Coronavirus

[rb]

Now we're talking state bankruptcies. That's surely gonna work out well for the economy.

 

https://www.reuters.com/article/us-health-coronavirus-usa-states/mcconnell-says-he-favors-state-bankruptcy-over-more-federal-aid-idUSKCN2242U7

[Dalal.Holdings]

Now we're talking state bankruptcies. That's surely gonna work out well for the economy.

 

https://www.reuters.com/article/us-health-coronavirus-usa-states/mcconnell-says-he-favors-state-bankruptcy-over-more-federal-aid-idUSKCN2242U7

 

Especially considering that the Fed now probably holds a good chunk of these bonds...

[patience_and_focus]

While we are talking about how this virus is a curveball and we keep learning new things, here is another one -

 

Alarmed as COVID patients' blood thickened, New York doctors try new treatments

https://www.reuters.com/article/us-health-coronavirus-usa-blood/alarmed-as-covid-patients-blood-thickened-new-york-doctors-try-new-treatments-idUSKCN22421Z

 

In many subjects showing up in hospitals, no typical symptoms of covid-19 but stroke or kidney complications.

 

"At Mount Sinai, nephrologists noticed kidney dialysis catheters getting plugged with clots. Pulmonologists monitoring COVID-19 patients on mechanical ventilators could see portions of lungs were oddly bloodless. Neurosurgeons confronted a surge in their usual caseload of strokes due to blood clots, the age of victims skewing younger, with at least half testing positive for the virus."

 

“I’ve never seen any other viruses causing that,” Jabbour said.

 

 

 

[clutch]

Just to share the potential backfire of relying on prediction models...

 

In Ontario, Canada, the health experts had "projected just under 1,600 COVID-19 deaths, 80,000 cases by end of April."

 

They had expected the hospitals to become full and ramped up the capacities, preparing for the surge.

 

As of April 22, 12,245 cases have been reported, significantly lower than the predicted number. Hospital beds are empty, and plenty of ICUs and ventilators are available.

 

Meanwhile, deaths are relatively still high, at 659 as of April 22. This is because long-term care facilities have become epicenters of the outbreak. Half of the deaths have come from long-term care facilities. They are now relocating the staffing and resources from hospitals to long-term care homes. Maybe the government should have focused on protecting the most vulnerable from the get-go (old age + living in shared housing).

 

These prediction models are not crystal balls. Yet, we seem to be relying more and more on them to make decisions that could lead to this kind of negative, unexpected consequences.

[RichardGibbons]

These prediction models are not crystal balls. Yet, we seem to be relying more and more on them to make decisions that could have this kind of negative consequences.

 

Yeah, models aren't perfect, but I don't really see an alternative. Is there one?

[samwise]

These prediction models are not crystal balls. Yet, we seem to be relying more and more on them to make decisions that could have this kind of negative consequences.

 

Yeah, models aren't perfect, but I don't really see an alternative. Is there one?

 

An alternative is feedback from experience. If we find there is a lot of capacity, then we can open up a bit. If they start trending towards overload, reduce social contacts a bit.

 

The risk is the feedback takes a couple of weeks to show in the data, so probably still a good idea to keep refining the models and have some foresight. Another risk is if the population can be controlled with that granularity.

 

One path through the epidemic is to keep hospitals just below full capacity. Assuming the only concern we have is higher death rate with healthcare overload.

[arcube]

The doctor who led the federal agency involved in developing a coronavirus vaccine said on Wednesday that he was removed from his post after he pressed for a rigorous vetting of a coronavirus treatment embraced by President Trump. The doctor said that science, not “politics and cronyism” must lead the way.

Dr. Rick Bright was abruptly dismissed this week as the director of the Department of Health and Human Services’ Biomedical Advanced Research and Development Authority, or BARDA, and as the deputy assistant secretary for preparedness and response.

Instead, he was given a narrower job at the National Institutes of Health. “I believe this transfer was in response to my insistence that the government invest the billions of dollars allocated by Congress to address the Covid-19 pandemic into safe and scientifically vetted solutions, and not in drugs, vaccines and other technologies that lack scientific merit,” he said in a statement to The Times’s Maggie Haberman.

