As of early August, 34 US states mandate the use of masks in public to limit the spread of COVID-19.

The efficacy of face masks has been a subject of debate in the health community during the pandemic. Because health experts disagree on their effectiveness, countries and health agencies around the world, including the World Health Organization and the CDC, have done a reversal on their mask recommendations during the pandemic.

Reasonable and persuasive cases can be made both for and against the use of masks in the general population. Unfortunately, the science of masks and viruses is becoming less clear because of the politicized nature of the debate.

A case in point is the Kansas public health official who made news last week after he was accused of using a deceptive chart to make it appear counties with mask mandates had lower COVID-19 case rates than they actually did.

At a press conference, Kansas Department of Health and Environment Secretary Dr. Lee Norman credited face masks with positive statewide COVID-19 trends showing a general decline in deaths, hospitalizations, and new cases.

Norman pointed to a chart (see below) that depicted two lines tracking cases per 100,000 people between July 12 and August 3. The red line begins higher than the blue line but then falls precipitously as it travels down the X-axis, ending below a blue line.

Norman explains that the red line represented the 15 counties with mask mandates, which account for two thirds of the state’s population. The flat blue line represented the remaining 90 counties, which had no mask mandates in place.

“All of the improvement in case development comes from those counties wearing masks,” Norman said.

The results are clear, Norman claimed. The red line shows reduction. The blue line is flat. Kansas’s real-life experiment showed that masks work.

It didn’t take long for people to realize something wasn’t quite right, however. The blue line and the red line were not on the same axis.

This gave the impression that counties with mask mandates in place had fewer daily cases than counties without mask mandates. This is not the case, however. In reality, counties with masks mandates have far higher daily COVID-19 cases than counties without mask mandates.

If the trends are depicted on the same axis, the blue and red lines look like this.

Many Kansans were not pleased with the trickery.

Kansas Policy Institute expert Michael Austin told local media that the chart clearly gives a false impression.

“It has nothing to do about whether masks are effective or not. [It’s about] making sure Kansans can make sound conclusions from accurate information,” Austin said. “And unfortunately, the chart that was shown prior in the week strongly suggested that counties that had followed Dr. Norman’s mask order outperformed counties that did not, and that was most certainly not true.”

Twitter was less diplomatic.

The chart is deceptive.

Worse, Norman also failed to note that the lines were on different axes until a reporter asked if the blue line “would get below the red line” if those counties passed mask mandates, which prompted Norman to mumble about different metrics and then admit that counties without mask mandates have lower case rates.

“The trend line is what I really want to focus on,” Norman said.

The deception prompted a non-apology from the Kansas Department of Health and Environment: “Yes, the axes are labelled differently … we recognize that it was a complex graph and may not have easily been understood and easily misinterpreted.”

Dr. Norman, meanwhile, vowed to do better next time.

“I’ll learn from that and try to [be] clearer next time,” he said following criticism from lawmakers.

The episode is unfortunate because it further clouds the science and erodes trust in the medical experts individuals rely on to make informed decisions.

It’s also ironic, because the controversy overshadowed the state’s positive data, which suggests masks may be working in Kansas. The chart may have been deceptive, but the data is correct and shows a 34 percent drop in COVID cases in counties with mandates in place.

It’s quite possible that drop is linked to county orders mandating the use of masks. Then again, the order may have nothing to do with the drop. Correlation, we know, doesn’t equal causation. If it did, the surge in COVID-19 cases in California following its mask order would be “proof” that masks increase transmission rates.

But science doesn’t work that way (at least it shouldn’t), and Dr. Norman knows this.

Maybe masks are an effective way to curb transmission of the coronavirus, or maybe it’s largely ineffective or even harmful, like the Surgeon General stated back in March. The truth is we don’t yet know.

What’s clear, as I noted last week, is that the top physicians and public health experts on the planet can’t decide if face coverings help reduce the spread of COVID-19.

In light of this, it seems both reasonable and prudent that public health officials should focus less on forcing people to “mask-up” and more on developing clear and compelling research which will allow individuals to make informed and free decisions.

This, after all, is the traditional role of public health: inform people and let them choose.

Allowing individuals to choose instead of collective bodies is the proper and more effective approach, because, as the great economist Ludwig von Mises reminded us, individuals are the source of all rational decision-making.

“All rational action is in the first place individual action,” Mises wrote in Socialism: An Economic and Sociological Analysis. “Only the individual thinks. Only the individual reasons. Only the individual acts.”

Mask orders aren’t just about public health. They are a microcosm of a larger friction at work in our society: who gets to plan our lives, individuals or the collective?

Despite what many today seem to believe, society is best served by allowing individuals to plan and control their own lives.

But individuals benefit from sound and reliable information. Sadly, that is something public health officials increasingly appear incapable or unwilling to offer.

This article was originally published on FEE.org. Read the original article.