On Thursday, Dr. Ali Mokdad, a rep for the Bill Gates-funded IHME dodged questions about the low Coronavirus cases in Japan despite the country not shutting down the country like the US.
Ali Mokdad didn’t answer the question — because he has no answer.
The University of Washington IHME Center has been putting out numbers on the coronavirus pandemic for several weeks now… Each one was just as sketchy and inaccurate as the last.
It is important to note that the IHME models predicting hundreds of thousands of dead Americans had social distancing and total lockdowns baked into the projections.
Americans were told that if they all stayed home and only went to the grocery store when necessary, over 200,000 would still die.
The IHME keeps revising their models because they have been WAY off — the latest projection model was revised downward from 2,000,000 projected deaths to about 60,000 deaths in the US. The current number of deaths in the US is 26,112 and that’s with New York tossing in an extra 3,700 to their total for the hell of it.
On Friday night Ali Mokdad joined Bill Hemmer on FOX News and announced that Washington, New York and California are going to start going down in their number of coronavirus deaths.
The IHME continues to adjust their models from extreme panic to something more resembling a typical flu season with each passing day.
It is shocking to watch respected journalists and US policy makers still give this shady group any authority.
There isn’t much about Ali Mokdad’s biography. However, in 2005 he had to print a retraction in the Journal of the American Medical Association for overestimating deaths from obesity. His models were grossly exaggerated.
So why was he ever trusted?
Ali Mokdad’s “Actual Causes of Death in the United States, 2000,” published in the Journal of the American Medical Association (JAMA) in 2005 was widely panned.
Mokdad’s team purported to demonstrate that 400,000 deaths in the United States per year could be attributed to overweight and obesity, leading the CDC to begin a wide-ranging campaign to reduce obesity rates. His testing was flawed and he was warned about his testing being flawed. He published his crap investigation anyway.
However, Mokdad’s results were suspect. Mokdad’s team was forced to print a correction in a 2005 issue of JAMA acknowledging a computational error that overstated the number of deaths from overweight and obesity.”
Via Activist Facts:
Ali Mokdad is an epidemiologist who authored a Centers for Disease Control (CDC) study in 2004 that received widespread criticism for its methodology, “Actual Causes of Death in the United States, 2000,” published in the Journal of the American Medical Association (JAMA). Mokdad’s team purported to demonstrate that 400,000 deaths in the United States per year could be attributed to overweight and obesity, leading the CDC to begin a wide-ranging campaign to reduce obesity rates.
Mokdad’s results were suspect, however. Mokdad’s team was forced to print a correction in a 2005 issue of JAMA acknowledging a computational error that overstated the number of deaths from overweight and obesity.
Subsequent research in JAMA demonstrated that Mokdad’s methodology was suspect as well. A different CDC research team found that a mere 25,000 deaths could be attributed to overweight and obesity combined, since overweight status was in fact protective against early death.
The model that Mokdad and his team used was questioned before the study was published. CDC scientists who reviewed the study noted the following (all emphases added):
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Methods used to calculate number of deaths due to obesity were incorrect and possibly miscalculated … The use of the improper formula is a rather serious mistake to make. At the time this study was being conducted, the scientific literature had several papers describing potential bias. Following Allison et al. in using an incorrect method was not justified. From the cross-clearance, it seems as if this bias from the wrong formula was pointed out to the authors.
The knowledge about inappropriate use of adjusted relative risks in certain attributable-fraction formulas was in the literature prior to the preparation of this manuscript and was apparently shared with the authors prior to publication.
My general conclusion is that the Mokdad et al. paper makes some bold statements, bolder than the original McGinnis and Foege paper, which might have been better off being presented as a policy exercise rather than a scientific study; the estimates seemed a combination of scientific calculation and expert opinion. Furthermore, the scientific reviewers of the paper who mentioned the problems were not taken as seriously as they could have been.