COVID COVID-19 Coronavirus Containment Efforts

[morrobay]

From the article, it says the CDC initially estimated 11 hospitalizations would be needed per death, then later dropped it to 7, then later to 4. This is almost certainly the same as the CFR issue; the disease is less severe than initially thought because the testing shortage meant we were missing most of the people infected.

And the CDC initially estimated the fatality rate for hospital cases was 9% then 14 % then 25%. So there are two tracks here. The hospitalizations / fatality has dropped with a corresponding increase in fatality rate/hospitalizations. And mutually inclusive the disease is less severe because the testing shortage was missing large numbers of mild/asymptomatic people.

 

[russ_watters]

@Russ: No one questions that many cases were missed in March and April. That's not what the discussion was about. Cases that go to a hospital are severe cases, they are not missed. If these people die more often than estimated before, how is that change in particular making the disease less dangerous? You cited that change as evidence that the danger was overestimated.

Ok, yeah, I see how the data/model can be interpreted from either direction if we don't have the context/method. FYI, I didn't make this interpretation up myself, I read it in the news/commentary article. But now I checked the original source to make sure that the direction the article specified is correct, and yes, it is correct: fewer hospitalizations per death means fewer hospitalizations, not more deaths. Deaths is the anchor, hospitalizations the variable, so when the fraction decreases its because hospitalizations decreased, not because deaths increased:

[page 5]
Why did these changes occur?

These changes in predicted hospital resource use and related gaps in states where demand might exceed supply are fairly large. In this section, we explore the changes in our analytical framework that resulted in these revised estimates of overall lower hospital resource use due to COVID-19.

...our overall ratio was 11.1 hospital admissions per COVID-19 death.

...Our estimates released today... 7.1 hospitalizations per death (95% CI 4.0 to 12.7). These lower ratios of admissions to deaths result in predicted peak hospital resource use – total beds, ICU beds, and invasive ventilators – that is lower than previously estimated.
[emphasis added]

http://www.healthdata.org/sites/default/files/files/Projects/COVID/Estimation_update_040520_3.pdf

If you argue people got less likely to be admitted to a hospital than before - while the disease stays unchanged - that would mean hospitals had to turn down increasingly severe cases. That would mean they are overwhelmed. I don't say that's true, but that's one of the few ways to interpret these numbers without saying it kills more people than expected before.
[emphasis added]

Since you already know it that it is in fact false, I don't understand why you are even offering it as a possibility. Please stop trying to use this inaccurate claim as a basis for your interpretation of the data, and instead follow the data where it actually leads. Again, I really don't understand why this should be controversial.

The options I see are:
1. The disease is more severe than previously thought, so the "cone" of infected, hospitalized, dead is steeper.
2. The disease is less severe than previously thought, so fewer people need to be hospitalized based on adjusted criteria on if/when to admit them.
3. The disease itself has changed.
4. Demographics issues (old vs young people) caused the change.

#1 was covered in the first section; not the case.
#2 seems plausible due to the early chaos and learning curve.
#3 is possible but harder to be sure of.
#4 seems plausible due to the known demographics shift in the infected.

 

[atyy]

http://www.healthdata.org/sites/default/files/files/Projects/COVID/Estimation_update_040520_3.pdf

For New York, by deaths per day (p10), the CDCs later estimates (April 2 & 5) seem to have been more severe than initially estimated (March 26).

 

[russ_watters]

For New York, by deaths per day (p10), the CDCs later estimates (April 2 & 5) seem to have been more severe than initially estimated (March 26).

Yes.

 

[atyy]

Yes.

Also, I guess these are IHME's estimates, not the CDC's?

 

[russ_watters]

Also, I guess these are IHME's estimates, not the CDC's?

Yes, apologies, you are correct: the first number (11.1) was direct from CDC data whereas the second (7.1) is from the expanded study/data set from IHME. The news article lists a third ("about 4") that is also presumably from IHME, but it doesn't have a link to it. It also mentions a Harvard model that also estimated too high.

 

[atyy]

Yes, apologies, you are correct: the first number (11.1) was direct from CDC data whereas the second (7.1) is from the expanded study/data set from IHME. The news article lists a third ("about 4") that is also presumably from IHME, but it doesn't have a link to it. It also mentions a Harvard model that also estimated too high.

