Key Investigator: Sheri W. Dister
Lyme disease is currently the most commonly reported vector-borne disease in the United States. This disease, which can cause serious health problems if left untreated, is transmitted to humans by the bite of a deer tick that is infected with the disease-causing bacteria. Lyme disease transmission risk generally depends on the spatial coincidence of ticks, their natural hosts (such as deer, small mammals, and birds), the Lyme disease bacteria, and humans. The vector, animal host, and human components of the ecology of Lyme disease are all associated with elements of the landscape. Therefore, the relative risk of Lyme disease transmission can be characterized by the structure and composition of the landscape within a given area. In this study, remote sensing (RS) and geographic information system (GIS) technologies provided an efficient means to characterize and model the relationships between landscape elements that contribute to Lyme disease transmission risk in Westchester County, New York.
Ames scientists used Landsat Thematic Mapper (TM) data to generate a map of landscape elements in Westchester County, emphasizing vegetation types associated with residential areas and habitat for ticks and deer (Map A) . A GIS-based analysis of the TM map by municipality demonstrated that urban areas (shown in grey), vegetated residential areas (red), and woods (green) were the major landscape elements comprising vegetation change within the county from south to north. Data acquired by the New York Medical College showed that the percentage of dogs infected with Lyme disease increased along this urban-to-rural gradient. GIS functions were then used to group residential areas based on their proximity to woods and their relative amount of vegetative cover (Map B) . A highly significant correlation was found between the canine data and the proportion of vegetated residential area adjacent to woods (shown in red). (Blue indicates vegetated residential areas not adjacent to woods.) Note that the numbers, which represent the percentage of dogs that tested positive for Lyme disease by municipality, tend to be higher in municipalities with higher proportions of residential/wood edges [red]. This finding suggests that a RS/GIS technique, which identifies the spatial distribution of these landscape patterns, can help generate predictions of Lyme disease risk within areas of the Northeast that are similar to Westchester County.
COLLABORATORS: New York Medical College; Westchester County Health Department
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