Mainstream media are continuing their two-year hyper-ventilation about alleged deaths “from” Covid-19 and failing in their fundamental obligation to explain complex issues to the public in an accurate way; the bottomline is that these deaths are reported by CDC as “deaths involving Covid-19,” and no reliable causal linkage is required between the virus and the reported death; if we apply the same causal standard applied by CDC itself in a 2022 study looking at vaccine-associated Covid-19 breakthrough deaths we see that a large number of “deaths involving Covid-19” were far more likely to have been from other causes
[This is an update of my essay from last month making similar comments about the alleged 800,000 deaths “from” Covid-19 headlines that were equally wrong at that time]
The Associated Press headline on Feb. 5, 2022 blared: “Propelled in part by the wildly contagious omicron variant, the U.S. death toll from COVID-19 hit 900,000 on Friday, less than two months after eclipsing 800,000.”
All of the pundits and commentators who just a few years ago decried the era of “truthiness” remain silent about these kinds of stories about the level of deaths “from” Covid— which aren’t even “truthy.”
They’re just blatantly wrong.
This 900,000 figure comes from the US CDC, which collects these statistics for the nation as a whole. CDC’s provisional mortality data shows, in Table 1, as of Feb. 5, 2022, 885,136 “Deaths involving Covid-19.”
I’ve reproduced CDC’s Table 1 below.
What does “deaths involving Covid-19” mean? Well, CDC clearly defines this term in footnote 1 to Table 1, right at the bottom of the image above, as follows: “[1] Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1.”
Note that it says “with” not “from.”
There is no mention in this definition of Covid-19 causing the death reported. And if you dig into the CDC’s death certificate reporting guidelines (as I did in the essay just linked) there is no requirement at all that Covid-19 needs to be causally responsible for the death at hand to be listed on the death certificate. It is enough for Covid-19 to be suspected to have caused or contributed to the death in any manner. And the guidelines strongly support listing Covid-19 on the death certificate if there is any association whatsoever.
In short, the CDC “deaths involving Covid-19” figure is night and day from any claimed causal linkage between Covid-19 and the reported death.
Night and day, oranges and apples, black and white. They are fundamentally two different claims about the harm from the virus.
Based on our analysis (this is an essay written by myself, Dr. Blaine Williams and Dr. Daniel Howard) of the pandemic surveillance chain and the various definitions of “case,” “Covid hospitalization” and “Covid death,” we suggest that all of these public figures should be discounted by about 90% to get a more accurate notion of what is really going on. In other words all public pandemic stats are being exaggerated by about 10-fold.
What is the appropriate level of causal certainty for attributing deaths to Covid-19?
I’ve had extensive dialogue with the CDC’s chief of mortality statistics about these issues. He argues, despite the definition described above for “deaths involving Covid-19,” that indeed CDC’s Covid-19 mortality figures are reasonably correct in terms of deaths being attributed to Covid-19. He points to a study put out by CDC that examined the “plausibility” of US Covid deaths figures. This study, Gundlapalli et al. 2021, which was published by CDC and not peer-reviewed, examined the very low causal bar of plausibility for attributing deaths to the virus rather than other causes. The authors conclude: “These findings support the accuracy of COVID-19 mortality surveillance in the United States using official death certificates.” In other words, their study, looking only at the plausibility of attributing these deaths to Covid-19, supported the accuracy of the CDC figures for “deaths involving Covid-19.”
But is plausibility the appropriate evidentiary standard? Interestingly, we can look to recent studies examining alleged vaccine-induced deaths and see that medical science has many other more stringent evidentiary standards that perhaps should be used with respect to Covid-19 deaths. A number of studies have looked at potential vaccine-associated harms, including fatalities. Let’s look at one study, Schneider et al. 2021, published in the peer-reviewed International Journal of Legal Medicine.
The standards of causality in that paper, including “proven beyond doubt” and “very likely cause of death,” are extremely high evidentiary standards, and if we use these same standards in looking at “Covid deaths” we find strong support for the conclusion that “Covid deaths” have probably been vastly exaggerated. This is the case because CDC has for some time now tracked other causes of death (comorbidities) listed on death certificates and as of early 2022 the average “death involving Covid-19” had 4.0 additional “conditions contributing to death” listed on their death certificates.
