.4%
Brantley 0 0 91.3% 8.1% 3792 20.6%
Brooks 0 0 61.5% 38.1% 4099 26.2%
Bryan 0 0 70.1% 28.8% 4985 14.3%
Bulloch 24 0 62.8% 36.3% 11463 15.5%
Burke 0 0 50.6% 48.9% 4540 20.0%
Butts 0 1 71.7% 27.7% 4813 20.4%
Calhoun 0 0 42.7% 57.1% 1362 20.9%
Camden 5 0 65.3% 33.6% 8503 16.3%
Candler 6 0 72.4% 27.2% 2476 22.7%
Carroll 18 14 69.8% 29.1% 20423 17.8%
Catoosa 0 0 79.5% 19.3% 14752 22.4%
Charlton 0 1 75.1% 24.4% 2473 19.1%
Chatham 78 4 40.0% 58.9% 56014 19.6%
Chattahoochee 0 0 54.5% 44.7% 645 5.8%
Chattooga 0 1 79.9% 19.4% 5705 22.9%
Cherokee 15 18 72.1% 26.3% 42210 17.9%
Clarke 104 9 28.6% 70.3% 17345 14.0%
Clay 0 0 45.3% 54.0% 937 31.0%
Clayton 34 13 11.8% 87.8% 36959 13.5%
Clinch 0 0 76.1% 23.6% 1466 21.6%
Cobb 119 61 44.6% 54.0% 120689 16.3%
Coffee 10 0 70.7% 28.8% 7860 18.3%
Colquitt 10 0 75.9% 23.5% 8918 19.4%
Columbia 0 3 66.5% 32.5% 26092 18.2%
Cook 0 0 70.9% 28.7% 3527 20.5%
Coweta 19 8 69.7% 29.1% 25269 18.3%
Crawford 0 0 72.9% 26.4% 2798 22.6%
Crisp 16 0 63.0% 36.6% 5331 23.2%
Dade 0 0 82.5% 16.2% 4079 25.1%
Dawson 0 1 85.9% 13.1% 6208 26.5%
Decatur 10 0 60.2% 39.4% 5831 21.6%
DeKalb 168 45 15.7% 83.4% 121505 16.5%
Dodge 6 0 73.9% 25.7% 4726 22.4%
Dooly 0 0 52.7% 47.0% 3522 25.1%
Dougherty 50 48 29.8% 69.8% 18997 20.8%
Douglas 8 4 39.4% 59.8% 22028 15.7%
Early 0 2 55.2% 44.5% 2739 26.3%
Echols 0 0 88.2% 11.0% 681 17.0%
Effingham 0 2 76.9% 22.0% 9061 15.9%
Elbert 4 0 70.0% 29.5% 5092 26.4%
Emanuel 8 0 70.0% 29.5% 4782 21.3%
Evans 0 0 69.4% 30.2% 2260 21.0%
Fannin 5 0 83.0% 16.1% 8800 35.9%
Fayette 37 9 56.0% 42.7% 25277 22.9%
Floyd 65 9 71.1% 27.8% 20941 21.7%
Forsyth 24 4 70.6% 28.0% 33215 15.7%
Franklin 8 0 86.5% 12.7% 5691 25.5%
Fulton 538 108 26.8% 72.2% 159840 15.8%
Gilmer 0 0 83.7% 15.3% 9166 31.0%
Glascock 0 0 91.4% 8.2% 713 23.6%
Glynn 24 3 63.6% 35.6% 20679 24.8%
Gordon 8 4 81.9% 17.1% 10941 19.4%
Grady 4 0 67.3% 32.3% 5593 22.3%
Greene 0 0 65.1% 34.4% 6034 36.1%
Gwinnett 82 27 42.3% 56.5% 122430 13.8%
Habersham 4 0 83.5% 15.6% 10665 24.3%
Hall 85 9 73.4% 25.5% 36793 19.1%
Hancock 0 0 24.7% 75.0% 2435 28.1%
Haralson 0 0 87.7% 11.5% 6357 22.1%
Harris 0 0 74.0% 25.2% 7948 23.9%
Hart 0 0 76.6% 22.6% 7015 27.5%
Heard 0 1 83.2% 16.1% 2692 23.2%
Henry 40 7 42.0% 57.3% 34127 15.7%
Houston 36 1 57.9% 41.1% 25522 17.0%
Irwin 0 0 75.8% 23.9% 2170 23.4%
Jackson 0 0 81.6% 17.4% 12724 19.9%
Jasper 0 0 74.5% 24.9% 3116 22.7%
Jeff Davis 4 0 82.6% 16.9% 3219 21.5%
Jefferson 0 0 47.0% 52.6% 3828 24.0%
Jenkins 0 0 64.7% 35.0% 2049 22.9%
Johnson 0 0 72.5% 27.2% 2334 23.8%
Jones 0 0 67.8% 31.6% 6333 22.2%
Lamar 0 3 69.4% 29.9% 3955 21.6%
Lanier 0 0 71.3% 28.4% 1972 19.0%
Laurens 16 2 65.9% 33.6% 10610 22.4%
Lee 0 16 74.7% 24.8% 4964 17.0%
