Kim Reynolds, COVID-19, and the Difference Between Data and Science
COVID-19 has changed our society in ways we won’t begin to fully understand for months or years. But one of the most immediate changes to our daily lives has been the fact that each and every one of us has become an amateur epidemiologist.
There are a lot of interesting manifestations and implications of this, but one of the most interesting cases in recent days has been taking place in my home state of Iowa.
During a press briefing on Thursday, Gov. Kim Reynolds explained why she’s one of a small minority of governors who have so far declined to issue a shelter-in-place order. There are many possible reasons a governor might want to avoid such an order, but Reynolds insisted that her decision was not based on politics or practicality. Her decision, she said, was based on science.
Reynolds said she is using a “12-point scale” to decide whether and when to issue a shelter-in-place decree. The scale, which was described in an internal document obtained by the Des Moines Register, includes four metrics: the rate of COVID-19 hospitalizations, the rate of infection, the infection rate among the elderly, and the number of outbreaks in long-term care facilities. Each of those categories is equally weighted, and a point value is assigned based on a scale included in the document. According to the plan, a shelter-in-place order is only indicated if the state scores a 10 out of 12.
In Reynolds’ mind, the presence of the 12-point scale means her decision is data-driven.
“My challenge I guess to the individuals out there that think I haven’t done enough, I would ask them to go and take a look at other states and recommendations that they’ve put in their stay at home — I don’t care what you call it — I’m basing it on data,” Reynolds said, as quoted by the Associated Press.
Of course, feeding data into a scoring system doesn’t make the scoring system scientifically accurate any more than pouring gasoline into something makes it into a car.
The value of the 12-point scale depends on the underlying science used to devise the point system, and therein lies Reynolds’ problem. While the governor has been more than willing to explain that she’s basing her decisions on the 12-point scale, she has been unwilling to describe precisely why this particular 12-point scale is valid.
When the Register asked the governor’s office for the names of the people who had developed the 12-point system, the governor’s office did not respond (the document is on Iowa Department of Public Health letterhead, but no names are attached).
When reporters from the paper attempted to ask about the document at a subsequent telephone-based press conference, the governor’s office did not call on any reporters from the Register, even though it’s the state’s largest paper.
When the Register called The University of Iowa’s Carver College of Medicine in an attempt to vet the scientific value of the scale, professor Eli Perencevich expressed frustration.
“Not one of the criteria has anything to do with how the virus spreads,” Perencevich told the Register. “The decision should be about estimating how many people are infected.”
Perencevich’s viewpoint appears to align with that of Anthony Fauci, head of the National Institute of Allergy and Infectious Disease, and a member of the president’s COVID-19 task force.
On Friday, the Iowa Board of Medicine voted unanimously to ask the governor to issue a shelter-in-place order.
To be sure, not every doctor or epidemiologist would agree with Perencevich, Fauci, and the Iowa Board of Medicine. After all, part of what makes science science is the fact that nothing is sacred. Some of history’s most influential scientists became influential precisely because they disagreed with the majority opinion.
The problem with Reynolds’ approach is not that she wants to use data to help make her decision. It’s that she has so far refused to explain the scientific basis of the tool she’s using to interpret the data.
If the 12-point scale is scientifically valid, then Reynolds ought to be open and transparent in explaining why it’s valid. If it’s not valid, then she’s merely hiding behind data. Hiding behind data is decidedly unscientific.
