Project Type: Core Prevention/Intervention Feasibility
Project Description: West Nile Virus (WNV) represents an emerging infectious disease in the United States and has the potential to impact the entire country. The disease has already had severe impacts on birds and other wildlife as it has moved westward from its point of introduction in New York. Because WNV is apparently carried by migrating birds, there are growing concerns over its impact on wildlife populations and the ripple effects on recreational activities like camping, fishing, and hunting.
Outbreaks of the virus in temperate regions generally occur during late summer or early fall, coinciding with the arrival of large concentrations of migratory birds (and mosquitoes); these outbreaks often occur among humans living in or near wetlands where high concentrations of birds come into contact with large numbers of ornithophilic mosquitoes (primarily Culex sp.)
Fears of a West Nile Virus ‘epidemic’ has frightened people into staying indoors or using copious quantities of mosquito repellant when they venture outside. As pesticides are applied to kill a particular target insect, many other non-target insects and other wildlife are exposed to chemicals in the process. Aggressive spraying campaigns raise important health issues for humans and wildlife.
Development of a system for predicting, monitoring, and responding to outbreaks of mosquito and tick vectored diseases is a critical need for community well-being including; public health and water management, disaster management, and agricultural competitiveness. Creation of a geospatially-based dynamic monitoring and prediction system that is sensitive to changing environmental, social, and political variables is the ultimate goal of this project. A coordinated team effort is needed among organizations and agencies that share data and/or are end users of the system. Robust ‘Regression-tree’ modeling techniques will be used that optimize the input of continuous and categorical variables. Interpretability of models is an advantage over ‘Neural Network’ modeling techniques.
Annual Report 2004
Presentation: Avian GIS Models Signal Human Risk for West Nile Virus in Mississippi
Presentation: Geospatial Technologies for Health (West Nile Virus)
Presentation: GIS as an Analytical Tool to Assess the Significance of Environmental Variables for 2002-2003 WNV Human Occurrences
Presentation: 2004 National Symposium on Agricultural Health and Safety