Airports In Honolulu, LA, NY Could Influence Pandemic Spread
Connie K. Ho for redOrbit.com — Your Universe Online
2003 SARS outbreak. 2009 H1N1 flu pandemic. These are just a few of the public health crises that have arisen in the past decade. To better understand how new bacteria or viruses could spread around the world with the help of air travel, epidemiologists and scientists from the Massachusetts Institute of Technology (MIT) Department of Civil and Environmental Engineering (CEE) looked at how location can affect high infection rates.
The researchers studied how the first few days of an epidemic could be influenced by airports, in particular the 40 largest U.S. airports. They believe that the study could help them better understand the actions needed to contain an infection and the policies public health officials should consider in distributing vaccines or treatments during a pandemic. The new MIT model in the project includes factors such as geographic locations of the airports, the amount of interactions among airports, the waiting time of passengers in airports, as well as the movement pattern of travelers. It will allow scientists to better predict the location and the amount of time it takes a disease to spread and is featured in a paper published recently in the journal PLoS ONE.
“Our work is the first to look at the spatial spreading of contagion processes at early times, and to propose a predictor for which ‘nodes’ – in this case, airports – will lead to more aggressive spatial spreading,” explained Ruben Juanes, the ARCO Associate Professor in Energy Studies in CEE, in a prepared statement. “The findings could form the basis for an initial evaluation of vaccine allocation strategies in the event of an outbreak, and could inform national security agencies of the most vulnerable pathways for biological attacks in a densely connected world.”
The foundation of the project was based off of Juanes´ past research done on the flow of fluids of subsurface rock via fractured networks as well as the studies done by fellow researcher Marta GonzÃ¡lez on human mobility networks and contagion processes in social networks.
“The study of spreading dynamics and human mobility, using tools of complex networks, can be applied to many different fields of study to improve predictive models,” remarked GonzÃ¡lez, a CEE professor, in the statement. “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.”
Juanes and fellow researchers then applied Monte Carlo simulations to understand the patterns of an individual traveler.
“The results from our model are very different from those of a conventional model that relies on the random diffusion of travelers “¦ [and] similar to the advective flow of fluids,” noted graduate student Christos Nicolaides in the statement. “The advective transport process relies on distinctive properties of the substance that’s moving, as opposed to diffusion, which assumes a random flow. If you include diffusion only in the model, the biggest airport hubs in terms of traffic would be the most influential spreaders of disease. But that’s not accurate.”
Based on the model, Kennedy Airport ranks first, with airports in Los Angles, Honolulu, San Francisco, Newark, Chicago (O´Hare), and Washington (Dulles) following. While Honolulu has 30 percent as much traffic as New York´s Kennedy International Airport, due to its location in the Pacific Ocean and its connection to important hubs, it became ranked third for its ability in spreading contagions. As well, while Atlanta´s Hartsfield-Jackson International airport in terms of number of flights, it ranks eight in contagion influence. Boston´s Logan International Airport came in 18th place.
“Nowadays, one of the most ambitious scientific goals is to predict how different processes of great economic and societal impact evolve as time goes on,” commented Professor Yamir Moreno, researcher of complex networks and epidemic patterns at the University of Zaragoza, in a statement. “We are currently capable of modeling with some detail real disease outbreaks, but we are less effective when it comes to identifying new countermeasures to minimize the impact of an emerging disease. The work done by the MIT team paves the way to find new containment strategies, as the newly developed measure of influential spreading allows for a better comprehension of the spatiotemporal patterns characterizing the initial stages of a disease outbreak.”
Image 2 (below): World map shows flight routes from the 40 largest U.S. airports. Credit: Christos Nicolaides, Juanes Research Group