Containment efforts for the COVID-19 Coronavirus are facing significant challenges, with experts suggesting that it may no longer be feasible to prevent its global spread. The virus has a mortality rate of approximately 2-3%, which could lead to a substantial increase in deaths if it becomes as widespread as the flu. Current data indicates around 6,000 cases, with low mortality rates in areas with good healthcare. Vaccine development is underway, but it is unlikely to be ready in time for the current outbreak, highlighting the urgency of the situation. As the outbreak evolves, the healthcare system may face considerable strain, underscoring the need for continued monitoring and response efforts.
Oddly, Kansas reports only 7 hospitalizations (Sheridan reports 25) which seems low for 20 deaths.
Something is amiss. Is the 7 hospitalizations for Gove County? According to the article, they send seriously ill patients to a hospital 50 miles away, which puts them in another county (not sure which one though). Looking at a map of Kansas, Gove County is <40 miles across east-west. The county area is 1,072 sq mi, or something like 35 miles (E-W) x 30.6 miles (N-S), or 34 miles x 31.5 miles.
I compared stats for Kansas and Washington States:
Washington State population 7.615 million (2019)
203797 positive cases, 12649 hospitalizations, 2918 deaths https://www.doh.wa.gov/Emergencies/COVID19/DataDashboard (numbers updated daily)
Kansas State population 2.913 million (2019)
190081 positive cases, 5895 hospitalizations, 2109 deaths https://www.coronavirus.kdheks.gov/160/COVID-19-in-Kansas (The COVID-19 Summary is published Monday, Wednesday and Friday at 12:30 p.m. and includes historical data.)
Hospitalizations averaged approximately 31.67/day from November 25 through December 9, with a total of new hospital admissions of 475. Hospitalization information came from "Reopen Kansas Metrics" page (click on the button).
From the following article, daily new infections in Kansas are running slightly higher than those of Washington state, but rates in Kansas may be falling slightly.
WICHITA, Kan. (KSNW) — The number of people who have tested positive for the Coronavirus in Kansas increased by 4,724 over the weekend. It brings the state’s total since the pandemic began to 190,018.
Gove county was somewhat isolated, and some distance from major metropolitan areas. However, I-70 runs across the northern part of Gove County, and Quinter is on the interstate. Early on, we saw metro areas (higher population density) get hit (particularly those with international and hub airports), and counties along interstates.
I expect USA Today to sensationalize headlines and the story. I don't care much for that practice or the political aspect. I was just interested in the fact that many thought the community had dodged the coronavirus, until they didn't.
By the time commissioners passed the mask mandate on Nov. 16, more than 1 out of every 10 county residents had contracted the virus. At least a dozen of them had died.
Southwest Kansas counties have a total ICU capacity of 22 beds at 18 hospitals for the region's roughly 143,000 residents, state officials report.
On Sept. 1, those hospitals reported 17 ICU patients, including nine hospitalized with COVID-19. By Dec. 7, 18 of the 21 ICU patients were being treated for COVID-19 and only one staffed bed remained open. Another 63 people with COVID-19 filled other in-patient beds.
. . .
Some hospitals have run out of beds and are transferring people to Denver or other cities in Kansas, though the state doesn’t publicly track those numbers. . . .
In contrast,
Sedgwick County (Wichita), 33,554 positive cases, with 199 deaths
Johnson County (Kansas City suburbs, Overland Park, Olathe), 33,144 positive cases, with 346 deaths
Wyandotte County (Kansas City), 13,568 positive cases, with 184 deaths
Shawnee County (Topeka). 9,829 positive cases, with 171 deaths
I expect USA Today to sensationalize headlines and the story. I don't care much for that practice or the political aspect. I was just interested in the fact that many thought the community had dodged the coronavirus, until they didn't.
Another place to watch is Ford County (pop. 33,619 (2019)) and Dodge City (est. pop. 27,329 (2018)) with 4914 cases of COVID-19, but only 10 deaths.