I guess the uncertainties are tricky to estimate. In the deaths per day estimates of the IHME's report, the uncertainties go to zero as the predicted deaths goes to zero in around June, whereas one might think that since those points are furthest from the then existing data, the uncertainties should be larger later in time. On the other hand, if the main model was China, COVID-19 deaths there do seem to have gone to zero for the moment.

 

[Vanadium 50]

0.10% of the population died in Manaus. Some parts of NYC had more deaths. It's possible that the official number underestimates the total deaths of course.

Ever been to Manaus? It is incredibly isolated. Everything goes in and out by air - there is a little river traffic (but it's over a thousand miles from the ocean) and one road north and one road south, neither of which is passable in the rainy season. It's like an island, surrounded by vegetation and not ocean.

 

[mfb]

Since you already know it that it is in fact false, I don't understand why you are even offering it as a possibility. Please stop trying to use this inaccurate claim as a basis for your interpretation of the data, and instead follow the data where it actually leads. Again, I really don't understand why this should be controversial.

"I don't say that's true" doesn't mean its false. I listed it as one possible interpretation of the data.

#1 was covered in the first section; not the case.

I don't see how you can rule this out, because hospitalized -> death did get steeper based on CDC/IHME estimates. Your own source demonstrates that #1 is the case for at least half of that chain.

I don't see how deaths could be any reasonable anchor. Infections would be the best, in the absence of reliable infection numbers we can use hospitalizations (limiting the analysis to cases that are not mild). But starting from deaths is weird. Going by that definition a disease that puts 1% into a hospital but only kills 0.001% must be the worst disease ever? 1000 hospitalizations per death! In addition hospitalizations per death go up if treatment in a hospital gets better (i.e. the hospital gets better in preventing deaths) - which certainly means the disease gets less dangerous, not more dangerous.

Ever been to Manaus?

No, but I'm not sure what the conclusion of your post is.

 

[Vanadium 50]

No conclusion at all, other than Manaus was an outlier long before Covid. There is no place quite like it anywhere.

 

[Astronuc]

NY Times is attempting to track COVID-19 cases at US universities and colleges.
https://www.nytimes.com/interactive/2020/us/covid-college-cases-tracker.html

A New York Times survey of more than 1,600 American colleges and universities — including every four-year public institution and every private college that competes in N.C.A.A. sports — has revealed at least 130,000 cases and at least 70 deaths since the pandemic began.

In a related articles, the NY Times reports on a seemingly very healthy, i.e., athletic and no apparent pre-existing condition (co-morbidity), 19-year-old "College Student Dies of Rare Covid-19 Complications"
https://www.nytimes.com/2020/09/29/us/college-student-dies-covid.html

He tested positive for the Coronavirus on Sept. 7 and quarantined for 10 days before returning to Boone, according to his uncle. Then he got worse, after he seemingly recovered well enough to return to his apartment near school. He was removed from life support by his parents on Sept 28. According to his uncle, "it was not clear how his nephew had contracted the virus. “He told us he was always careful to wear a mask.” " A family friend who taught Chad Dorrill in high school, said doctors told the family that they suspected he had a previously undetected case of Guillain-Barré syndrome, a rare neurological disorder in which the body’s immune system attacks nerves. So, it seems possible that he did have an undiagnosed condition.

 

[russ_watters]

"I don't say that's true" doesn't mean its false. I listed it as one possible interpretation of the data.

I don't see how you can rule this out, because hospitalized -> death did get steeper based on CDC/IHME estimates. Your own source demonstrates that #1 is the case for at least half of that chain.

*I* am saying it's false and I'm saying that you should understand/accept by now that it is false because we just discussed it in some detail. It's fine to follow a chain of logic to find "possible" interpretations, but then you have to start analyzing them and checking against other facts to verify if they are in fact true, false or actually unknown/possible. This one has been determined to be false, so it should be taken off the list, not continued to be listed as "possible".

I don't see how deaths could be any reasonable anchor. Infections would be the best, [snip] But starting from deaths is weird.

