ISU research validates CDC vaccine rollout

DES MOINES — The federal government’s plan for distributing the first doses of the COVID-19 vaccines roughly a year ago mostly hit the mark and likely helped to limit the number of virus-related deaths, according to a recent analysis and report from researchers at Iowa State University.

About this time last year, the COVID-19 vaccines were first being rolled out to the American public. One of the most important debates at that time was how the first doses should be distributed. In other words: Who should be able to get the vaccine first?

The U.S. Centers for Disease Control and Prevention developed a plan that prioritized health care workers, long-term care residents, other front-line essential workers like police and firefighters, the elderly and individuals with problematic health conditions.

ISU researchers were part of a team that used computer modeling to evaluate 17.5 million possible strategies that the CDC could have recommended to state and local governments for the COVID-19 vaccine rollout. The researchers’ analysis generally validated the CDC’s plan, while highlighting some possible minor improvements.

The research could help inform future strategies, ISU officials said.

“The CDC strategy did really well when we compared it to all the other possible strategies, especially in preventing deaths across age groups,” Claus Kadelka, an assistant professor of mathematics at ISU and an author of the paper published off the research, said in a university report. “Our research shows the CDC’s higher prioritization of front-line essential workers, people in older age groups, and people with underlying health factors was a highly effective strategy for curbing COVID-19 mortality, while keeping overall case numbers at bay.”

To perform the analysis, according to ISU, the research team built a mathematics model incorporating the CDC’s four staggered phases for the COVID-19 vaccine rollout, 17 subpopulations of people based on myriad demographic factors, and 20 health categories like vaccinated, susceptible, infected and recovered. The group also incorporated other influencing factors like vaccine hesitancy, social distancing levels and infection rates.

For each of the 17.5 million runs, researchers recorded several outcome metrics, including projected cases and deaths.

The research showed the CDC’s recommendations could have been optimized if more individuals with known COVID-19 risk factors had been prioritized over people in their cohort without health risks. However, the gains would have been statistically small — 1 percent fewer deaths and 4 percent fewer cases — and the model was unable to take into account possible logistical challenges.

“We don’t know enough about the situation in nursing homes to know how easy it would be to distinguish which residents have greater risk factors that would put them at the front of the vaccination line,” Kadelka said. “That’s something you can do in a mathematical model, but it could be hard in practice.”

Researchers said their mathematical model could be used to inform future vaccination strategies, whether related to COVID-19 or another, future pandemic.

“If the (SARS-CoV-2) virus mutated enough that it rendered the current vaccines ineffective, or we have a new pandemic, whether that’s in another 100 years or two years from now, we need to be able to accurately predict what the outcome will be when decisions are made regarding who’s vaccinated first,” Kadelka said.