“I am speaking out because to combat this deadly virus, science — not politics or cronyism — has to lead the way,” he said.

 

 

The White House declined to comment. A spokeswoman for Alex Azar, the health and human services secretary, did not immediately respond to an email seeking comment. The medical publication Stat reported on Tuesday that Dr. Bright had clashed with Bob Kadlec, the assistant health secretary for preparedness and response.

Dr. Bright, who noted that his entire career had been spent in vaccine development both in and outside of government, has led BARDA since 2016.

In the statement, he said: “My professional background has prepared me for a moment like this — to confront and defeat a deadly virus that threatens Americans and people around the globe. To this point, I have led the government’s efforts to invest in the best science available to combat the Covid-19 pandemic.

“Unfortunately, this resulted in clashes with H.H.S. political leadership, including criticism for my proactive efforts to invest early into vaccines and supplies critical to saving American lives. I also resisted efforts to fund potentially dangerous drugs promoted by those with political connections,”

 

Dr. Bright, who is a career official and not a political appointee, pointed specifically to the initial efforts to make chloroquine and hydroxychloroquine widely available before it was scientifically tested for efficacy with the coronavirus.

“Specifically, and contrary to misguided directives, I limited the broad use of chloroquine and hydroxychloroquine, promoted by the administration as a panacea, but which clearly lack scientific merit,” he said.

 

“While I am prepared to look at all options and to think ‘outside the box’ for effective treatments, I rightly resisted efforts to provide an unproven drug on demand to the American public,” Dr. Bright said, describing what ultimately happened: “I insisted that these drugs be provided only to hospitalized patients with confirmed Covid-19 while under the supervision of a physician.

 

“These drugs have potentially serious risks associated with them, including increased mortality observed in some recent studies in patients with Covid-19.

[Guest cherzeca]

"The number of U.S. coronavirus-linked deaths in long-term care facilities including nursing homes has eclipsed 10,000, as facility owners said they are still struggling to access the testing they need to detect and curb outbreaks."  https://www.wsj.com/articles/coronavirus-deaths-in-u-s-nursing-long-term-care-facilities-top-10-000-11587586237?mod=hp_lead_pos1

 

this is gross negligence.  shutting down access to nursing homes and focusing all mitigation resources on the elderly rather than ordering sheltering in place for non-elderly would have been common sense.  dont look to Fauci and birx for common sense. 

[clutch]

These prediction models are not crystal balls. Yet, we seem to be relying more and more on them to make decisions that could have this kind of negative consequences.

 

Yeah, models aren't perfect, but I don't really see an alternative. Is there one?

 

Make decisions based on the most pertinent observations? E.g., the fact that COVID-19 has significantly higher death rates in older people.

 

In general, scientists should inform decision-makers primarily based on observations/experiments, not prediction models. People are getting delusional regarding these models... thinking that they can accurately predict the future if the models are built by scientists.

[John Hjorth]

These prediction models are not crystal balls. Yet, we seem to be relying more and more on them to make decisions that could have this kind of negative consequences.

 

Yeah, models aren't perfect, but I don't really see an alternative. Is there one?

 

Make decisions based on the most pertinent observations? E.g., the fact that COVID-19 has significantly higher death rates in older people.

 

In general, scientists should inform decision-makers primarily based on observations/experiments, not prediction models.

 

Easy to say, when the matter at hand is basically unknown from the beginning of the situation.

[clutch]

These prediction models are not crystal balls. Yet, we seem to be relying more and more on them to make decisions that could have this kind of negative consequences.

 

Yeah, models aren't perfect, but I don't really see an alternative. Is there one?

 

Make decisions based on the most pertinent observations? E.g., the fact that COVID-19 has significantly higher death rates in older people.

 

In general, scientists should inform decision-makers primarily based on observations/experiments, not prediction models.

 

Easy to say, when the matter at hand is basically unknown from the beginning of the situation.

 

It was well-known for this particular case, which was at the end of March.

[Guest cherzeca]

These prediction models are not crystal balls. Yet, we seem to be relying more and more on them to make decisions that could have this kind of negative consequences.