Liberty 0 0 36.2% 63.1% 7447 12.0%
Lincoln 0 1 69.4% 29.9% 2318 29.8%
Long 0 0 64.7% 34.4% 2398 13.4%
Lowndes 48 8 57.7% 41.6% 17921 15.7%
Lumpkin 0 1 79.2% 19.3% 7478 23.7%
Macon 0 0 36.9% 62.9% 2925 21.4%
Madison 0 0 78.5% 20.7% 6721 23.5%
Marion 0 0 63.9% 35.3% 2190 25.6%
McDuffie 0 0 60.5% 39.0% 4855 22.6%
McIntosh 0 0 59.5% 40.0% 4475 31.8%
Meriwether 0 0 58.9% 40.4% 5261 24.9%
Miller 0 1 77.9% 21.6% 1561 26.5%
Mitchell 0 0 56.2% 43.5% 4919 21.8%
Monroe 0 1 71.9% 27.2% 6594 24.6%
Montgomery 0 0 76.1% 23.3% 1891 21.1%
Morgan 0 0 71.2% 28.0% 4678 26.0%
Murray 0 0 85.8% 13.4% 7520 19.1%
Muscogee 61 2 38.6% 60.7% 34483 17.4%
Newton 10 4 45.1% 54.3% 18455 17.6%
Oconee 0 1 69.8% 29.0% 7602 21.1%
Oglethorpe 0 0 70.5% 28.4% 3441 23.5%
Paulding 8 4 66.6% 32.5% 21365 14.0%
Peach 0 3 52.2% 47.3% 5201 19.2%
Pickens 6 2 84.8% 14.2% 8464 27.9%
Pierce 0 0 88.9% 10.7% 4228 22.1%
Pike 0 0 85.7% 13.6% 3658 20.4%
Polk 0 4 79.1% 20.1% 8705 21.0%
Pulaski 6 0 69.8% 29.8% 2806 24.6%
Putnam 0 0 71.9% 27.5% 6275 29.3%
Quitman 0 0 55.5% 43.6% 913 42.7%
Rabun 0 0 80.0% 18.8% 5564 34.0%
Randolph 0 1 45.1% 54.4% 2258 31.3%
Richmond 264 10 31.5% 67.7% 38152 18.9%
Rockdale 16 2 32.0% 67.4% 17124 19.4%
Schley 0 0 81.0% 18.3% 1100 21.3%
Screven 0 0 60.4% 39.4% 3450 24.6%
Seminole 0 0 66.7% 32.8% 2541 29.7%
Spalding 22 2 61.2% 37.9% 14777 23.0%
Stephens 6 0 80.7% 18.6% 6327 24.7%
Stewart 0 0 41.8% 58.0% 1209 20.7%
Sumter 10 2 48.8% 50.7% 6539 21.3%
Talbot 0 0 39.5% 59.8% 2045 31.8%
Taliaferro 0 0 38.1% 61.6% 511 27.7%
Tattnall 0 0 76.3% 23.1% 4769 18.8%
Taylor 0 0 62.9% 36.5% 2020 24.4%
Telfair 0 0 66.8% 32.8% 3802 23.3%
Terrell 0 2 45.7% 53.9% 2148 23.9%
Thomas 35 0 61.2% 38.3% 10319 23.0%
Tift 20 2 69.7% 29.7% 8091 20.0%
Toombs 8 0 74.8% 24.8% 5815 21.4%
Towns 0 0 81.7% 17.4% 4566 40.9%
Treutlen 0 0 68.9% 30.8% 1666 24.7%
Troup 20 4 60.9% 38.4% 13380 19.3%
Turner 0 1 63.0% 36.6% 2004 24.9%
Twiggs 0 1 52.7% 46.8% 2395 28.8%
Union 5 0 83.4% 15.6% 8856 39.8%
Upson 28 0 66.8% 32.6% 6294 24.0%
Walker 0 0 81.0% 17.9% 16583 24.2%
Walton 7 0 76.9% 22.4% 17821 20.1%
Ware 22 0 71.7% 27.8% 7974 22.3%
Warren 0 0 46.6% 53.1% 1586 29.3%
Washington 0 0 50.6% 49.1% 4483 21.9%
Wayne 12 0 80.2% 19.1% 6149 20.6%
Webster 0 0 59.9% 40.0% 671 25.5%
Wheeler 0 0 71.1% 28.7% 1550 19.5%
White 0 0 84.5% 14.4% 7553 26.5%
Whitfield 34 2 72.3% 26.8% 18625 17.9%
Wilcox 0 0 73.3% 26.5% 1960 22.0%
Wilkes 0 0 59.0% 40.4% 2863 28.9%
Wilkinson 0 0 55.6% 44.0% 2285 25.0%
Worth 0 2 75.4% 24.1% 5131 24.7%
Totals 2508 562     1,863,154 18.3%

 

 

 

 

One Comment Post a comment
  1. Nicee post thanks for sharing

    October 10, 2022

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