Why are these places to watch? How's Lansdale doing? I don't understand this fascination with small communities (except for the obvious provocation value). I don't see any value in the statistics of small numbers here. There is huge opportunity for error or outlier irrelevancy and no insight that I can see even if the numbers are accurate. E.G., if those numbers are real, what can we do with them?
Sheridan County has a population 2556. With the average US rates we expect 2 deaths. Everything from 0 to ~5 isn't surprising in any way.
Gove County has a population of 2695. 20 deaths here are far higher than normal.
Sheridan County has a population 2556. With the average US rates we expect 2 deaths. Everything from 0 to ~5 isn't surprising in any way.
Gove County has a population of 2695. 20 deaths here are far higher than normal.
The virus is spread by close contact; so we should expect pockets of higher case rates, not an even spread with 1/20 cases throughout the population and a death rate of 0-5 out of every 2,500 people.
#4,449
brainpushups
456
195
Vanadium 50 said:
PS "Republican leaning"? That sounds political to me.
Obviously looking at single towns, or perhaps even cities, there are going to be outliers for in either direction from the national trend by political partisanship. But, in the US at this particular time, there seems to be a correlation between political partisanship and both infection and death rates:
The second link is animated, but you can use the slider at the bottom to see the current sort by partisanship. The button at the top allows you to view the states with least cases instead.
Sensationalizing small town deaths and infection rates is not helpful, but I can understand why that connection is made by news outlets when it is consistent with the national trend.
Obviously looking at single towns, or perhaps even cities, there are going to be outliers for in either direction from the national trend by political partisanship.
If you look at individual counties, there is a correlation between extremes and Republican voting. Because rural counties are small and small samples have large relative fluctuations.
If you look state-by-state I don't think one can draw conclusions. Wave 1 hit blue states harder. Waves 1 and Waves 3 are anticorrelated. Wave 3 hit red states harder. Which is cause and which is effect?
#4,451
brainpushups
456
195
Vanadium 50 said:
If you look state-by-state I don't think one can draw conclusions. Wave 1 hit blue states harder. Waves 1 and Waves 3 are anticorrelated. Wave 3 hit red states harder. Which is cause and which is effect?
I'm not sure about that. Based on the second source I provided above the top 11 states with fewest cases per million are democratic (one neutral) based on the partisanship metric used, and the top 9 states with most cases per million are republican (one neutral). I'm referring to the most recent numbers, not the trend over time.
Same source different chart: top 13 states for death rate are republican and 13 out of 15 of the states with the lowest death rate are democratic.
I'm not making any claim about cause and effect because I could only speculate. Just an observation.
I'm not sure about that. Based on the second source I provided above the top 11 states with fewest cases per million are democratic (one neutral) based on the partisanship metric used, and the top 9 states with most cases per million are republican (one neutral). I'm referring to the most recent numbers, not the trend over time.
V50 said first wave; that link's graphic starts in June. The first wave hammered liberal states, in particular in the New England region. It gets fuzzier when you look at pandemic totals, though, since the testing rates are vastly different for the different waves/stages.
In my view, the media getting to add a partisan zinger is just a bonus; the main motivation I expect, is the media needing stories to drive clicks and sell ad space. And then people post those stores here, as if they are meaningful, when they aren't. PF members should know better.
#4,453
brainpushups
456
195
russ_watters said:
V50 said first wave; that link's graphic starts in June. The first wave hammered liberal states, in particular in the New England region.
I understand that. But the overall rates of infection and deaths right now are distributed differently. My point was that, though it may be misleading for news sources to pick individual towns/cities/counties when they say "Hey look at this case/death rate and the fact that they are democratic/republican" there is a definite correlation between partisanship and case/death rates at the state level.
Maybe that doesn't mean much. Maybe the trend will flip and in a few months we'll see USA Today headlines about how democratic towns have the nations highest death rates and this will reflect a shifted nationwide trend where democratic states are back at the top.
