Satellite Observations Used To Track Avian Flu> Real time maps of "hot spots" and "hot times" for viral transmission

An international, interdisciplinary team of researchers led by professor Xiangming Xiao of the

University

of

New Hampshire

is taking a novel scientific approach in an attempt to understand the ecology of the avian influenza, develop better methods of predicting its spread, and provide an accurate early warning system.

Xiao and colleagues were recently awarded $1.55 million for a four-year project funded by the U.S. National Institutes for Health (NIH) as part of the Ecology of Infectious Diseases (EID) Program jointly sponsored with the U.S. National Science Foundation. The EID program supports research projects that develop quantitative analysis and modeling capacity for better understanding the relationship between man-made environmental change and transmission of infectious agents.

The UNH project will use environmental remote sensing data from Earth observing satellites in combination with research in epidemiology, ornithology, and agriculture to provide a better picture of how the Highly Pathogenic Avian Influenza survives and gets transmitted among poultry and wild birds. The work focuses on

China

, where outbreaks of the virus have been prominent.

"The ecology of the avian influenza involves a complex web of factors, including environmental settings, agricultural practices of rice production and harvesting, poultry production involving huge populations of free-grazing ducks, and the migratory behavior of wild bird populations. Depending on how all of these risk factors intermingle over time, the virus can be spread through the environment by infected wild birds or domestic poultry.

For example, using imagery of varying resolution from different types of satellites, the team can map and track the spatial-temporal dynamics of crop cultivations (when planted, harvested, etc.) and wetlands. Used in conjunction with other geospatial data of environment, bird migration, and poultry production, dynamic maps of "hot spots" and "hot times" for viral transmission can be developed in near-real-time mode and will aid the public, researchers, business, and decision-makers in preparing for a potential pandemic crisis."

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