Artificial intelligence could help ‘fine-tune’ vaccine priority lists, predict mortality, study reports

Much of the debate around vaccine prioritization hinges on one question: Who faces the greatest risk of dying if they become infected with COVID-19? Thus far, it is a question without a definitive answer.

Age is one way to gauge risk, with the Centers for Disease Control and Prevention recommending that people aged 75 and older be among the first members of the general public to have access to the vaccine. But in the next phase of distribution, as the CDC tries to factor in underlying medical conditions, the calculation becomes much more complex.

Artificial intelligence, when applied to standard patient medical records, can help untangle that web, a new study by Massachusetts General Hospital and Harvard researchers found.

Using only information known before a patient’s COVID-19 infection — diagnosed health problems, medications, and basic demographic information — researchers were able to identify factors that predict a heightened risk of COVID-related death. Age emerged as the most important predictor, immediately followed by a history of pneumonia, a condition not currently listed in the CDC’s prioritization plan.

“If we can predict [mortality] so well, based off of all these features that happen before individuals even get sick, this can really be applied in ways that I think are novel for an algorithm like this,” said Dr. Zachary Strasser, one of the study’s lead researchers, along with Hossein Estiri, an assistant professor of medicine at MGH and Harvard. “We can really think about who needs to get prioritized for limited resources, because these are the people that are probably going to do worse.”