I understand that. But the overall rates of infection and deaths right now are distributed differently. My point was that, though it may be misleading for news sources to pick individual towns/cities/counties when they say "Hey look at this case/death rate and the fact that they are democratic/republican" there is a definite correlation between partisanship and case/death rates at the state level.
Maybe that doesn't mean much. Maybe the trend will flip and in a few months we'll see USA Today headlines about how democratic towns have the nations highest death rates and this will reflect a shifted nationwide trend where democratic states are back at the top.
I think it's unlikely to flip back, but no, I don't recall the news media taking the opportunity to point out the partisan disparities in the other direction when they existed/had the opportunity. What I remember from the media analysis in the spring was a heavy focus on racial disparities...which is related, but a different spin.
[edit]
At least in the spring, such stories had statistical relevance so they were worthy of discussion. But the political spin is, again, just an excuse to politicize what is primarily an issue of demographics (who lives in cities?).
There's certainly some value in doing a real analysis of things like mask mandate effects, but care needs to be taken to focus on the issue and analyze it properly to avoid the political bias, rather than crafting the analysis to support the bias.
#4,455
OmCheeto
Gold Member
2,482
3,408
Regardless of how this current argument turns out, I would just like to say that I've found these Dan Goodspeed graphics simply fascinating.
The correlation between deaths per million and the Cook Political Index is -0.10. Republican defined as positive, so the fatality rate is incrementally lower in red states. But 0.1 is very low - it means 1% of the effect could possibly be ascribed to this factor. I think this makes a pretty strong case that the partisan effect is chasing ghosts.
I am, of course, prepared to believe that if you remove the period of time when blue states did worse you find they do better. However, I don't think that tells us anything - it's pretty close to a tautology.
If one insists that surely this is real, I feel compelled to point out that this correlation is weaker than death rate and alphabetical order (0.11) and much weaker than death rate and state name length (0.36). And my favorite - the death rate is positively correlated (0.2) with the number of negative tests.
#4,457
brainpushups
456
195
Vanadium 50 said:
The correlation between deaths per million and the Cook Political Index is -0.10. Republican defined as positive, so the fatality rate is incrementally lower in red states. But 0.1 is very low - it means 1% of the effect could possibly be ascribed to this factor. I think this makes a pretty strong case that the partisan effect is chasing ghosts.
That's a good point. I had overlooked that Goodspeed's charts are only accounting for numbers since July so they tell a different story than if we were counting from January. My mistake.
It's expected that Moderna's vaccine will get emergency use authorization (EUA) in the US in two days, first vaccinations with it could start early next week.
It would become the fifth vaccine with such an approval somewhere, and the second in Western countries.
Tozinameran (BioNTech, Pfizer), is quickly accumulating approvals internationally.
BBIBP-CorV got an EUA in China in July (!) and a full approval in UAE and Bahrain in the last week.
CoronaVac got an EUA in China in July (!)
Sputnik V got an EUA in Russia in August
GOVE COUNTY, Kan. (KWCH) - With numbers showing that about one out of every 132 of its people has died from COVID-19, a report published last week in USA Today calls Gove County “The deadliest place in America.” The distinction comes because, as of last Thursday (Dec. 10) COVID-19 has killed a higher percentage of Gove County residents than any other county in the U.S. As of late last week, there were 20 COVID-19-related deaths in the county with a population of about 2,600 residents.
While COVID-19 has hit the rural community hard, Eyewitness News spoke with Gove County Medical Center CEO David Caudill who said recent numbers tell a different story, showing improvements from the past couple of months. In October, Caudill was among 50 employees at the hospital in Quinter who tested positive for COVID-19. In response to a spike in cases, the Gove County Commission on Nov. 23 passed an emergency resolution that requires masks in public.
Gove County Sheriff Alan Weber has been hospitalized since mid-October and has been on a ventilator for weeks at a hospital in Denver (about 280 miles W from Quinter).