 

Yeah, models aren't perfect, but I don't really see an alternative. Is there one?

 

Make decisions based on the most pertinent observations? E.g., the fact that COVID-19 has significantly higher death rates in older people.

 

In general, scientists should inform decision-makers primarily based on observations/experiments, not prediction models.

 

Easy to say, when the matter at hand is basically unknown from the beginning of the situation.

 

this is BS Hj.  the early data from china was definitive on excessive impact on elderly.  and we knew the genomics of this virus very early on.  we were not operating in the dark, we were just operating stupidly.

[patience_and_focus]

These prediction models are not crystal balls. Yet, we seem to be relying more and more on them to make decisions that could have this kind of negative consequences.

 

Yeah, models aren't perfect, but I don't really see an alternative. Is there one?

 

Make decisions based on the most pertinent observations? E.g., the fact that COVID-19 has significantly higher death rates in older people.

 

In general, scientists should inform decision-makers primarily based on observations/experiments, not prediction models. People are getting delusional regarding these models... thinking that they can accurately predict the future if the models are built by scientists.

 

The only thing that is delusional is to believe that people who have spent all their lives in this area (doctors in the area of infectious diseases, diagnostic, vaccine and drug development experts, and yes, epidemiologist) make decisions solely based on models and not update their hypothesis based on hard data on the ground.

[clutch]

These prediction models are not crystal balls. Yet, we seem to be relying more and more on them to make decisions that could have this kind of negative consequences.

 

Yeah, models aren't perfect, but I don't really see an alternative. Is there one?

 

Make decisions based on the most pertinent observations? E.g., the fact that COVID-19 has significantly higher death rates in older people.

 

In general, scientists should inform decision-makers primarily based on observations/experiments, not prediction models. People are getting delusional regarding these models... thinking that they can accurately predict the future if the models are built by scientists.

 

The only thing that is delusional is to believe that people who have spent all their lives in this area (doctors in the area of infectious diseases, diagnostic, vaccine and drug development experts, and yes, epidemiologist) make decisions solely based on models and not update their hypothesis based on hard data on the ground.

 

Fair point -- if you assume that these scientists were all rational, just like how economists would assume.  ;)

[SnarkyPuppy]

@orthopa

"how can the hospitalization rate/positive rate be so high..."

 

I have heard from several NYC doctors I know that when admits are presumed covid based upon symptoms, and then there is a "confirmatory" test which is negative, hospital just treats it as a false negative and doesnt change record, and proceeds with oxygen, IV and monitoring

 

Accepts anecdotal data in direction that confirms preconceived bias.  Ignores anecdotal data in opposite direction

 

https://www.sfgate.com/bayarea/article/Santa-Clara-county-coronavirus-February-deaths-15217371.php

[Guest cherzeca]

hume interview of Berenson:  https://www.foxnews.com/politics/brit-humes-interview-with-ex-nyt-reporter-alex-berenson-read-the-transcript

[RichardGibbons]

this is BS Hj.  the early data from china was definitive on excessive impact on elderly.  and we knew the genomics of this virus very early on.  we were not operating in the dark, we were just operating stupidly.

 

This is BS, CZ. People have tried closing down nursing homes.  It doesn't work, particularly when the President prevents testing.  Your repeated assertions that it would work are silly.

[RichardGibbons]

The only thing that is delusional is to believe that people who have spent all their lives in this area (doctors in the area of infectious diseases, diagnostic, vaccine and drug development experts, and yes, epidemiologist) make decisions solely based on models and not update their hypothesis based on hard data on the ground.

 

+1.  Note that "making decisions based on the most pertinent observations" basically means "enhancing models based on new information".

[RichardGibbons]

Accepts anecdotal data in direction that confirms preconceived bias.  Ignores anecdotal data in opposite direction

 

I find it remarkable that people have lived through two months of this, but, as new information has come in, have not updated their theories at all.

 

Terrifying.

 

But it does show nicely how someone like Trump can maintain popularity. Basically, a large segment of the population--including some doctors!--doesn't care at all about evidence except insofar as it supports what they want to believe.

