Government Technology

Engineering An Advanced Pandemic Warning System



Advanced Pandemic Warning System
Advanced Pandemic Warning System

May 12, 2009 By

Researchers are proposing a new system that would warn of an impending pandemic before the first case of disease emerged in a given population by detecting subtle signals in human behavior.

"The goal is a public information and awareness system for pandemics with the same level of credibility, timeliness and visibility as storm-warning icons presented on television screens," said Barrett Caldwell, a Purdue University associate professor of industrial engineering.

The system works by monitoring "event phases" of human behavior leading up to a pandemic, such as an increase in people purchasing flu-related medications or "foraging" on the Internet for certain types of information related to the flu.

Understanding these phases might be a way to overcome a fundamental hurdle in controlling pandemic: Conventional approaches require public-health officials to know when certain events leading to pandemic begin, Caldwell said.

"The problem with this requirement is that by the time you know an event has happened, it's often too late to do much about it," he said.

Caldwell and former Purdue industrial engineering doctoral student Sandra K. Garrett have proposed a new approach to warn the public of an impending pandemic.

"If you can recognize the triggers, the signals suggesting an event is likely to occur, you can start responding to it, gathering resources, preparing and mobilizing people," said Garrett, an assistant professor of industrial engineering at Clemson University. "Our basic research idea could be used for any pandemic, or even other types of disasters."

Garrett and Caldwell detailed the findings in a paper that will be presented June 2 at the Industrial Engineering Research Conference in Miami.

Method Harnesses "Signal Detection"

The paper shows how pre-pandemic events are separated into four categories of "human factors," or social behavior: a period during which it is first possible to detect signals of an emerging pandemic; a time when it is possible to begin early efforts to prevent or mitigate spread; a time when it is critical to implement such measures; and a period when it is time to complete mitigation steps.

The method is an elaboration of "signal-detection theory," conceived decades ago.

"Normally, when researchers study signal detection, they are looking at very rapid changes, like whether a tone changes, whether a light changes color or turns on and off," Caldwell said.

The new approach proposes to make signal detection sensitive to more gradual events that are slower to develop.

"This is important because a pandemic is not a single point in time but a scenario that may take place in several waves over a period of months," he said. "One of the challenges is that the way influenza spreads, you don't know that someone's sick until several days later, and by then they have had the opportunity to infect other people. At that point you have to project backward to see where people have first been sick and where certain flu-related events have happened. You are reactive, rather than proactive."

The researchers envision a system that uses icons similar to those used to alert the public about an impending blizzard, hurricane or tornado. The new approach would enable public health officials to properly manage "event deadlines" or respond to a problem before it's too late.

"For example, by now we have many cases in the United States, so the event deadline for closing travel borders with Mexico has already passed," Caldwell said.

The method also would enable officials to recognize a critical "trigger" that marks when people are prompted to act in certain ways based on a mental preview of what they think may happen soon.

"This trigger could be that something has already happened or


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