Using transportation data to predict pandemics

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 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.

The ability to pinpoint with certainty the location of a 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 are limited.

Previous pandemic models have been based on geographical distance, but geography provides an incomplete picture of a pandemic. For instance, New York City and London are geographically very far apart, but with approximately 10,000 people traveling between the cities each day, the cities are far more connected than, for instance, New York City and Milwaukee, which are geographically closer.

"Furthermore, cities with a very high level of connectedness, such as London, are important epicenters for tracking the spread of diseases," Brockmann said. "When a disease reaches these cities, it is likely to spread far and quickly."

Using network theory and official transportation data, Brockmann developed a model that can generate with high accuracy the origin of an and the predicted arrival times of a pandemic in specific locations. The model can generate these findings using only data about the geographical location and number of occurrences of the disease.

"Spatial disease dynamics become far more straightforward when viewed from the right perspective using our technique," Brockmann said.

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.

add to favorites email to friend print save as pdf

Related Stories

Eyjafjallajokull's Global Fallout

Apr 23, 2010

(PhysOrg.com) -- Eyjafjallajokull and its massive cloud of volcanic ash clearly have had an enormous impact on Europe and its airports, disrupting the mobility of millions and costing airlines more than a ...

SARS: a model disease

Nov 21, 2007

A new model to predict the spread of emerging diseases has been developed by researchers in the US, Italy, and France. The model, described in the online open access journal BMC Medicine, could give healthcare professionals advanc ...

Recommended for you

Sri Lanka celebrates two years without malaria

1 hour ago

Sri Lanka has not reported a local case of malaria since October 2012, according to the Sri Lankan Anti-Malarial Campaign. If it can remain malaria-free for one more year, the country will be eligible to apply to the World ...

Poll: Many doubt hospitals can handle Ebola

5 hours ago

A new poll finds most Americans have some confidence that the U.S. health care system will prevent Ebola from spreading in this country, but they're not so sure their local hospital can safely handle a patient.

Number of Ebola cases nears 10,000

5 hours ago

The number of people with Ebola is set to hit 10,000 in West Africa, the World Health Organization said, as the scramble to find a cure gathered pace.

'Breath test' shows promise for diagnosing fungal pneumonia

6 hours ago

Many different microbes can cause pneumonia, and treatment may be delayed or off target if doctors cannot tell which bug is the culprit. A novel approach—analyzing a patient's breath for key chemical compounds made by the ...

User comments