In California, a public health crisis unfolded at Disneyland in late 2014. The theme park drew millions of visitors, including many unvaccinated children. This set off one of the biggest measles outbreaks in the state in two decades, with dozens hospitalized.
Amid growing alarm, then-state Senator Richard Pan, a pediatrician, pushed a bill to eliminate personal exemptions for vaccinations. By early 2015, measles had infected 125 people across California and spread to neighboring states and Canada. As the public debated, protests erupted against Dr. Pan’s initiative.
To strengthen his case, Dr. Pan collaborated with a team at the University of Pittsburgh. They used a modeling tool called the FRED model (Framework for Reconstructing Epidemiological Dynamics) to simulate disease spread. By analyzing vaccination rates, population density, and commuting patterns, they painted a clear picture of how measles could quickly spread. This data was crucial in persuading lawmakers to approve the bill, which ultimately removed all non-medical exemptions for vaccinations in California. By the end of 2016, vaccination rates for measles in California rose—indicating a protective barrier against the disease had been achieved.
Three years later, the same Pitt team was called to Texas. Their simulations for the state’s measles situation revealed a troubling trend: declining vaccination rates in schools left pockets of children vulnerable. Short videos illustrated how quickly a single measles case could multiply if vaccination rates dropped. Their findings helped stop legislation aimed at easing vaccination opt-outs for parents. Yet, despite the warnings, Texas ignored the need for immediate action. In 2025, over 800 people were infected, resulting in two tragic deaths.
Dr. Mark Roberts from Pitt noted the significance of their predictions. He pointed out that policymakers neglected the warning signs even when simulations clearly illustrated the risks. Today’s context shows many states continue to grapple with vaccine hesitancy, and similar dynamics may exacerbate future outbreaks.
FRED’s development began back in 2001, initiated by Dr. Donald Burke after the September 11 attacks. The aim was to create a model that could predict disease outbreaks without needing to vaccinate the entire population. This approach has evolved over the years, providing valuable insights not only for measles but also for other health concerns.
As vaccination rates fall across various regions, experts stress the importance of using modeling tools like FRED. These tools are not just academic exercises; they serve as critical resources for public health planning. While predictions about disease spread have limitations, they can illuminate potential hotspots and vulnerable areas, and help guide policy decisions.
Public attention remains crucial. Campaigns that educate communities about the benefits of vaccinations are essential to counteract misinformation and fears. The measles outbreaks of the past serve as reminders of how quickly a preventable disease can spread, affecting not just those who choose to remain unvaccinated but the wider community as well.
For more detailed information on this topic and to explore simulations of measles outbreaks, you can check out the FRED model at the University of Pittsburgh here.
