July 19, 2011 – In an age when the next pandemic could leap continents in the hours it takes for an international flight to take off and land, University of Utah Professor Paul Hu fears the death toll may depend on how fast and efficiently world health officials can respond to an outbreak.

That is why Hu, a faculty scholar at the university’s David Eccles School of Business Department of Operations and Information Systems, is calling for both a more “comprehensive framework” worldwide to discover and monitor disease outbreaks—and a “loose coupling” approach to gathering, interpreting and sharing public health data. In computing and systems design, a loosely coupled system is one where each of its components has little or no knowledge of other separate components.

In the paper, “Managing Emerging Infectious Diseases with Information Systems: Reconceptualizing Outbreak Management through the Lens of Loose Coupling,” Hu and his co-authors studied what was effective – and what was not – in the world’s reaction to the 2003 deadly Severe Acute Respiratory Syndrome (SARS) epidemic in Taiwan. The World Health Organization reports that SARS spread in a matter of weeks from Hong Kong to nearly 40 nations around the world and infected more than 8,400 people. Roughly 11 percent of the victims died from the virus.

“The failure of central (public health) agencies to detect and manage SARS was generally attributed to weak disease surveillance mechanisms,” writes Hu and co-authors Yi-Da, Hsinchun Chen, Susan Brown of the University of Arizona and Chwan-Chuen King of National Taiwan University. Their paper is to be published in the September (2011) issue of Information Systems Research, the journal of the Institute for Operations Research and the Management Sciences. The study goes on to note, “It was believed that if officials had received more information indicating (the outbreak) sooner, important public health decisions could have been made to control the disease faster.”

Prodded by the SARS scare, the researchers say, the U.S. Department of Health and Human Services alone dished out nearly $850 million to improve response in all 50 states. About 30 percent of that money went directly to upgrading information technology to more quickly identify emerging epidemics. However, the devil may indeed be in the details, based on the mountain of new disease-related data health officials must interpret.

“The reality is that public health practitioners experience difficulty in dissecting the meaning behind frequent surveillance alerts and often feel overwhelmed by the volume of the alerts,” the researchers find. That is where adoption of “loose coupling” guidelines for disease data comes in.

Traditionally, Hu and his colleagues say, the response to outbreaks has been highly centralized, with public health agencies gathering, interpreting and then ordering responses to infectious disease reports they deem as significant. However, the system can “break down at several decision points” along the way, slowing—or even temporarily blinding—health agencies’ reactions to the emergence of a new epidemic, the researchers conclude.

While not downplaying the critical importance of a centralized, globally effective response to outbreaks, Hu and his colleagues suggest the traditional system’s inherent rigidity can be tempered by a more open approach – one that encourages local clinicians’ judgments and autonomy. This could potentially counter disease flare-ups while they are still contained within a pocket of community or region.