COVID-19 Coronavirus Containment Efforts

[russ_watters]

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?

 

[mfb]

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.

Even combined it would be an anomaly.

 

[PeroK]

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.

 

[brainpushups]

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:

https://www.nature.com/articles/s41562-020-00977-7
https://dangoodspeed.com/covid/total-cases-since-june

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.

 

[Vanadium 50]

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?

 

[brainpushups]

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.

 

[russ_watters]

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.

 

[brainpushups]

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.

 

[russ_watters]

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.

 

[OmCheeto]

Regardless of how this current argument turns out, I would just like to say that I've found these Dan Goodspeed graphics simply fascinating.

And reading through his text below his "90-day rolling impact" graphic, it seems he's run into the same problems I've had.

ps. If I were Covid-19, my theme song would be "One Way or Another", by Blondie.

"One way, or another, I'm going to find ya​

I'm going to get you get you get you get ya"​

 

[Vanadium 50]

Some facts:

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.

 

[brainpushups]

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.

 

[mfb]

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.

https://www.cnbc.com/2020/12/15/cov...ata-meets-expectations-for-emergency-use.html

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

 

[Astronuc]

Why are these places to watch? How's Lansdale doing?

Lack of people wearing masks during a pandemic has consequences. Incidentally, some folks from Quinter (Gove County) have been interviewed following the article in USAToday.
https://www.kwch.com/2020/12/14/nat...-kansas-community-deadliest-place-in-america/

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

https://www.bfhd.wa.gov/cms/One.aspx?portalId=10766056&pageId=16584954
Positive cases 17836 (ahead of state dashboard numbers)
Hospitalizations 386 (current in Benton-Franklin)

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

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.

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.

 

[russ_watters]

Lack of people wearing masks during a pandemic has consequences. Incidentally, some folks from Quinter (Gove County) have been interviewed following the article in USAToday.
https://www.kwch.com/2020/12/14/nat...-kansas-community-deadliest-place-in-america/

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.

 

[Ivan Seeking]

Yeah, it's a real mystery.
https://coronavirus.jhu.edu/us-map

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.

Party support by county.

https://www.nytimes.com/interactive/2016/11/01/upshot/many-ways-to-map-election-results.html

 

[russ_watters]

You can't compare the first wave to this one.

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.

 

[russ_watters]

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.

 

[Vanadium 50]

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.

 

[brainpushups]

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.

 

[Vanadium 50]

If folks want to slice up the time intervals

I consider this an example of starting with the conclusion, and figuring out what cuts are needed to get the data to show it.

 

[brainpushups]

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.

 

[russ_watters]

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.

 

[Vanadium 50]

Here's Covid mortality vs. the number of negative tests, state by state:

FWIW, I believe this is in fact real.

 

[Vanadium 50]

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.

 

[atyy]

Tom Cruise scolds Mission Impossible crew for not social distancing in leaked audio
https://www.nbcnews.com/pop-culture...t-outburst-covid-era-anxieties-power-n1251456

 

[Astronuc]

Oddly, Kansas reports only 7 hospitalizations (Sheridan reports 25) which seems low for 20 deaths.

I believe the 7 hospitalizations reflects 'active' hospitalizations as opposed to cumulative.

I searched and found Gove County Health Department data and made a timeline. Between March 01 and October 04, there were a total of 101 positive cases and no deaths. The first (2) deaths occurred between October 4 and 7. As of November 25, there were 20 deaths, but then none since. In the timeline below, the second active refers to active hospitalizations.

Oct 04, 2020 - 101 positive cases cumulative, 67 active cases; 12 hospitalizations cum., 4 active, and 0 deaths
Oct 07, 2020 - 115 positive cases cumulative, 77 active cases; 16 hospitalizations cum., 3 active, and 2 deaths
Oct 12, 2020 - 136 positive cases cumulative, 63 active cases; 21 hospitalizations cum., 3 active, and 2 deaths
Oct 16, 2020 - 148 positive cases cumulative, 39 active cases; 26 hospitalizations cum., 5 active, and 9 deaths
On October 18, Gove County Sheriff Allan Weber was flown to the Swedish Medical Center in Denver Colorado in respiratory distress due to Covid 19 complications. Upon arrival, he was intubated, put on a ventilator and placed in the Intensive Care Unit.
Oct 21, 2020 - 162 positive cases cumulative, 34 active cases; 28 hospitalizations cum., 6 active, and 10 deaths
Oct 23, 2020 - 171 positive cases cumulative, 29 active cases; 29 hospitalizations cum., 5 active, and 11 deaths
Oct 28, 2020 - 182 positive cases cumulative, 28 active cases; 30 hospitalizations cum., 2 active, and 12 deaths
Oct 30, 2020 - 185 positive cases cumulative, 23 active cases; 31 hospitalizations cum., 2 active, and 12 deaths
Nov 02, 2020 - 202 positive cases cumulative, 25 active cases; 35 hospitalizations cum., 3 active, and 16 deaths
Nov 04, 2020 - 213 positive cases cumulative, 33 active cases; 37 hospitalizations cum., 4 active, and 18 deaths
Nov 06, 2020 - 220 positive cases cumulative, 39 active cases; 41 hospitalizations cum., 3 active, and 19 deaths
Nov 16, 2020 - 245 positive cases cumulative, 29 active cases; 59 hospitalizations cum., 9 active, and 19 deaths
Nov 20, 2020 - 263 positive cases cumulative, 40 active cases; 61 hospitalizations cum., 12 active, and 19 deaths
Nov 23, 2020 - 272 positive cases cumulative, 40 active cases; 62 hospitalizations cum., 8 active, and 19 deaths
Nov 25, 2020 - 283 positive cases cumulative, 49 active cases; 62 hospitalizations cum., 8 active, and 20 deaths
Dec 02, 2020 - 294 positive cases cumulative, 35 active cases; 69 hospitalizations cum., 6 active, and 20 deaths
Dec 07, 2020 - 297 positive cases cumulative, 17 active cases; 73 hospitalizations cum., 7 active, and 20 deaths
Dec 09, 2020 - 299 positive cases cumulative, 17 active cases; 75 hospitalizations cum., 5 active, and 20 deaths

