It might be time to stop relying so heavily on statistical significance, he argues.
 | By Alexandra Sifferlin Senior Staff Editor, Opinion |
The Omicron wave in the United States has subsided over the past month, with cases down about 60 percent from two weeks ago. In response, state and local governments are relaxing many restrictions, like mask mandates, while vaccine requirements in places like New York City may be on the way out. The Centers for Disease Control and Prevention is also changing the way it evaluates community risk levels to include data on hospitals and health care capacity, in addition to case counts. Cases alone may not offer the clearest picture of how an area is faring after widespread vaccinations and infections. |
Dr. Ashish Jha, the dean of the Brown University School of Public Health, writes in a guest essay that the United States has entered a "new phase" of the pandemic, so these new metrics are reasonable. "A virus and a population interact in a dizzyingly dynamic system, with mutations and layering immunity forming different profiles of population-wide risk at different times," he writes. "Policy does and should recognize when these factors have changed enough to justify new approaches." |
While restrictions relax and many Americans resume some of their prepandemic routines, there are still roadblocks for some groups. Parents of children under 5, for example, may feel stuck given the delay in vaccines for that age group. One such person is Aubrey Clayton, a statistician and a father of three children under age 4 who cannot yet be vaccinated. |
"Like many caregivers guarding young children against the coronavirus, my winter has been full of rapid tests, mask reorders and outdoor play dates in borderline frostbite conditions," he writes in a guest essay. "I'm able to manage this because I believe it's temporary; we just need to hold out a little longer until our children can get vaccinated." |
Clayton, who studies statistics, argues that the vaccines are not being evaluated with the best framework. "I'm also racked with concern that if the data had been assessed in a more nuanced way, we might be putting vaccination appointments on the family calendar right now," he adds. |
Specifically, Clayton argues that the thinking around the data for a vaccine for children under five years old needs to shift. His essay is part of a larger debate among statisticians over the value of relying too heavily on statistical significance, which some argue is too binary. "What we need for the under-5 vaccine trial evaluation, instead of judgments of absolute safety or efficacy, is probable improvement over the next best alternative, taking into consideration all the available information," Clayton writes. |
Clayton favors a Bayesian approach to data assessment. This framework would have investigators constantly update their understanding of any scientific claim based on the latest data, while also incorporating their prior beliefs, never definitively labeling a claim as proven or disproven. |
The essay is a compelling argument for a different way of thinking, not just about the vaccine for kids under 5, but also about how to best navigate decision-making in times of uncertainty and limited information. |
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