16 February 2013

Studying Current 21st Century Patterns of a Spreading Pandemic

World map shows flight routes from the 40 largest U.S. airports.
Image: Christos Nicolaides, Juanes Research Group

Northwestern University developed a computational model, based on transportation data, that determines its source and how quickly a pandemic will spread to a specific location.

A pandemic refers to an epidemic of infectious disease that has spread across a large area or even in global proportions. It occurs when a strain of a virus appears that causes a readily transmissible disease for which most have no immunity. Influenza pandemics are the most common and occurs with little or no warning and infects a large area of population in multiple waves.

In 1918, The Spanish Flu Pandemic infected 500 million worldwide and killed 20 to 30 million. At the time, the death toll equates to about one to three percent of the world's population, making it one of the deadliest natural disasters in human history. The most recent pandemic was the 2009 H1N1 flu pandemic that killed about 300,000 people worldwide.

Recently, scientists are worried about the H5N1 virus, also known as the avian flu virus. Currently it only affects birds but studies have surfaced showing how this virus can be modified to infect mammals. They believe that if this virus carries over to humans, it may cause a pandemic that will overshadow the disaster brought about by the Spanish Flu Pandemic.

Scientists are studying how pandemics can spread worldwide and how this can be contained in the fastest and most effective way. With the advent of air travel and how fast one can travel from one point in the world to another, the dynamics of a spreading disease has changed from how it was centuries ago.

21st Century Patterns of a Spreading Pandemic

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.

Video: The role of U.S. airports in disease epidemics

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.

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 outbreak 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.


Northwestern University
American Association for the Advancement of Science (AAAS)
MIT News: Airports Major Influence In Spreading Disease and Cause A Pandemic
H5N1 Virus Controversy: Avoid a Pandemic or a Terrorist Attack?
Creating Biological Defense Against Bioterrorism
AAAS News: Letter on Resuming Avian Flu Transmission Research
U.S. National Science Advisory Board for Biosecurity Restricts Publication of H5N1 Virus Study