Ecology-based Risk Assessment and Early Warning of Highly Pathogenic Avian Influenza in Asia

Xiangming Xiao¹, Marius Gilbert², Jan Slingenbergh³, Fumin Lei⁴, Zhongwei Guo⁴ and Bobby Braswell<sup>1


1</sup>Institute for the Studies of Earth, Oceans and Space, University of New Hampshire, Durham, NH 03824, USA
²Université Libre de Bruxelles, Brussels, Belgium;
³United Nations Food and Agriculture Organization (FAO), Rome, Italy
⁴Institue of Zoology, Chinese Academy of Sciences, Beijing, China

Since late 2003 several East and Southeast Asia countries have experienced outbreaks of Highly Pathogenic Avian Influenza (HPAI), or bird flu. HPAI outbreaks in Southeast Asia have resulted in the death of 86 people (as of 2nd February 2006) and nearly 140 million domestic poultry. In late 2005 and early 2006, HPAI outbreaks have been reported in many more countries, including Russia, Turkey, Iraq and recently Nigeria. Widespread circulation of the avian flu virus also increases the chances of mutation into a form that could pass from human to human, which could result in a new human flu pandemic of unknown magnitude. At present, the efforts in risk assessment of HPAI and response strategies are to large degree hampered by (i) the lack of comprehensive understanding of the ecology of avian influenza, particularly in relation to agricultural systems, poultry, wild birds, biophysical and biochemical environments, and (ii) the facts that geospatial datasets used for risk assessment and reduction strategies are often out-of-date and at coarse spatial (e.g., national or provincial) and temporal (e.g., at annual) resolutions.

Here we introduce a new interdisciplinary and international project that combines epidemiology, ornithology, agriculture and environmental remote sensing. This 4-year project (2006 – 2010) is funded by the National Institutes of Health (NIH) and National Science Foundation (NSF), as part of the NIH/NSF Ecology of Infectious Diseases Program.  Its overall goal is threefold: (a) to better understand the ecology of HPAI in Asia; (b) to develop a data-model integration system that could identify “hot spots” (location-varying risk) and “hot times” (time-varying risk) of HPAI in Asia, and (c) to provide near-real-time ecology-based risk assessment and early warning of HPAI in 2007-2009 for Asia. Specifically, it will (1) provide updated and improved geospatial datasets of HPAI-relevant ecological factors, including migration flyways and timing of wild waterfowls, agricultural systems (cropping intensity, crop calendar, and irrigation), seasonality of wetlands, and biophysical variables (e.g., land surface temperature); (2) quantify the relationships between HPAI and ecological variables; (3) develop a GIS-based epidemiological model, (4) develop an internet-based geospatial web system (primarily through linking Google Earth with research-oriented websites, e.g., http://remotesensing.unh.edu) for distributed mapping and timely distribution of HPAI-relevant information. This project employs remote sensing and GIS/GPS, in-situ observations, epidemiological models, and internet technology.