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Spatial analysis of human Lyme disease risk in an endemic county




Kugeler, Kiersten Jenae, author
Peel, Jennifer, advisor
Reif, John, committee member
Eisen, Lars, committee member
Mead, Paul, committee member
Biggerstaff, Brad, committee member

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An understanding of the factors that drive spatial variation in human Lyme disease risk is important for appropriate development and implementation of public health interventions. Yet, these factors are poorly understood. This dissertation utilized fine-scale environmental and human Lyme disease data from a single county to quantify the spatial distribution of human Lyme disease occurring 2001-2011 and to evaluate whether spatial variation in disease risk was explained by several factors, including land use, land cover, deer density, and tick infestation on deer. All studies were conducted with data from Howard County, Maryland. The first project described spatial clustering of human Lyme disease according to residence. When compared to other areas of the County, areas with elevated disease risk were characterized by more low-density development and more red and white oak forest. The second project used multilevel (i.e., mixed effect) models to examine risk factors for human Lyme disease among all homes in Howard County. In this analysis, 8% of all variation in human disease risk was due to the census block group location of households; the remaining variation in human disease risk occurred within census block groups. Most of the variation in risk between census block groups was explained by household-level land use and land cover characteristics and census block group-level differences in forest and socio-demographics, yet some variation in risk between block groups remained unexplained with available covariates. Increased risk of Lyme disease was associated with low- and medium-density residential development, red and white oak forest, increasing proportion of the census block group classified as forest, and residing in a census block group characterized by higher income, home value, and education. The third project evaluated associations between deer density, tick infestation on deer, and human disease risk. Study findings suggested that areas with lower deer density had higher abundance of ticks on deer and higher risk of human Lyme disease. These results suggest that moderate deer reduction in inland areas, as occurs through community deer management programs, may not be a viable Lyme disease prevention measure. This dissertation advances knowledge of the fine-scale epidemiology of human Lyme disease and demonstrates the importance of using human outcome data, in addition to entomologic data, to understand variation in Lyme disease risk. These studies use advanced analytic methods to demonstrate significant sub-county spatial variation in risk of human Lyme disease, validate previously recognized risk factors for human illness, identify novel associations of a specific forest type with human disease, and demonstrate the importance of human behavior in placing humans at risk. Finally, results of this dissertation suggest that additional analyses using multilevel modeling techniques may help to provide insight regarding many remaining questions in the epidemiology of Lyme disease.


2014 Summer.

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