I couldn't readily find out about Lansdale (Pa, I presume), but I found the Montgomery county (PA) dashboard, and the state dashboard, which oddly, don't agree (with the state showing higher numbers).
https://data-montcopa.opendata.arcgis.com/pages/covid-19 (Dec 15, 2020)
Montgomery County, Pa (pop. 830,915 (2019)), Lansdale, Pa (pop. 16,707 (2018))
Positive cases 27394 cumulative (3.30% of population)
Hospitalizations 536 current
Active Cases ??
Deaths 941 (since March 7, 2020) 0.113% of population
Alternatively, from the Pa state dashboard with slightly higher number (??). https://www.health.pa.gov/topics/disease/coronavirus/Pages/Cases.aspx
Montgomery County
Total Cases: 29,234
Confirmed: 28,116
Probable: 1,118
Negative: 242,335
Cases per 100,000: 3,528.1
Deaths: 1,018
Deaths per 100,000: 122.9
For comparison, some counties with which I am familiar. Both Wa and NY have some kind of mask mandate, but certainly there are folks who do not wear masks. From observation, the non-compliance to the mandate seems somewhat higher in Benton-Franklin than in Dutchess Co.
Dutchess County, NY (pop. 294,218 (2019)) = 0.354 * Montgomery Co, Pa
Positive cases 9146 cumulative (0.334 * Montgomery Co, Pa) (3.11% of population), so similar to Montgomery.
Active Cases 1366
Deaths 206 (0.218 * Montgomery Co, Pa), 0.070% of population, slightly lower compared to Montgomery https://www.dutchessny.gov/Departments/DBCH/covid-19-dashboard.htm
Benton County, WA (pop. 204,390 (2019)) + Franklin County, WA (95,222 (2019)) https://www.doh.wa.gov/Emergencies/COVID19/DataDashboard
Positive cases 10052 (Benton), 7789 (Franklin) 17850 total cases (5.96% of pop)
Hospitalizations 576 (Benton), 430 (Franklin) cumulative
Deaths 150 (Benton), 77 (Franklin) 227 total deaths, 0.076 % of population
Two very rural counties in WA with low incidence, and not deaths, so far.
Garfield County, WA (pop. 2,247 (2018)) - last county to have 0 cases
Positive cases 61
Hospitalizations 3
Deaths 0
Wahkiakum County, WA (pop. 4,426 (2018))
Positive cases 44
Hospitalizations 0
Deaths 0
Code:
Top 15 Counties and least populous county in NY, by population, Pos. Cov and deaths
County Pop. 2019 Pos. Covid % of pop Deaths % of pop
1 Kings 2,559,903 102995 4.02% 5266 0.206%
2 Queens 2,253,858 104668 4.64% 5251 0.233%
3 New York 1,628,706 53345 3.28% 2180 0.134%
4 Suffolk 1,476,601 76625 5.19% 2132 0.144%
5 Bronx 1,418,207 72409 5.11% 3470 0.245%
6 Nassau 1,356,924 72122 5.32% 2304 0.170%
7 Westchester 967,506 59991 6.20% 1575 0.163%
8 Erie 918,702 33793 3.68% 983 0.107%
9 Monroe 741,770 24293 3.28% 375 0.051%
10 Richmond 476,143 28810 6.05% 831 0.175%
11 Onondaga 460,528 15722 3.41% 288 0.063%
12 Orange 384,940 19892 5.17% 469 0.122%
13 Rockland 325,789 24334 7.47% 554 0.170%
14 Albany 305,506 8214 2.69% 173 0.057%
15 Dutchess 294,218 9482 3.22% 208 0.071%
62 Hamilton 4,416 70 1.59% 1 0.023%
Now interestingly, the population of NY State is ~19.45 million (2019) and number of tests as of today for Coronavirus is 22,316,327. It's possible health care workers have been tested more than once, although I thought the cumulative number was supposed to be one individual.
I don't understand this fascination with small communities (except for the obvious provocation value).
