First, JHU published the following article in the News-Letter…
Then, after the outcry began… They retracted it. This is the opening paragraph of the retraction…
Editor’s Note: After The News-Letter published this article on Nov. 22, it was brought to our attention that our coverage of Genevieve Briand’s presentation “COVID-19 Deaths: A Look at U.S. Data” has been used to support dangerous inaccuracies that minimize the impact of the pandemic.
Full article, HERE.
A friend put it best- The real issue here is that science is messy and epidemiology especially so. Somewhere in the last several weeks, I read an article regarding CDC
reporting of statistics. It made a statement to the effect that CDC reported data in a way meaningful to epidemiologists but misleading to everybody else. I have long since come to the belief that a true measure of competency in a scientist is the ability to make something complex simple to the layman. In failing to provide data useful to epidemiologists as well as meaningful to the layman, the CDC has failed.
So effectively, they pulled the article because the READERS were actually asking questions… Sigh…
EDIT- h/t McChuck, a good discussion on the original article, with more readable graphs by William Briggs, HERE.
I guess this is going to be the next thing if Slo Joe has his way…
The security certificate for the website comes up expired, but the ‘explanation’ can also be seen at https://archive.is/dJrXX and I gotta say… boy howdy did they throw the author under the bus.
I particularly liked:
‘Briand was quoted in the article as saying, “All of this points to no evidence that COVID-19 created any excess deaths. Total death numbers are not above normal death numbers.” This claim is incorrect and does not take into account the spike in raw death count from all causes compared to previous years. According to the CDC, there have been almost 300,000 excess deaths due to COVID-19. Additionally, Briand presented data of total U.S. deaths in comparison to COVID-19-related deaths as a proportion percentage, which trivializes the repercussions of the pandemic. This evidence does not disprove the severity of COVID-19; an increase in excess deaths is not represented in these proportionalities because they are offered as percentages, not raw numbers.’
Hell, I’m not even certain what they’re trying to say here.
Briggs has a good take on this.
https://wmbriggs.com/post/33680/
Briggs is the MAN. Also a witness for Sydney Powell.
He’s been on my radio show a couple times about Covid and The Great Reset.
Just another example of academia bowing to the over-reaching power of the narrative. If it is good science, but counters the narrative, it must be suppressed.
it must be suppressed… or you,lose your funding.
Hey Old NFO;
I consider this “Covid crap” kabucki theater, sure people have died and some precautions should be taken, but the overreactions that they have done is astounding, when the pandemic was here in 2009 during the Lightbringers reign, the media and academia played it down as to not hurt him, whereas with trump, they ratcheted up the pain….lying double standard bastards, I don’t trust anything they say.
Somewhere, some really evil people are laughing at the foolishness. May they burn in Hell.
Science is hard. Oftentimes Science rises up against the scientists and slaps them silly with this thing called ‘facts’ and especially ‘reproduceable results.’
Do you remember a bunch of right-wing nutjobs all saying that, come the election, the truth about the Covidiocracy, the Wu Ping Cough, the Chinky Pox would come out?
This is actually nothing new. This is that mean old ‘reproduceable results’ that we’ve been seeing from other scientific studies since the Pox came among us, sometime like 10 seconds after Impeachment! failed.
Not denying the disease, just denying (with scientific proof) the deadliness of it and the need to lock us all down and violate our civil rights so that THEY could try to cheat themselves to victory.
First rule of Science – Be Skeptical! Verify, Verify and Verify before trusting.
And if Biden had actually won the election the study would still be up to justify completely unlocking the country now that Orange Man Bad would be leaving office in January.
Lying liars gotta lie.
All- Thanks for the comments, McC, added the Briggs post to the main post, thank you!
Posted from my iPhone.
Lying is very lucrative to science…
More fundamental question.
Why the hell are we letting medical doctors practice epidemiology?
The doctors have earned their credibility with one one one patient diagnosis and treatment. Their training is memorization heavy, and includes many, many details for identifying the underlying health issues of a single patient.
Epidemiology, as Fauci practices, seems to be a matter of using population based metrics to diagnose underlying health issues of a population, to be remedied by policy.
Data about an individual and data about a collection is essentially different. Statistics exists as a field because tools valid for one are not necessarily valid for the other.
We can validate the tools of the doctor on individual patients by looking at deaths.
