As public health officials around the world contend with the latest surge of the COVID-19 pandemic, researchers at Drexel University have created a computer model that could help them be better prepared for the next one.
Using machine learning algorithms, trained to identify correlations between changes in the genetic sequence of the COVID-19 virus and upticks in transmission, hospitalizations and deaths, the model can provide an early warning about the severity of new variants.
The Drexel model, which was recently published in the journal Computers in Biology and Medicine, is driven by a targeted analysis of the genetic sequence of the virus’s spike protein — the part of the virus that allows it to evade the immune system and infect healthy cells, it is also the part known to have mutated most frequently throughout the pandemic — combined with a mixed effects machine learning analysis of factors such as age, sex and geographic location of COVID patients.