My interest in rural counties, or small communities, relates to several interests. The first five years of my life, I lived in two small towns, then my family moved to the suburbs of a large city. I started university in a large city then transferred to a state university in a moderate size city. In my professional life, I've lived in two semi-rural areas outside of two small cities. When I leave my current job, I'll be looking for opportunities in small rural areas, and I believe that rural areas are underserved, particularly regarding healthcare.
I was interested to see if Gove County actually had a high rate as claimed. I suppose on some per capita level, it may, but I haven't satisfied myself yet. I'm also curious about several areas where I have lived, or had some experience. Some are listed above.
Clearly, some places thought that they were not vulnerable and wearing masks was not a strong local practice. I have limited first hand experience, but having a high proportion of the population wearing masks and maintaining social distancing to the extent possible does mitigate the spread of infection and does save lives. Until one receives a vaccine, the best defense is wearing a mask and limiting social contact outside the immediate family.
One does have to be careful with raw data and statistics, and numbers reported by others.
Code:
Selected small counties in Montana
Rank County Pop (2019) Pos Cov % of pop Deaths % of pop
37 Mineral 4,397 111 2.52% 0 0%
43 Liberty 2,337 97 4.15% 1 0.043%
44 Wheatland 2,126 119 5.60% 6 0.282%
I passed through Mineral and Wheatland Counties several months ago. Unfortunately, I didn't have time to stay. Liberty County is on the border with Canada and is pretty remote. Mineral County has I-90 running through it (but probably not a lot of folks stopping), while Wheatland County has US12 running through it (mostly local traffic).
As of 2020, there are currently 3,143 counties and county-equivalents in the 50 states and the District of Columbia. If the 100 county equivalents in the U.S. territories are counted, then the total is 3,243 counties and county-equivalents in the United States. Ideally, someone would do some big data analysis of the pandemic and determined why some counties had low incidence of infection/mortality and others higher.
Caveat: some data may have been updated while I was composing this post.
The USA Today article contains many anecdotes about controversy over mask wearing, but exactly zero statistics about it. Maybe that was a factor, maybe it wasn't; the article doesn't present a data-backed case. That's how the media works; primarily what gets clicks and views is compelling stories. Data is boring and is best avoided. Facts are nice to have, but aren't critical when crafting a compelling story. The narrative is what matters.
I couldn't readily find out about Lansdale (Pa, I presume), but I found the Montgomery county (PA) dashboard, and the state dashboard, which oddly, don't agree (with the state showing higher numbers).
I track Montgomery County data daily, with my own spreadsheet, so I'm fully aware of the status and evolution of the pandemic here. My point is that data on small towns is not very useful for insightful analysis or broad conclusions. Turns out, Pennsylvania doesn't consider small towns even relevant enough to report data for towns like Lansdale. And why should they? In the half hour drive to my parents' place in Lansdale, I drive through at least 5 towns of a few thousand residents, while remaining in Montgomery County.
Montgomery County, on the other hand, is larger than North Dakota by population. But it's not a state, so it doesn't get listed on charts of states. As if the title "state" means anything when analyzing data.
As of 2020, there are currently 3,143 counties and county-equivalents in the 50 states and the District of Columbia. If the 100 county equivalents in the U.S. territories are counted, then the total is 3,243 counties and county-equivalents in the United States. Ideally, someone would do some big data analysis of the pandemic and determined why some counties had low incidence of infection/mortality and others higher.
I'm certain people will. And I'm certain much of it will be spun to fit agendas, and even when people try to do honest analysis it will be difficult to keep biases at bay and draw salient conclusions. There are a lot of variables to account for and the data is very noisy.
The attached image linked above shows the infection rate by county.
The first wave was not anticipated nor was anyone ready. Also, it hit the coastal areas first. You can't compare the first wave to this one.
The very first case in the US was a few miles from my home, in January! And I think I had it all through February and into March. Comparing that to people getting infected today is illogical. No one was pushing the use of masks until March or April. In fact the recommendation for use of masks was delayed due to shortages for medical workers.
