CDC Director Rochelle Walensky recently hinted at a press conference that she is going to do more media appearances. She got that opportunity on Sunday, when she walked into the fire on Fox News.
Bret Baier finally asked her about one of the biggest mysteries of the Covid pandemic. It only took two years, but the CDC Director was finally confronted about the shady Covid-related deaths reporting, which has often been used to justify draconian and often unlawful policies.
“Do you know, how many of the 836,000 deaths in the U.S. linked to COVID are from COVID or how many are with COVID, but they had other comorbidities. Do you have that breakdown?” Baier asked.
“Um, yes, of course, with Omicron we’re following that very carefully,” she said. “Our death registry, of course, takes a few weeks… to collect. And of course, Omicron has just been with us for a few weeks, but those data will be forthcoming.”
As was recently reported on Becker News, the CDC’s accounting of “Covid-related deaths” has raised serious issues. The “generally mild” Omicron variant’s rapid and pervasive spread has exposed this problem in a much starker way than in the past.
The dam burst when several public health officials, such as Dr. Anthony Fauci, finally made the distinction between child hospitalizations with Covid and hospitalizations for Covid. This “incidental” Covid hospitalization provided further evidence that the data being reported to the public about the pandemic was intentionally confusing, and the conflation of variables was designed to foster hysteria in the public.
Dr. David Samadi commented on the development:
The CDC will begin to provide data on how many of the 836,000 deaths in the U.S. linked to Covid are FROM Covid and how many are WITH Covid.
I’ve been encouraging this from day one as it would have changed the entire perspective on the response.
Glad it’s finally happening.
— Dr. David Samadi (@drdavidsamadi) January 9, 2022
“The CDC will begin to provide data on how many of the 836,000 deaths in the U.S. linked to Covid are FROM Covid and how many are WITH Covid,” he said. “I’ve been encouraging this from day one as it would have changed the entire perspective on the response. Glad it’s finally happening.”
However, it remains to be seen if the data will be at all reliable. One of the primary principles in statistical reporting is that variables be mutually exclusive — at least to the greatest extent possible in the social sciences. However, Covid deaths reporting has been marred from the very beginning by the presence of comorbidities — many of the patients with multiple comorbidities — among 95% of those who died.
Distinguishing between those who died with Covid and from Covid is not an enviable task and is undoubtedly complex. It takes a seasoned medical examiner to be able to formulate the best assessment about what probably happened to the deceased patient. When faced with hundreds of thousands of excess deaths in the midst of a pandemic, it may be tempting to simply chalk up nearly all of the all-cause excess deaths as “Covid-related.”
In the U.S., nearly all of all-cause excess mortality has been attributed one way or another to Covid. Here is a chart from the CDC showing all-cause excess deaths.
Now, below is a chart of Covid-related excess mortality.
These charts look pretty much identical. That’s because the CDC admits they calculate their Covid-19 deaths based on a model derived from the unexplained all-cause mortality rates.
“COVID-19 deaths are estimated using a statistical model to calculate the number of COVID-19 deaths that were unrecognized and those that were not recorded on death certificates and, as a result, were never reported as a death related to COVID-19,” the CDC says.
“To estimate these unrecognized COVID-19 deaths, all-cause deaths are obtained from the National Center of Health Statistics,” the CDC continues. “Before applying the statistical model, reported COVID-19 deaths are subtracted by age, state, and week from all-cause deaths, so that these reported COVID-19 deaths are not included in the calculation of the expected deaths for the statistical model.”
“Then, to understand how many deaths may have not been recognized as being related to COVID-19, CDC uses a statistical model to estimate the number of expected deaths from all causes assuming that there was no circulation of COVID-19 (that is, those deaths expected in the absence of any COVID-19 illnesses). Researchers then use the model to predict the number of all-cause deaths that would have occurred taking into account information on COVID-19 circulation,.[sic].”
“To obtain the number of unrecognized COVID-19 deaths, the number of expected all-cause deaths (without COVID-19 circulation) are subtracted from the number of predicted all-cause deaths (with COVID-19 circulation). The model is used to calculate estimates by state and age (for six age groups: 0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years),” the CDC adds.
“Once investigators estimate unrecognized COVID-19 deaths, they add documented COVID-19 deaths to the unrecognized deaths to obtain an estimate of the total number of COVID-19-attributable deaths,” the CDC says.
The CDC might be burying the potential harm of Covid-response policies under this rubric, which puts undetermined all-cause excess mortality in the category of Covid-related excess mortality. This makes it difficult for actual policymakers to discern if the Covid response policies are helping or harming society overall.
The CDC explains why it has been using such a methodology, which it feels compelled to point out has been “peer reviewed” by The Lancet.
“Because current surveillance systems do not capture all cases or deaths of COVID-19 occurring in the United States, CDC provides these estimates to better reflect the larger burden of COVID-19. CDC uses these types of estimates to inform policy decisions and public messages.”
So, “health policy” and “messaging” have been guides for the CDC’s statistical analysis. Needless to say, this is not really the CDC’s job. It should be reporting clear and accurate data reports so actual policymakers can interpret them and put into place policies that make the requisite overall trade-offs leading to the overall best public good.
It has always drawn suspicion about the reporting that there is a tremendous amount of overlap between Covid-related deaths and serious underlying health conditions. Indeed, 95% of all Covid-related deaths have at least one ‘comorbidity,’ and the average number of Covid-related comorbidities is 4.0.
Serious underlying health conditions thereby exponentially increase one’s risk of dying from Covid-19. This is something the CDC Director recently said publicly. Furthermore, it was determined in 2020 that the average age of mortality for Covid-19 related deaths (77 years old) was about that of life expectancy (78 years old). That raises red flags about how these deaths are getting coded.
There may have been a time when in the interest of showing an abundance of caution and out of concern for the safety of medical practitioners, as well as acknowledging the strain on the health system that would result from being thorough, that the CDC’s reporting was understandable, albeit not entirely defensible from a scientific standpoint.
Two years into the pandemic, however, there will undoubtedly be tens of thousands of people dying with a “generally mild” virus like the Omicron variant. It is no longer acceptable to report Covid-related mortality in such a manner.
Finally, we got to see the CDC Director pressed on such a vital issue. Her response, contrary to the misleading assessments of “fact checkers,” acknowledges the issue, thereby proving that this was a valid line of questioning all along.
This is what journalism looks like: Holding elected officials and policy makers accountable. It isn’t uncritically repeating the CDC’s guidance without stopping to question the reasoning or the motives behind it.
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