I agree that starting from deaths does feel weird, but as you pointed out previously, deaths are a solidly known number. So that make them a good, perhaps the best anchor. It's best to rely on the facts we have for an anchor, agreed? That's why, somewhat separately, we are starting from death #s and projecting infected #s. The death numbers are known to be more reliable.

in the absence of reliable infection numbers we can use hospitalizations (limiting the analysis to cases that are not mild).

Hospitalizations are the output of the model, so they can't be an input.

I feel like you may have lost track of what we were discussing. I entered the latest chain on Sunday to contradict the common claim that hospitals were overwhelmed (potentially driving a higher death rate). I presented data that shows they weren't, models that shows they were predicted to be, and data that explains the disconnect. You're still saying it is "possible" that's all backwards. It's not.

Going by that definition a disease that puts 1% into a hospital but only kills 0.001% must be the worst disease ever? 1000 hospitalizations per death! In addition hospitalizations per death go up if treatment in a hospital gets better (i.e. the hospital gets better in preventing deaths) - which certainly means the disease gets less dangerous, not more dangerous.

A disease that puts 1% into the hospital and kills 0.001% is worse than a disease that puts 0.1% into the hospital and kills 0.001%. Same number dead, more hospitalized is "worse". Or even worse, if having 1% in the hospital increases the death rate to 0.002% due to hospitals being "overwhelmed". That's the claim/prediction, I entered to counter. Here it is again:

Overall an IFR of 1% may be a bit high, but given that the NYC health system was overwhelmed in the early stages, it seems plausible that IFR in the early stages of the NYC outbreak was higher

We should all agree/accept by now that the "given" premise is false, not "possible" and therefore it could not have driven the conclusion to be true.
[edit] ...which doesn't mean the conclusion about the IFR couldn't be true for other reasons. It may well be true due to demographics (old people were practically targeted for infection).

 

[mfb]

I agree that starting from deaths does feel weird, but as you pointed out previously, deaths are a solidly known number.

Hospitalizations are known as well. Maybe even better, because they don't include deaths for unknown reasons outside hospitals. Being solidly known alone doesn't make something a good anchor.

Hospitalizations are the output of the model, so they can't be an input.

Past hospitalizations and deaths are known and can be inputs (if it's an output, then you better check it's correct), future hospitalizations and deaths (the reason you make a model) can be an output but not an input.

I feel like you may have lost track of what we were discussing.

I was commenting on a very specific claim - that more deaths per hospitalization would mean the disease is less severe. I said this is not the case. I made a small side remark how you could get more deaths per hospitalization without a more severe disease (overcrowded hospitals), and I said this was largely a theoretical option without much relevance. I think you missed that part, because you keep going back to that side remark as if it would have been something important. It wasn't. Forget it.
If more people who go to a hospital die that's bad.

A disease that puts 1% into the hospital and kills 0.001% is worse than a disease that puts 0.1% into the hospital and kills 0.001%. Same number dead, more hospitalized is "worse".

But how realistic is this comparison? hospital->death ratio depends on how severe the disease is in cases that we can count easily. Why would cases that we can't study easily behave in exactly the opposite way? A disease that puts more people into a hospital than a comparable disease will almost certainly kill more people, too.----

The sum of official death tolls exceeded 1 million two days ago.

 

[atyy]

We should all agree/accept by now that the "given" premise is false, not "possible" and therefore it could not have driven the conclusion to be true.
[edit] ...which doesn't mean the conclusion about the IFR couldn't be true for other reasons. It may well be true due to demographics (old people were practically targeted for infection).

I still wouldn't agree that you have ruled it out (although I agree remains conjecture), since we do agree that the health system was stretched. In my ventilator sharing example, your objection to that as a possible contributing factor is that only a small fraction of patients shared ventilators. But you can imagine other possibilities, For example, suppose it takes an hour a day to optimize ventilator settings per patient, but due to the huge caseload, there is only 20 minutes a day for adjusting ventilator settings, that could also lead to worse outcomes.