This public health policy stuff is much less falsifiable, because it is implemented on a polity wide basis, and it is not clear that data is really comparable between polities.
Teaching medical doctors statistics only works if those medical doctors have the right type of intelligence to use statistics to extend their training to an entirely different domain of problem.
If the AMA’s oversight of medical doctor training excludes people with that type of intelligence and curiosity, then doctors should not automatically be trusted in public health policy.
I heard a guy who looked at the state of epidemic modeling, and concluded that different training was in order, say “they will be made to understand what a Kalman filter is”. I figure that means he was a senior electrical engineer of some sort. Maybe that is personal preference talking, and isn’t the answer either.
Whatever the training, if an occupation attracts mainly not very bright wannabe technocrats, they are going to use their tools to conclude that technocracy is the best.
It’s not doctors – it’s bureaucrats. Remember, the guy who finishes in the bottom quartile of the class has to go to work for the government. No one else will hire him (her) He works for 30 yrs. at his job – which is to avoid pandemics. He fails. His name is Fauci.
Most doctors and essentially all bureaucrats are innumerate. Almost all medical researchers and epidemiologists have been taught statistical methods that are wrong, so they are worse than useless.
Briggs has been going on about this for quite a few years. Check him out. Buy his book on how government policy turned a routine pandemic into a global disaster.
We will see another big push for “net neutrality” if Joe and Ho actually make it into office. Can’t have all us bitter clingers disputing the “narrative”.
Bob- Excellent points.
Was there ever such a monumental scam? I was going to add: “Of EPIC, BRAZEN, lying, corrupt, sly, duplicitous, mendacious, scheming, malfeasant proportions” but thought better of it.
Trying to clean up my prose, with a view to “less is more.”
The degrees were revoked later, after the war, but Mengele was a PhD and an MD.
Voluntarily or because they were coerced, American MDs agreed to follow certain requirements in terms of informed consent.
We can assess those easily for one on one treatment.
Where is the consent in this combination of modelers and policy bureaucrats?
In theory, it could come from oversight of a representative government. a) such a government would need to be able to administer oversight b) If the bureaucrats are partisan, and clearly have their thumb on the scales for partisan ends…
Framed that way, I’ve been taking the problem a little lightly.
The main problem is not physicians in epidemiology. The problem is that Schools of Public Health are, as with many many other academic institutions, controlled by leftists. The linked article was from Johns Hopkins University. JHU has a named (for a donor, obviously) SPH. It is the “Bloomberg School of Public Health”. I trust there are no questions. Harvard’s TH Chan is also “fully converged”.
Many MDs are indeed innumerate, but not all of us are. For example, I have a Masters in engineering from MIT. I have also done a multi-year fellowship in cardiovascular epidemiology (after my standard 3-year clinical cardiology fellowship). There are quite a few of us who have quantitative training. (Though I agree completely that the med school curriculum is very memorization-based; FWIW I hated it.)
The problem with having Public Health and Epidemiology in the hands of non-MDs is that, exceptional ones aside, to most statistical types (that I have worked with, and these are ones at leading academic institutions) numbers are just numbers; they have no physical meaning or interpretation to most of these people. (I have had the privilege of working some VERY FEW leading medical statisticians who have excellent understanding of the topics they are working on, but these men are literally one in a hundred, or fewer). Many of the the “stats/epi” people you find attached to various research programs are girls with a Masters in biostatistics, and zero clinical experience. You need to have people trained in medicine in the loop, at a high-input level, when it comes to serious public health issues.
As to the AMA, it is a leftist, gun-grabbing organization. I am vehemently opposed to the AMA and refuse to join despite the weekly mailers from those [bad people]. The medical school admission process is a nasty one, and the training culture encourages and rewards group think, ass-kissing, and sucking up to petty tyrants. Despite that, some good people do get in and through, but I have always been amused by TV shows where the doctor yells about how the patient is his first and only priority. The training process is seemingly designed to achieve the exact opposite. But that’s a different rant.
TL;DR. Public Health and Epidemiology needs persons with quantitative biostatistical* skill sets, but also persons with extensive clinical medical experience at the decision-making levels. Neither group alone is adequate.
(*I note that biostats != [does not equal] the sort of statistics one may have taken in engineering or physics programs. I know for damned sure that my engineering stats were not useful for the epi work I did; I had to learn an entirely new set of skills.)