This single data point shows that it is likely that many or even most deaths attributed to Covid-19 were due far more to preexisting conditions than from the virus. And it is certainly not “proven beyond doubt” in the vast majority of these alleged Covid-19 deaths that they should be attributed to Covid-19 rather than any of the many preexisting conditions listed.
Recent comments from CDC’s director strongly support these arguments
Indeed, CDC director Rachel Walensky made the same point in early 2022 but in the context of vaccine breakthrough deaths from Covid-19, examined in another CDC study from early 2022 (Yek et al. 2022). Walensky stated:
[CDC published] a study of 1.2 million people who are vaccinated between December and October. And demonstrated that severe [Covid-19] disease occurred in about 0.015% of the people who were — received their primary series — and death in 0.0003% of those people. The overwhelming number of deaths, over 75%, occurred in people who had at least four comorbidities. So really, these are people who were unwell to begin with.
The study itself concludes (p. 24): “COVID-19–associated outcomes occurred in a small proportion of persons (0.015%) who had completed primary vaccination, all of whom were aged ≥65 years, immunosuppressed, or had other underlying conditions.” And the “over 75%” figure quoted by Walensky is actually 78% in the study and it applies to “risk factors,” which is a more general term than “comorbidities” (p. 23). The risk factors studied by Yek et al. include (see Table 1): “age ≥65 years, diabetes mellitus, immunosuppression, chronic kidney disease, chronic liver disease, chronic neurologic disease, chronic cardiac disease, or chronic pulmonary disease.”
This same logic, stated by Walensky and by Yek et al., applies for all “deaths involving Covid-19,” and not just those associated with breakthrough cases, but it’s even worse. As just mentioned, CDC’s own data show that on average there were 4.0 other causes of death (comorbidities) in US “deaths involving Covid-19.” The list of “conditions contributing to death where Covid-19 was listed as a cause of death” in this CDC table is a longer list than the eight “risk factors” examined by Yek et al. 2022.
So it’s not only 78% of deaths that had 4.0 additional comorbidities, as CDC found in the context of vaccine-linked Covid-19 deaths, but 100% of deaths being attributed to Covid-19 more generally have had 4.0 additional comorbidities.
Critics of the CDC rightly pounced and claimed that this same logic used by Walensky applies to Covid-19 deaths more generally.
Then the “fact checkers” pounced and cried foul — but got it wrong yet again, for the reasons I’ve just gone over. Walensky’s logic about alleged vaccine-associated Covid-19 deaths does indeed apply to all “deaths involving Covid-19,” but with even more force.
It’s very similar to the recent debate (a major step in the right direction) about hospitalization “with” or “from” Covid. Walensky herself, again, and joined by Dr. Fauci, have highlighted the need to distinguish hospitalizations figures in terms of incidental vs. causally-related Covid hospitalizations. All patients in the US are tested for Covid-19 upon admission to the hospital, regardless of symptoms and regardless of why they’re at the hospital. This practice will lead to a lot of false positives and a lot of incidental Covid-19, as explored by The Atlantic’s David Zweig in this piece. One study discussed by Zweig, Webb and Osburn 2021, found fully 86% of pediatric “Covid hospitalizations” were not related or only minimally related to Covid-19.
This same logic again applies directly to “deaths involving Covid-19,” and again for the same reasons: massively over-inclusive definitions that generally rely simply on a positive test result to label something a “Covid hospitalization” or a “Covid death.” How many of the approximately 900,000 deaths “involving Covid-19” were “with” vs. “from” Covid-19? The data are steadily coming out supporting the view that a large share of these “deaths involving Covid-19” are “with” rather than “from” Covid-19.
We’ve gone through the data in some detail in this recent essay and we conclude that about 90% of cases, hospitalizations and deaths attributed to Covid are probably “with” rather than “from.” This leads to a very different view, indeed, about the nature of the pandemic — and what the appropriate public and policy reactions should be.
In sum, US and global media are fundamentally failing in their duty to inform the public about complex issues and to explain all of these figures. The CDC does not claim that these deaths are “from” Covid-19 and all of these writers from mainstream media outlets should know this basic fact about these statistics.
So at this point the mainstream media seem to be intentionally distorting the truth, apparently out of a desire for eyeballs and associated ad revenue. Clickbait. “If it bleeds it leads.” And I’m extremely tired of it.
It is only if you — yes, you — start spreading these facts that the media and our elected and public officials will start to actually be honest with the data.
