A new artificial intelligence model developed at MIT, called VaxSeer, promises to substantially improve the accuracy of flu vaccine predictions, possibly leading⁢ to more effective seasonal ⁢immunizations.The⁣ technology analyzes viral data to anticipate which strains will be dominant, addressing a long-standing challenge in public ⁢health.

Predicting which ⁣influenza strains will circulate each⁤ season is notoriously challenging. The ⁣influenza virus mutates rapidly, and the dominant strains ⁣can vary significantly across geographic regions.⁤ Traditional ⁢methods rely⁤ on surveillance data from the Southern Hemisphere during⁢ its ⁣flu season, which is than used to inform ⁣vaccine⁢ development for the Northern⁤ Hemisphere. This process is frequently enough⁤ slow⁤ and imperfect, leading to vaccines that don't always match the circulating strains[[[[CDC - Vaccine Effectiveness ].

The effectiveness of flu vaccines typically ranges from 40% to 60%, according to the Centers for⁣ Disease Control and prevention (CDC). A mismatch⁤ between the vaccine and circulating strains is a primary reason for lower effectiveness.