Analyzing the Evolution of SARS-CoV-2 with AI – A First Step in Infectious Disease Countermeasures

A research group including Junya Sunagawa, a doctoral student at the Graduate School of Life Science, Hokkaido University, and Assistant Professor Ryo Yamaguchi in the Faculty of Life Science, Hokkaido University, in collaboration with a research group led by Professor Shingo Iwami in the Graduate School of Science, Nagoya University, has revealed that the evolution of SARS-CoV-2 was related to clinical symptoms such as incubation period and asymptomatic rate, as well as to human behaviour.

Analysis of clinical data from 274 individuals infected with Wuhan, Alpha, Delta, and Omicron strains showed an evolutionary trend toward increased and accelerated peak viral shedding in vivo with the emergence of mutant strains. Furthermore, the development of a simulator incorporating AI methods suggested that this evolutionary trend may have been established as a survival strategy of the virus to overcome the actions humans take to protect themselves from infectious diseases (e.g., quarantining infected persons) in response to the appearance of mutant strains.

While previous studies have shown that antimicrobials and antivirals have driven pathogen evolution, this study reveals that human behaviour itself is also an important cause in understanding virus evolution. Amid concerns about the emergence of new mutant strains, the results of this study and a simulator incorporating AI technology are expected to be an important step forward in predicting future virus evolution and establishing countermeasures against infectious diseases.