In a world of increasing global connections, predicting the spread of infectious diseases is more complicated than ever. Pandemics no longer follow the patterns they did centuries ago, when diseases swept through populations town by town; instead, they spread quickly and seemingly at random, spurred by the interactions of 3 billion air travelers per year.
A computational model developed by Northwestern University's Dirk Brockmann could provide better insight into how today's diseases might strike. Brockmann, an associate professor of engineering sciences and applied mathematics at the McCormick School of Engineering and Applied Science, uses transportation data to develop models that better pinpoint the source of an outbreak and help determine how a disease could spread.
Brockmann will discuss his research in a presentation titled "Are Pandemics Predictable?" at the American Association for the Advancement of Science (AAAS) annual meeting in Boston. His presentation is part of the symposium "Predictability: From Physical to Data Sciences" to be held from 8:30 to 11:30 a.m. on Saturday, Feb. 16.
The ability to pinpoint with certainty the location of a pandemic outbreak and to predict where and how quickly it will spread would give governments and clinicians an important -- and potentially lifesaving -- advantage in responding to the disease, but current prediction models are limited.