12/14: "On 12/13/20 Allan went into cardiac arrest while he was at PAM Speciatly Hospital. They do not know the exact amount of time he was without oxygen. His code lasted 15 mins after they found him unresponsive, after three rounds of epinephrine and shocking him they were able to get him back. He was transferred to Denver Health and the care at Denver Health has been beyond amazing."

I hope Sheriff Allan Weber pulls through.

Ref: https://www.facebook.com/govecocovid19/

 

[mfb]

Here's Covid mortality vs. the number of negative tests, state by state:

Wouldn't it make more sense to divide negative tests by population, too?
Number of negative tests is very similar to the total number of tests now. Early in the pandemic that was different.

 

[Vanadium 50]

We have a winner! (Sort of)

The mortality rate is correlated with population. As are the number of positive tests (0.96) and negative tests (0.90) However, it turns out the population is only correlated with mortality rate at 0.08, so I suspect that about 2/3 of the effect is random noise.

And random noise is clearly a factor, since the correlation with nonsensical quantities like state names is even larger than the "signal" being bandied about.

 

[Ivan Seeking]

We have a winner! (Sort of)

The mortality rate is correlated with population. As are the number of positive tests (0.96) and negative tests (0.90) However, it turns out the population is only correlated with mortality rate at 0.08, so I suspect that about 2/3 of the effect is random noise.

And random noise is clearly a factor, since the correlation with nonsensical quantities like state names is even larger than the "signal" being bandied about.

Geography correlates with behavior. There is nothing silly about it.

People who are infected and don't wear masks, spread the virus. Right?

 

[mfb]

Moderna studied how many people tested positive at the time of the second dose (28 days after the first one). The vaccinated group had ~1/3 the rate of positive tests of the placebo group, suggesting that the vaccine is very effective against asymptomatic infections as well (even after the first dose). That's good news for other mRNA vaccines, too.
Source

Vaccination trackers have started.
Worldwide - at the moment only the UK has data at 0.2% of the population
By US state - they seem to use doses and people interchangeably which confuses me. There should be a factor 2. All data there are plans. Generally the expectation seems to be that states get enough doses by the end of the year to give ~5% of their population the first dose. Most of these will be healthcare workers.

 

[PeroK]

Geography correlates with behavior. There is nothing silly about it.

People who are infected and don't wear masks, spread the virus. Right?

The problem is that the data is complex enough that it may be genuinely difficult to extract conclusive evidence for that; and, someone with a particular poltical agenda can look at the data differently to reject the conclusion.

The best/worst example I can remember of this was when the Scottish government began paying undergraduate university fees. The English Conservative government was/is opposed to this - and in England students have to take out a student loan.

One English Conservative looked at the data and concluded that students from poorer backgrounds were less likely to go to university in Scotland because their fees were being paid!

I've always remembered that because that's about as mad as politics can get.

I might say that, for an unknown reason, Scotland was still struggling to get more students from poorer backgrounds to go to university despite their fees being paid. Not because of it.

 

[Borg]

Tom Cruise scolds Mission Impossible crew for not social distancing in leaked audio
https://www.nbcnews.com/pop-culture...t-outburst-covid-era-anxieties-power-n1251456

I had heard about it but didn't check out the audio until this morning. He does sound a bit upset.

 

[Jarvis323]

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.

View attachment 274435Do 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.

I guess, due to the many confounding factors, it is difficult to compare political influences. Rural areas are usually more republican leaning. Rural areas are also less densely populated. And it seems that for the most part, they are getting hit later, with right now being the beginning of a surge. There is also a difference in attitude once it starts hitting. At my hometown, even staff at the clinic weren't taking it seriously and even believed it was a hoax. But as soon as someone close to them was hospitalized, they started freaking out.

I propose instead that you should be comparing based on the measures and adherence to them. If there are compelling correlations with mask use, distancing, etc, and there are correlations with political affiliation and those measures, then you might have something fairly solid to talk about.

In my personal opinion, I think that preventative measures work, but are limited in effectiveness when not taken far enough and/or not adhered to strongly enough. We see clearly from the success of many countries (particularly in Asia) that measures can work very well. But perhaps due to culture differences, many countries tend to have populations which act more or less responsibly overall. And also, which have worse or better guidance and resources.

In places like the US, we see a somewhat half baked response, coupled with half baked adherence. There is no doubt also some political correlation, but the entire county is not doing so good. We have public officials (poor response, messaging, etc) and the public (poor adherence) both to blame I guess. It makes sense to talk about the political influence, but yes, lying with statistics is pretty easy (e.g. cherry picking, not correcting for population density, accounting for time, etc, etc. etc.).

 

[Jarvis323]

I had heard about it but didn't check out the audio until this morning. He does sound a bit upset.

It's funny because the day before, there was a lot of media buzz about Tom's cake gifting. He sends cakes to a whole bunch of people for Christmas. I guess that was his PR team doing some preemptive damage control. Even though I doubt it will hurt him anyways.