Researchers at the Massachusetts Institute of Technology recently published a report that used mathematical modeling to identify the U.S. airports that, in the event of an infectious disease outbreak, are most likely to spread disease. The study took into consideration passengers’ travel patterns, airport location, interactions between airports, and waiting times for travelers.
Of the forty largest airports in the United States, John F. Kennedy International Airport in New York City ranked first on the list, followed by Los Angeles International Airport. Third on the list is Honolulu International Airport, which may come as a surprise since it only has thirty percent as much traffic as JFK. However, the researchers found that it is a key stopover for long haul flights between the United States and Asia, making it a hub for diseases and contagion.
In the MIT press release, researchers emphasized that this research differs from most of the current work in outbreak modeling and prediction because of its focus on the earliest days of an outbreak. Many studies try to predict epidemic outcomes. Instead, researcher Marta Gonzalez explained, “This [research] can improve the measures for containing infection in specific geographic areas and aid public health officials in making decisions about the distribution of vaccinations or treatments in the earliest days of contagion.”
Many recent outbreaks have been catalyzed by international travel patterns. In 2003, SARS killed 1,000 individuals, and the 2009 H1N1 epidemic is believed to have killed 300,000.
There is also hope that this type of modeling, that incorporates human mobility and technology, can be applied to other fields. Gonzalez noted, “It’s a relatively new but very robust approach. The incorporation of statistical physics methods to develop predictive models will likely have far-reaching effects for modeling in many applications.”
