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New methodology to predict pandemics
Date:2/14/2013

itial analysis shows a promising advantage to aid in predicting and preventing possible pandemic diseases that can result in devastating losses in life and global economic crises. "This application of network theory is exciting not only because it provides a fast, affordable method for associating undiagnosed outbreaks with a set of most likely known diseases, but perhaps most importantly because it provides a method for researchers to work with public health experts to identify potentially novel pathogen threats, as these agents will not fall into any of the known disease clusters and therefore can be easily identified," said Dr. Tiffany Bogich, Princeton University.

Often, new pandemics start as a few cases of an unknown disease in a remote region of the globe. After a few weeks or months depending on conditions, the disease continues to spread through the rapid movement of global travelers. As with the SARS outbreak, the virus incubated for a few months in China before it spread to Hong Kong, Canada and other points around the world. In 2009, the outbreak of H1N1 'Swine' flu circulated in Mexico for at least a couple of months before it was discovered as a real threat to public health. When Nipah virus caused outbreaks in pigs and farm workers in Malaysia, many health officials thought the disease was symptomatic of Japanese encephalitis. All of these examples illustrate the need to identify highly infectious diseases at the very earliest stage when there are just a few cases allowing public health officials to thwart these new viruses from spreading globally.

"This research may be critical to rapidly deciding which outbreaks are something completely novel and have pandemic potential, rather than a repeat outbreak of a known pathogen. It allows public health agencies to target their resources in the most efficient way, and helps protect us from new emerging diseases, which often erupt in remote corners of the Earth where it is someti
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Contact: Anthony M. Ramos
ramos@ecohealthalliance.org
212-380-4469
EcoHealth Alliance
Source:Eurekalert

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