Scripps Researchers out of California have developed a machine learning system to track the evolution of epidemic viruses in detail. The technology can also predict the emergence of viral variants.
In a Cell Patterns paper published July 21, 2023, the scientists demonstrated their system. They used data from the COVID-19 pandemic, including the emergence of SARS-CoV-2 variants and mortality rates.
The program predicted the emergence of “varients of concern” (VOCs) ahead of their official designations by the World Health Organization (WHO).
“There are rules of pandemic virus evolution that we have not understood but can be discovered, and used in an actionable sense by private and public health organizations, through this unprecedented machine-learning approach,” says study senior author William Balch, PhD, professor in the Department of Molecular Medicine at Scripps Research.
The co-first authors, Salvatore Loguercio, Ph.D., and Ben Calverley, Ph.D., work in the Balch lab, which specializes in developing computational, often AI-based methods, showing how genetic variations alter the spread and symptoms of disease. Their software tracked three data sets over the course of the COVID pandemic:
- The genetic sequences of SARS-CoV-2 variants found in infected people worldwide
- The frequencies of those variants
- The global mortality rate for COVID-19
The researchers claim that a similar system could enable scientists to predict changes in a future pandemic’s trajectory in real-time.