Laura E Jackson1, Elizabeth D Hilborn, James C Thomas. 1. National Health and Environmental Effects Research Laboratory, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA. jackson.laura@epa.gov
Abstract
BACKGROUND: Incidence of Lyme disease in the US continues to grow. Low-density development is also increasing in endemic regions, raising questions about the relationship between development pattern and disease. This study sought to model Lyme disease incidence rate using quantitative, practical metrics of regional landscape pattern. The objective was to progress towards the development of design guidelines that may help minimize known threats to human and environmental health. METHODS: Ecological analysis was used to accommodate the integral landscape variables under study. Case data derived from passive surveillance reports across 12 counties in the US state of Maryland during 1996-2000; 2,137 cases were spatially referenced to residential addresses. Major roads were used to delineate 514 landscape analysis units from 0.002 to 580 km(2). RESULTS: The parameter that explained the most variation in incidence rate was the percentage of land-cover edge represented by the adjacency of forest and herbaceous cover [R(2) = 0.75; rate ratio = 1.34 (1.26-1.43); P < 0.0001]. Also highly significant was the percentage of the landscape in forest cover (cumulative R(2) = 0.82), which exhibited a quadratic relationship with incidence rate. Modelled relationships applied throughout the range of landscape sizes. CONCLUSIONS: Results begin to provide quantitative landscape design parameters for reducing casual peridomestic contact with tick and host habitat. The final model suggests that clustered forest and herbaceous cover, as opposed to high forest-herbaceous interspersion, would minimize Lyme disease risk in low-density residential areas. Higher-density development that precludes a large percentage of forest-herbaceous edge would also limit exposure.
BACKGROUND: Incidence of Lyme disease in the US continues to grow. Low-density development is also increasing in endemic regions, raising questions about the relationship between development pattern and disease. This study sought to model Lyme disease incidence rate using quantitative, practical metrics of regional landscape pattern. The objective was to progress towards the development of design guidelines that may help minimize known threats to human and environmental health. METHODS: Ecological analysis was used to accommodate the integral landscape variables under study. Case data derived from passive surveillance reports across 12 counties in the US state of Maryland during 1996-2000; 2,137 cases were spatially referenced to residential addresses. Major roads were used to delineate 514 landscape analysis units from 0.002 to 580 km(2). RESULTS: The parameter that explained the most variation in incidence rate was the percentage of land-cover edge represented by the adjacency of forest and herbaceous cover [R(2) = 0.75; rate ratio = 1.34 (1.26-1.43); P < 0.0001]. Also highly significant was the percentage of the landscape in forest cover (cumulative R(2) = 0.82), which exhibited a quadratic relationship with incidence rate. Modelled relationships applied throughout the range of landscape sizes. CONCLUSIONS: Results begin to provide quantitative landscape design parameters for reducing casual peridomestic contact with tick and host habitat. The final model suggests that clustered forest and herbaceous cover, as opposed to high forest-herbaceous interspersion, would minimize Lyme disease risk in low-density residential areas. Higher-density development that precludes a large percentage of forest-herbaceous edge would also limit exposure.
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