Prediction Models for COVID-19 Can’t Account for All Human Elements

Early in the COVID-19 pandemic, researchers were scrambling to predict how the disease would spread. One such model was developed at the University of Illinois, Urbana-Champaign, by two physicists: Nigel Goldenfeld and Sergei Maslov. They were able to adapt some of the tools used in their physics research to build a model predicting how quickly the disease could spread on campus. The accounted for a range of factors, such as spread by studying, partying, and asymptomatic spread. However, positive cases of COVID-19 reached nearly 800 students in the first week of the fall semester, many more than expected.

According to Ellie Graeden of Georgetown University, “Decision-makers want answers,” noting, “A model cannot produce an answer. And it shouldn’t. It can get close. It can be suggestive.” Read more here.

(Source: Jordana Cepelwicz, Quanta Magazine, 1/28/21)