For example, early reports about death rates for those on ventilators were higher than this later report. The authors discuss "Several local and regional considerations may have influenced the observed outcomes. First, the arrival and peak of the COVID-19 pandemic in Georgia were later than in many of the regions from earlier reports. This delay provided time to establish organizational structures, acquire equipment, prepare personnel, create consensus-driven clinical protocols, and align resources across a large healthcare system. In addition, while patient volumes did merit the redesignation of several specialty ICUs as COVID-ICUs, all critically ill patients with COVID-19 were admitted to preexisting ICUs and cared for by critical care teams with experience managing acute respiratory failure and at standard patient-to-provider ratios."
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7255393/
https://news.emory.edu/stories/2020/05/coronavirus_emory_icu_outcomes/index.html

 

[Astronuc]

Meanwhile in NY, the Dept of Health continues to "aggressively track clusters with a particular focus on the 20 ZIP codes with the highest infection rates. Within these 20 "hotspot" ZIP codes, the average infection rate is 5.5 percent. The rate of infection for the rest of New York State, excluding those 20 ZIP codes, is 0.82 percent. While these 20 ZIP codes accounted for almost a quarter of yesterday's positive cases, they represent only 6 percent of the state's population." - from an email alert from the Governor's office.

By zip code: Rockland County (10952, 10977), Brooklyn (11230, 11204, 11219, 11223, 11229, 11210, 11234), the Bronx (10465, 10462), Manhattan (10040), Queens (11374), Staten Island (10306, 10304), Suffolk County (11717, 11746) and Nassau County (11580).

https://www.governor.ny.gov/news/go...h-community-leaders-address-covid-19-clusters

 

[StevieTNZ]

Confirmed Donald Trump has COVID-19.

https://www.stuff.co.nz/world/ameri...ne-process-and-tests-positive-for-coronavirus

 

[mfb]

Please keep our rules about political discussions in mind. Posting the news is fine - and it's certainly a high profile news.

Here is CNN's article - I guess every larger news outlet has an article or will have it soon.

 

[Astronuc]

I read an article that mentioned the surveillance testing at the White House uses the Abbott rapid test.

Apparently Trump advisor, Hope Hicks, began showing symptoms Wednesday evening and subsequently tested positive for COVID-19. Donald and Melania Trump were tested Thursday, and he may be experiencing mild symptoms at present.

 

[Vanadium 50]

Abbott rapid test

Which is important, as that test determines whether or not the subject has the virus right now, as opposed to an antibody test which determines if the subject ever had it.

 

[StevieTNZ]

https://www.newshub.co.nz/home/worl...ised-after-being-diagnosed-with-covid-19.html

US President Donald Trump is on his way to military hospital Walter Reed Medical Centre, White House Press Secretary reports.
"The President will be working from the presidential offices at Walter Reed for the next few days," White House Press Secretary Kayleigh McEnany said in a statement on Saturday.
Trump has had a fever since Saturday morning, according to CNN.
McEnany said this was "out of an abundance of caution, and at the recommendation of his physician and medical experts."

 

[mfb]

Trump has had a fever since Saturday morning, according to CNN.

I assume this is Saturday morning New Zealand time, i.e. now, not nearly a week ago.

 

[StevieTNZ]

I assume this is Saturday morning New Zealand time, i.e. now, not nearly a week ago.

I would think so.

 

[Astronuc]

Trump has had a fever since Saturday morning, according to CNN.

I read a short message attributed to the NY Times that Trump had a fever, congestion and cough, as of some time today (Friday in US). Hope Hicks was 'not feeling well' 48 hours ago, so she was already infectious.

 

[StevieTNZ]

Ardern had asked for New Zealand's representatives in the United States to pass on the message wishing the president a "speedy recovery".

She had previously personally messaged UK Prime Minister Boris Johnson when he contracted Covid-19 earlier in the year, but that was because she had his phone number. As you could expect, Ardern said, it would not be common for people to have the personal number of the US President -- and she didn't.

"We've used our official channels to pass on that message."

and

Asked about the possible implications for New Zealand, such a disruption to the US presidency could have, Ardern said it was "too early to say".

"We still haven't even seen out of the administration the likely effect they believe it will have on the election campaign. Of course, we haven't seen an election date moved before [in the US] and it's quite a process for that to happen.

