AI-based Modeling May Predict Measles Outbreaks

As the world battles the resurgence of measles outbreaks, most vaccination campaigns are reactive.

According to an announcement by Ginkgo Bioworks, an AI-enabled measles forecasting model may soon empower proactive public health measures, such as immunization campaigns.

Announced today, Ginkgo's epidemiological modeling experts and Northeastern University researchers were awarded a grant from the Bill & Melinda Gates Foundation to develop a forecasting model to assess the risk of measles outbreaks and inform decision-making for timely interventions.

This innovative model will draw upon traditional and non-traditional data, including public health reports, travel patterns, economic activity, and other factors, and utilize AI approaches such as machine learning and deep learning to structure and analyze a multitude of data sources to produce actionable insights.

Matt McKnight, General Manager for Biosecurity at Ginkgo Bioworks, commented in a press release on April 10, 2024, "If we wait until large pockets of measles show up in hospital systems to launch public health responses, we are missing a critical window to act and slow the spread of this debilitating and highly contagious disease."

"Modern data and AI tools can shift the biosecurity and public health paradigm from reactive to proactive by helping global health leaders make more timely, effective decisions to prevent outbreaks from happening in the first place."

Measles is a highly contagious and often severe disease that most commonly affects children. While the widespread availability of measles vaccines has dramatically reduced the disease burden over the past several decades, cases are on the rise in the U.S. in 2024.

The majority of measles cases imported into the United States occur in unvaccinated residents who become infected during international travel, says the U.S. CDC.

For example, a substantive, ongoing measles outbreak has occurred in Chicago, Illinois, over the past two months.