Evaluation of Critical Spatial Elements for Animal Disease Surveillance in Illinois
College: Veterinary Medicine
Award year: 2006-2007
Disease surveillance has been practiced for many years in the United States, notably for the human diseases the Centers for Disease Control (CDC) deem reportable, the animal diseases of high economic import, and specific diseases, such as types of cancer, that are the responsibility of a particular institution. While systems for human illness are well underway, systems for animals have tended to lag behind. In an era of new, emergent and re-emerging infectious diseases, which are often disease of both animals and people, consistent and unbiased surveillance for animal disease outbreaks is needed for both the maintenance of the economic viability of domestic herds and the protection of human health This project seeks to improve the ability to track and respond to an outbreak of animal diseases and to provide spatially oriented outbreak information to both public and veterinary health decision-makers. It focuses on two spatial aspects of disease surveillance: animal location and mapping interface, which, based on past work, prevent efficient animal disease surveillance. The first area focuses on animal locations, which are usually not completely known. Often animal disease mapping is done without this context. I propose to develop a new method of modeling animal location from incomplete data and then test the degree to which this method of determining animal locations is reflected in the pattern of the expected level of disease in a particular area compared to using more traditional data. Animals in question will include pets, wildlife, and farm animals. Second is the development of an alternative means by which outbreak information are presented to decision makers, especially in terms of maps and supporting tables. Maps are complex entities and the best way to make them available to convey disease patterns and information is not known. Specifically, I will assess empirically an internet based delivery method using Google Earth to provide a spatial context for outbreak results compared to one in which the spatial context is supplied through GIS software similar to the systems described above. These two areas are evaluated using data on past animal disease outbreaks in Illinois to make recommendations to improve the ability to report animal diseases and to identify outbreaks. An emphasis will be placed on visualization and information content for decision makers in public and veterinary health.