On November 13, Genevieve Briand conducted “COVID-19 Deaths: A Look at U.S. Data,” an online lecture she called a “friendly conversation on a morose topic.” In her presentation, the Johns Hopkins University professor posed a question of little interest to most politicians and media personalities. “How can we say COVID-19 death numbers are concerning,” she wondered, “if we don’t compare them to total death numbers — the numbers that we should expect every year?”
After crunching data from the Centers for Disease Control and Prevention, Briand reached a conclusion that a physicist and regular KIVA listener reached months earlier: As a killer, at least so far, the novel coronavirus is a bit of a bust.
Briand’s analysis began with the observation that however intensely most of us want to ignore it, death is ubiquitous. People die all the time, for all sorts of reasons. For example, about 530 Americans aged 14 or under lose their lives every week. So to get a sense of COVID-19’s true toll, it’s essential to scrutinize what mortality was in previous, comparable periods, and contrast it with the figures for the time of The Rona.
The first of Briand’s findings was a sign of the strangeness to come. It’s commonly accepted that COVID-19 claims far more elderly than middle-aged and young victims. But as 2020 wore on, and the pandemic intensified, the share of older Americans comprising weekly all-cause deaths did not change to any significant degree. (See chart below.)
When the economist shifted to a survey of total mortality from all causes and in all age groups, from January through September for the years 2014 through 2020, Briand was stunned. She found that for 2020, “death numbers [were] not above normal death numbers,” and thus, there was “no evidence that COVID-19 created any excess death.”
How can that possibly be, given official statistics that “confirmed and probable” COVID-19 deaths reached nearly 200,000 by the end of September?
The answer is that the trend in declared — as opposed to actual — causes of death had transformed. Americans started to “die from COVID” right around the time of year when mortality, due to all forms of illness and disease, peaks. And as the university’s student newspaper reported, in an article that was later scrubbed because it was being “used to support dangerous inaccuracies that minimize the impact of the pandemic”:
When Briand looked at the 2020 data during that seasonal period, COVID-19-related deaths exceeded deaths from heart diseases. This was highly unusual since heart disease has always prevailed as the leading cause of deaths. However, when taking a closer look at the death numbers, she noted something strange. As Briand compared the number of deaths per cause during that period in 2020 to 2018, she noticed that instead of the expected drastic increase across all causes, there was a significant decrease in deaths due to heart disease. Even more surprising … this sudden decline in deaths is observed for all other causes.
As Briand asked in her lecture, “Where have all the heart attacks gone?” For that matter, what about deaths from cancer and diabetes and Alzheimer’s disease?
Two words: “ascertainment bias.” As described by Carl Heneghan, the director of the University of Oxford’s Centre for Evidence-Based Medicine, it’s the tendency for disease outbreaks to induce medical professionals “to focus on the worst-case scenario.” Back in the earliest days of the novel coronavirus, he predicted that “people will call every death as though it’s related to Covid-19. But that is not the case.”
Not long after Heneghan’s warning, Ngozi O. Ezike, the director of the Illinois Department of Public Health, publicly admitted:
If you were in hospice and had already been given a few weeks to live, and then you also were found to have COVID, that would be counted as a COVID death. It means technically even if you died of a clear alternate cause, but you had COVID at the same time, it’s still listed as a COVID death. So, everyone who’s listed as a COVID death doesn’t mean that that was the cause of the death, but they had COVID at the time of the death.
In an October piece for Newsweek, Timothy Allen and John Lott noted that:
The Centers for Disease Control guidance acknowledges the uncertainty that doctors face when identifying causes of death. When coronavirus cases are “suspected,” the agency counsels doctors that “it is acceptable to report COVID-19 on a death certificate.” This advice has produced a predictable inflation in the numbers. On April 21, when New York City’s death toll rose above 10,000, The New York Times reported that the city included “3,700 additional people who were presumed to have died of the coronavirus but had never tested positive” -- a more than 50 percent increase in the number of cases.
Regardless of the reason(s) for the glaring anomaly she uncovered, Briand makes a strong case that COVID-19 deaths are being vastly overstated. And that same conclusion was reached, this summer, by a scientist based in New Mexico.
A Ph.D. physicist employed at a key facility in the federal government’s vast research-and-development infrastructure, he has spent “the past 25 years in semiconductor processing.” Understandably, with Cancel Culture raging, “Dr. X” wishes to remain anonymous. Like Briand, he uses data from the Centers for Disease Control and Prevention, but he journeys much further back. Our source’s first product explored all-cause “deaths per 100 people … from January through July for 1999-2020 by state and age group” for “the 22 contiguous states west of the Mississippi River.” He determined that “relative to things that kill us all the time, [COVID-19] is not exceptionally deadly,” and “that’s true for all age groups.”
Earlier this month, Dr. X was back, sending KIVA a review of total deaths “from all causes from January through October, 1999-2020,” for the contiguous states excepting North Carolina. The figures confirm his earlier work, as the chart below, focused solely on New Mexico, shows.
Dr. X. also found that the “correlation between total (all causes) death rates and [COVID-19] death rates is weak.” For example, New York has an official coronavirus death rate 35 times higher than Maine, but the two states’ total “death rates are essentially the same.” The entire data set’s correlation value, which measures “how an ostensibly independent variable impacts an ostensibly dependent variable,” is 0.345487. (See below.) Not very impressive, since “anything less than 0.5 is a weak correlation.”
Both Briand and Dr. X have not conducted formal, peer-reviewed analyses, of course, and the latter cautions that he is merely “plotting the readily available CDC data in a way that I think makes it easier to understand the [COVID-19] risk in context.” But their findings are compelling enough, and should invite fresh inquiry, investigation, and discussion. Sadly, at a time when any deviation from the public-health establishment’s coronavirus narrative is swiftly condemned as “COVID denial,” no such effort is likely to occur.