"So at this stage, I'd say it would all be highly speculative we just haven't heard anything official from the White House in that regard."

-- https://www.stuff.co.nz/national/po...ent-donald-trump-first-lady-a-speedy-recovery

 

[Astronuc]

According to CNN,

Shortly before midnight, the President's physician, Navy Cmdr. Dr. Sean Conley finally gave an update on the President's condition, saying in a memo that the President is "doing very well" and has not required any supplemental oxygen, but that doctors have initiated the antiviral drug remdesivir, which has been shown to shorten recovery time for some Coronavirus patients.

https://www.cnn.com/2020/10/03/politics/donald-trump-coronavirus-walter-reed/index.html

Melania Trump remained at the White House with what the White House physician described as a mild cough and a headache.

Meanwhile, Former White House counselor Kellyanne Conway said Friday night that she has tested positive for coronavirus, and Trump's campaign manager Bill Stepien has tested positive for coronavirus, who expressed 'mild flu-like symptoms.' Three journalists who work at the White House tested positive on Friday, according to a series of memos from the White House Correspondents Association.

Update: Three US Senators, Mike Lee (R - Utah), Thom Tillis (R - North Carolina) and now Ron Johnson (R-Wisconsin). Johnson had quarantined for two weeks after exposure to someone who tested positive, he was again exposed to Coronavirus after his quarantine ended and he returned to Washington!

Cleveland (Politico) - Eleven new cases of Covid-19 were reported in Cleveland stemming from the presidential debate held in the city this week, the city government disclosed Friday.

 

[Dale]

Frequent testing is clearly not a viable substitute for social distancing and PPE usage

 

[BillTre]

Its my understanding from news reports that even though they had the resources for frequent testing, they failed to make use of those opportunities.
In addition to their other failings with with distancing and PPE.

Not taking it seriously.
Discouraging others in their circle from taking precautions.

 

[Ygggdrasil]

According to CNN,

Shortly before midnight, the President's physician, Navy Cmdr. Dr. Sean Conley finally gave an update on the President's condition, saying in a memo that the President is "doing very well" and has not required any supplemental oxygen, but that doctors have initiated the antiviral drug remdesivir, which has been shown to shorten recovery time for some Coronavirus patients.

https://www.cnn.com/2020/10/03/politics/donald-trump-coronavirus-walter-reed/index.html

Many news outlets are also reporting that the President has been given an experimental monoclonal antibody cocktail currently in testing as a potential COVID-19 therapy:

Trump received a single 8 gram dose of Regeneron's dual antibody cocktail Friday and completed the infusion without incident, the President's physician, Dr. Sean Conley, said in a statement.

"In addition to the polyclonal antibodies, the President has been taking zinc, vitamin D, famotidine, melatonin and a daily aspirin," Conley said.

https://www.cnn.com/2020/10/02/health/trump-regeneron-antibody-treatment/index.html

Frequent testing is clearly not a viable substitute for social distancing and PPE usage

This is also apparent from outbreaks that have occurred the among the Tennessee Titans NFL team (which has forced the league to postpone the team's game this weekend). The team has seen a Coronavirus outbreak spread to six players and seven team personnel despite testing all players and personnel six days a week.

 

[Astronuc]

Many news outlets are also reporting that the President has been given an experimental monoclonal antibody cocktail currently in testing as a potential COVID-19 therapy:

Yes, apparently it's two monoclonal antibody compounds, which were administered at the White House. Remdesivir was started at the hospital as a prophylactic, and treatment will continue over 5 days. The president seems to have responded as he apparently has no fever and is without need of supplemental oxygen (his oxygen levels are good).

About Regeneron's treatment
https://www.sciencemag.org/news/2020/09/provocative-results-boost-hopes-antibody-treatment-covid-19
https://science.sciencemag.org/content/369/6506/1014.abstract

 

[Ygggdrasil]

Remdesivir was started at the hospital as a prophylactic

It's not a prophylactic if he is already is infected with the virus.

Experience with other antivirals (such as tamiflu) suggests that these types of treatments are more likely to be effective at preventing severe symptoms if administered early in the course of the disease.