Data supports new CDC mask policy

The Centers for Disease Control and Prevention (CDC) announced that those who have been vaccinated can doff their face masks when around other vaccinated people. This announcement was inevitable — though some may argue that it is premature — given that the number of daily confirmed infections continues to hover in the tens of thousands.   

The big qualifier in the announcement is “around other vaccinated people.”    

One’s immediate reaction is that no one knows who is vaccinated, unless they volunteer such information. Won’t this open the floodgate to those who are not vaccinated to go maskless in public?  

Indeed it will. These people most likely never wanted to wear a face mask and only did so under duress to accomplish some prescribed objective, like keeping their job. Such people can use the CDC face mask relaxation as their ticket to going maskless. Many in this group are also least likely to be vaccinated, remaining silent or misrepresent their situation if asked.     

Those who have been vaccinated are happy to share their status and continue to follow CDC guidelines on face coverings in public places where physical distancing is infeasible and people’s vaccine status cannot be confirmed.    

Habits die hard. After over a year of donning a face mask, many who have been adherent to wearing face coverings and social distancing when in public will continue to follow such practices. They are also the same people most likely to be vaccinated.  

The data on vaccine safety and efficacy is remarkable. Over 124 million people have been fully vaccinated to-date, with minimal side effects reported. This represents almost one-half of the entire adult population. For those over 65 years, almost 75 percent of them have been fully vaccinated. These numbers explain why the number of new cases have plummeted from a peak of over 312,000 on Jan. 8, to current levels, a drop of over 90 percent.    

Breakthrough infection data (people who become infected after they are vaccinated) provide valuable information to assess the effectiveness of the vaccines. As of May 10, the CDC reports a rate of less than one COVID-19 hospitalization for every 144,000 vaccinated adults, which indicates that the vaccines are keeping people safe. The rate for COVID-19 fatalities has been one in 635,000 vaccinated adults, again, a remarkably low fatality risk and well below the general population COVID-19 fatality risk by a factor of 100.  

At some point, the CDC had to take this leap of faith and trust the science behind the vaccines and the data supporting the science to allow vaccinated people to make personal choices on how they wish to open their lives.     

Nothing prevents local areas from adjusting to these guidelines to suit their circumstances, such as local surges in cases.The CDC guidelines do not preclude such actions, since bottom-up actions are often needed to improve top down directives.   

The new CDC guidelines are less about wearing or not wearing face masks and more about being vaccinated. The data indicates that those vaccinated are not experiencing the worst outcomes from COVID-19. Earlier data indicated that those vaccinated were being infected at a rate of one in 10,000. Even if this data is off by a factor of 100, an infection rate of 1 percent, with most of these people asymptomatic or with mild symptoms is the bridge forward to a safe society for all.    

The new CDC guidelines reward the 120+ million people who are vaccinated to-date. Punishing these adherent people for the 50 million people who indicate no interest in being vaccinated is unnecessary and misguided, given the data available. 

Amongst those unwilling to be vaccinated, many will get infected, some will be hospitalized and a number will die. These are avoidable deaths, but in a free society, people make choices that are not always in their best interest.      

Getting vaccinated is one such choice.   

Sheldon H. Jacobson, PhD, is a founder professor of Computer Science at the University of Illinois at Urbana-Champaign. He is a data scientist focusing on data–driven decision-making under uncertainty.