S&T Snapshots - Infrastructure & Geophysical

All Over the Map

(March 2008) A Washington, D.C., think tank says it has pioneered a way to simulate, through advanced computer technology, the spread of an infectious disease on a national scale using both biological and sociological data.

Information about how the disease is transmitted can be combined with statistics from the census on 300 million–plus Americans in more than 31,000 ZIP codes—all into one image. These data—compiled in compliance with relevant privacy laws—include traits such as age, income, and the proximity of people to others. As a result, homeland security and other policymakers could be able to actually see the overall effect that preventive measures, such as school closings and limited quarantines, could have in reducing illnesses or deaths.

The Large-Scale Agent Model (LSAM) is developed by the Brookings Institution and can be used to plot and plan for insect-borne and sexually transmitted diseases, industrial accidents that can produce harmful chemical plumes, and even trends such as obesity and teenage smoking. Eventually, LSAM will be able to expand to encompass data on schools, workplaces, and every hospital and medical facility in the country. It could even be integrated with travel and sociological data from other countries to predict disease spread and emergency response around the globe.

“We build artificial communities of cyber people who represent the real population,” said Joshua Epstein, the project lead at Brookings. “Basically, we grow large-scale social dynamics of central importance to policy.”

LSAM is a major initiative of the National Center for the Study of Preparedness and Catastrophic Event Response (PACER), a DHS Center of Excellence based at Johns Hopkins University. PACER partners with other schools and organizations such as the American Red Cross to find ways to improve the Nation’s ability to prepare for and respond to high-consequence natural or man-made disasters.

The Brookings model fits into PACER’s focus on surge capacity, which deals with the challenge of accounting for enough medical care in the event of a catastrophe. Epstein and his colleague Jon Parker—who built the computer program for LSAM—will input over the next year information about the location of every staffed hospital bed in the country. Then, they’ll run a simulation that shows where shortages in medical care can be expected if there’s ever an epidemic or disaster.

In the same scenario, public health experts and policymakers would be able to use LSAM to map out and “observe” the effectiveness of vaccine distribution and other measures that could, for example, stop the spread of contagious diseases. These other measures could range from simple health advisories to moratoriums on travel.

Epstein said PACER and Brookings see a host of potential uses for LSAM, which could apply to government agencies in the United States and, eventually, around the world. “We’re trying to have a very big picture of things,” he said, “and so far, we’ve had a lot of success.”