Yes, that's my point. And at the next level, you also can't really compare pandemic totals either, because of the differences between the waves:
1. For case rates, most of the cases in the first wave went undiagnosed.
2. The severity of the first wave impacts the severity of subsequent waves.
There's going to have to be analysis done - and I'm sure it will be - but making sense of the [spread of the] pandemic will not be an easy task.
One thing I'm noticing for the current wave that I find interesting is that while google tells me there are some, I'm seeing a lot fewer reports of temporary field hospital deployment during the current wave than in the first one.
I can't believe people are still arguing "My political tribe is doing better! You just have to look at the data the right way!"
OK, so my numbers proved unconvincing. Here's the scatter plot. Cook Political index is on the x-axis and deaths per million is on the y-axis.
Do you see a trend there? I sure don't. People who are arguing that their political tribe is doing best are starting with the conclusion and fiddling with the data to support it. They sure aren't looking at the above data and drawing conclusions from it.
#4,465
brainpushups
456
195
Vanadium 50 said:
Do you see a trend there? I sure don't. People who are arguing that their political tribe is doing best are starting with the conclusion and fiddling with the data to support it. They sure aren't looking at the above data and drawing conclusions from it.
Perhaps part of the problem is that people are considering different time periods. When you look at the data from January there is (currently) no correlation as you point out and all states are doing poorly. If folks want to slice up the time intervals trends may be noticed. For example, taking data from July 1 there is a positive correlation (r = 0.5) with the partisan index and death rate (again letting Republican partisan index being greater than zero).
Whether or not the partisan divide plays a cause/effect relationship with any of these sub intervals probably can't be determined with certainty.
I consider this an example of starting with the conclusion, and figuring out what cuts are needed to get the data to show it.
#4,467
brainpushups
456
195
Vanadium 50 said:
I consider this an example of starting with the conclusion, and figuring out what cuts are needed to get the data to show it.
Maybe. Maybe not. I don't think it is unreasonable to look at different time intervals and I can imagine that some folks looked into this without being motivated by partisanship.
Whether or not a person has a partisan motivation behind looking at sub-intervals might be irrelevant if we communicate more clearly about the specific intervals being observed and follow basic statistics 101: don't draw cause/effect conclusions from observational data.
Maybe. Maybe not. I don't think it is unreasonable to look at different time intervals and I can imagine that some folks looked into this without being motivated by partisanship.
I agree. My complaint is fairly specific to the types of stories posted in this thread recently. They are basically saying; "Red states/counties/towns/households/people are managing the pandemic poorly because they are red." Period. Little or no context and no or cherry-picked data, with heavy emphasis on anecdotal narratives. These are not scientific reports.
If a statement is made that reds are doing poorly "today", then there needs to be a broader context provided to avoid the implication that it's just a political cheap-shot. My first reaction on seeing these stories was; who cares about Bumblefrick, Kansas? Does this really tell us anything useful about the pandemic? Why is this newsworthy? Then I realize I know the answer to that.
I'm seeing a lot fewer reports of temporary field hospital deployment during the current wave than in the first one.
Well, they weren't exactly needed then. And beside, who cares about people dying in Bumblefrick, Kansas. Their plight is only important in that it generates clicks. (OK, I'm feeling cynical)
It's not so clear what can or should reasonably done. Gove County - "Bumblefrick" had 20 fatalities, so they must have had ~40 hospitalizations, even though Kansas says 7. They have 21 beds in that county, so it sure looks like a mismatch. Kansas as a whole has about the same number of hospital beds per person as the US as a whole, but the majority is in the eastern half of the state.
Is plopping down a field hospital with maybe 100 beds really a better solution than sending people to an existing facility if it's 50 miles away? Pre-Covid, people would have to do this (travel to a hospital) all the time for anything non-routine, and nobody seemed to care. Because Bumblefrick.
