James is lying (again). Oh, to be fair, in the context of this clip, Walensky is referring to a new study of vaccinated individuals. But the lie by James is one of omission, namely that this actually applies to ALL COVID-19 deaths.
Yes, Walensky was referring to a single study about vaccinated deaths. But that study is actually just corroborating what the data shows for all COVID-19 deaths.
Walensky used the term "comorbidities" today. The CDC table shows the same term. Don't like that comparison or my definition? Well this is the CDC definition.
A final thought: even if we accept the paper's use of risk factors as separate from comoboridies, risk factors or underlying medical conditions are a subset of comobordities as are organ failures leading to death.
The CDC definition of comorbidities is presence of 2+ diseases
In this case, an organ failure constitutes a disease. While the assumption is COVID-19 is the cause of organ failures, often these happen because of conditions that may not have been known prior to COVID (like undiagnosed heart and other organ conditions).
But one thing is true, while the CDC paper is portraying risk factors as a subset of comorbidities (Walesnky used the latter term because risk factors are also comorbidities), one "risk factor" used in the paper is age, which is not a comorbidity.
The paper adds all people who died had at least one risk factor and four or more. But nearly 80% of all COVID-19 deaths are over 65+, which the paper is using as a risk factor. If 65+ were a comobordity used by the CDC, nearly 80% of deaths would have one immediately.
So bringing this back: even if you accept the paper as comparing a subset of risk factors that might exclude some organ failures, the concept of having multiple underlying medical conditions and risk factors is very much consistent with all COVID-19 deaths.
What Walensky said: 'these people were not well,' is not unique to the deaths occurring in vaccinated people. This is true for a great deal of COVID-19 deaths. We absolutely have known that most deaths occur with multiple underlying conditions or "comorbidities." That's a fact.
So as I said last night, Walensky was specifically referring to a paper assessing "risk factors." But risk factors are also comorbidities and that's why she labeled them as such. What she was saying is generically true for all deaths despite the singling out of one specific paper
All I'm saying, ultimately, is that if you want to provide context that she was citing a specific paper for deaths in vaccinated patients, that's fine. It's accurate. But to act like this isn't true in general is the height of dishonesty. The general pattern can be applied to all
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California reported 308,820 cases today for 3 days of data, bringing the 7-day average to 101,129.
The 7d average for NY is 72,900.
The 7d ave for FL actually DROPPED today from 64,507 to 63,965. This is the first drop in 7d average for Florida in 35 days.
I posted this about growth rate in Florida down to 3.4% just a few days ago. Doesn't mean we have peaked yet, this could be a one day aberration, but...
7d new hospital admissions in Florida grew by only eight (8) people today, suggesting that indeed the peak is very near. Perhaps a mere couple of days.
The clip that went viral today by @CDCDirector was specifically referring to a new MMWR report showing 78% of vaccinated deaths with COVID-19 had at least four risk factors. Walensky referred to them by their analogous term "comorbidities."
This study from Mortality and Morbidity Weekly Report, calls them by risk factors. But all risk factors are also labeled as comorbidities when they are believed to have contributed to death.
Comorbidities can mean existing conditions and specific causes
So a comorbidity can be an existing risk factor (like heart disease) or a condition brought on by disease (like pneumonia). When Walensky says 4+ comorbidities, she was referring to a combination of the two.
But this is not unique to vaccinated individuals.
3/
My real issue with this aside from Pfizer and Moderna not being honest with their obvious motives is that we are purposely misleading people as to what isn’t working. Absolutely none of these studies show a decline in protection against severe illness. It’s all about antibodies.
Vaccines are supposed to trigger an immune response to the virus by preparing the immune system as if it were the actual virus. Antibodies wane, just like after an infection, but the long lasting T cells remember the virus to help protect people against severe illness…
It's really sad how misinformed the justices of the highest court in the land are on this disease. It shouldn't matter, as it should be about the law, but since they're making it about the disease itself, it would help if they weren't citing utterly false statistics.
"Those numbers show that Omicron causes as much severe disease and death in the unvaccinated as Delta did."
Ladies and gentlemen, I give you an actual quote just now from a SCOTUS justice.
This is how grossly ignorant they are. There is no data in the world that shows this.
Among the gems so far:
* There are unprecedented levels of people in hospitals (false)
"We do not contest COVID is a grave danger," heard by the counsel in the OSHA hearing.
They should be contesting that. It's certainly a grave danger to some people, but 80% of deaths occur at retirement age. OSHA mandate addresses working age persons under 65.
This is not going well at all. The justices are just up here citing untrue statistics based on faulty perception. They need to be also arguing the grave danger aspect as well as the law.
Justice Breyer out here saying hospitals are the fullest they've ever been. That is utterly false.
Early anecdotes coming from doctors in South Africa suggested Omicron was mild, or certainly mild(er).
Data there quickly started supporting those anecdotes, and also in places like UK, Denmark, and more recently, Florida.
But now there is hope for the U.S.
A thread.
We'll call this decoupling rate. It's basically an odds ratio type of calculation using a 30d rate of change of three indicators.
A) New hospital admissions 7d ave compared to cases 7d
B) Hospital census 7d compared to new admissions
C) ICU census 7d to hospitalizations
2/
Using these odds ratio, we can see decoupling in the differences of rates of change. We have been seeing it in Florida. Measuring these three together is analogous to measuring ICU (severe illness) as a rate of cases.
Until now, these have predictably moved similarly.
3/