Lying With Statistics: How One Group Is Using Bad Numbers to Suggest a Mask Mandate

The Journal Nature Medicine published a story in late October that showed half of all Americans aren’t wearing masks, and that by pushing up the number of people wearing masks we could prevent as many as 130,000 deaths by the end of February. The claim came from the University of Washington’s Institute for Health Metrics Evaluation, or IHME.

The numbers are being thrown around in a bid to get the federal government to require that all Americans wear masks in public, but there’s a problem. The numbers are old and inaccurate and therefore lead to a false conclusion.

The data on mask-wearing comes from a study that finished in late June, showing 49% of Americans say they “always” wear a mask in public, even though the study as printed suggests the data was current up to late September. The IHME determined that if we increased that number closer to 90%, we could dramatically reduce the number of deaths.

But as Philip Magness points out, a study by YouGov showed that mask-wearing skyrocketed in July, with nearly 80% of Americans reporting they either “always” or “almost always” wear a mask in public. With the number of people wearing masks already at high levels, we can’t increase mask-wearing by another 35% to 40% as the study in Nature Medicine suggests, so a national push or mandate to wear masks would not achieve their estimate of saving 130,000 lives over the next four months.

Magness reached out to the journal and pointed out the error. This is the response he received:

“An editor replied that the “alleged discrepancies” were “not issues of substance that would require further action” because “information about what datasets were utilized in the authors’ models and periods they encompass are reported in the study.”

So as long as they identified their datasets, then misleading the public really isn’t a concern.

This is how misinformation becomes embedded in the public conversation.

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