[clutch]

FYI, guys, I was talking about the situation in Ontario, Canada... not US or Trump...

 

I guess nobody cares about Canada and I should just leave this thread alone.  ;D

[Guest cherzeca]

this is BS Hj.  the early data from china was definitive on excessive impact on elderly.  and we knew the genomics of this virus very early on.  we were not operating in the dark, we were just operating stupidly.

 

This is BS, CZ. People have tried closing down nursing homes.  It doesn't work, particularly when the President prevents testing.  Your repeated assertions that it would work are silly.

 

More BS from you RG.  No visitors to nursing homes instituted by the industry late march.  should have been late January.

[rb]

It is really amazing to me. When all this anti-intellectualism, anti-expertise started with Trump there were questions posed like if you have the guy who operates on you to be a doctor? That was purely theoretical back then and didn't need to be addressed. Now fast forward to 2020 when you have a situation where it's not theoretical anymore. You actually need the doctors. Turns out that no, they still don't want the doctors.

 

This is how you end up with a situation where they put a dog breeder in charge of the COVID task force. Unbelievable! But it's ok... because he's a small business guy.

 

https://www.reuters.com/article/us-health-coronavirus-usa-hhschief-speci/special-report-hhs-chief-azar-had-aide-former-dog-breeder-steer-pandemic-task-force-idUSKCN2243CE

 

As an aside, what's up with the Republicans putting animal people in charge of disaster? Wasn't the guy who fucked up Katrina a horse guy or something like that?

[Spekulatius]

While we are talking about how this virus is a curveball and we keep learning new things, here is another one -

 

Alarmed as COVID patients' blood thickened, New York doctors try new treatments

https://www.reuters.com/article/us-health-coronavirus-usa-blood/alarmed-as-covid-patients-blood-thickened-new-york-doctors-try-new-treatments-idUSKCN22421Z

 

In many subjects showing up in hospitals, no typical symptoms of covid-19 but stroke or kidney complications.

 

"At Mount Sinai, nephrologists noticed kidney dialysis catheters getting plugged with clots. Pulmonologists monitoring COVID-19 patients on mechanical ventilators could see portions of lungs were oddly bloodless. Neurosurgeons confronted a surge in their usual caseload of strokes due to blood clots, the age of victims skewing younger, with at least half testing positive for the virus."

 

“I’ve never seen any other viruses causing that,” Jabbour said.

 

Yes, that’s a real problem . My wife runs the dialysis machines in ICU‘s and they’re super busy , because many patient need dialysis (often the result of organ failures from oxygen deficiencies most likely) and the machines clogging up from blood clots. Nobody expected anyone this going into this. Now we are short dialysis equipment, staff to operate them and consumables. Doctors trying treat this with blood thinners and clot busters.

 

On a related note, an investigation offend in Switzerland and Germany found blood knots  in lung and heart of the deceased, likely contributing or even causing the death. This may have implications for treating severe cases going forward.

[RichardGibbons]

More BS from you RG.  No visitors to nursing homes instituted by the industry late march.  should have been late January.

 

Agreed it should've been January. It doesn't matter though--you can't stop COVID-19 from getting into care homes if a large segment of the population is infected. Your "best practices" would roughly be the same outcome as a bunch of COVID-19 patients running around care homes, coughing on people.

 

(Yeah, I know you don't care....)

[pocoapoco]

Let me repost my 5 things that people don't understand.

[*]Exponential growth

[*]It takes weeks between infection and hospitalization and death

[*]Hospitals are not infinitely expandable--if enough people come in, hospitals run out of resources

[*]If you're in the ICU with this, you are likely in there for weeks

[*]That without ventilators, the death rate increases dramatically

 

Maybe #5 not true

 

 

Some 88% of Covid-19 patients in the New York City area who had to be placed on ventilators subsequently died.

https://www.bloomberg.com/news/articles/2020-04-22/almost-9-in-10-covid-19-patients-on-ventilators-died-in-study?cmpid=BBD042220_BIZ&utm_medium=email&utm_source=newsletter&utm_term=200422&utm_campaign=bloombergdaily