Kelsie Cassell1, Paul Gacek2, Joshua L Warren3, Peter A Raymond4, Matthew Cartter2, Daniel M Weinberger1. 1. Departments of Epidemiology of Microbial Diseases, New Haven, Connecticut. 2. Connecticut Department of Public Health, Hartford. 3. Departments of Biostatistics, Yale School of Public Health, New Haven, Connecticut. 4. Yale School of Forestry and Environmental Studies, New Haven, Connecticut.
Abstract
Background: There has been a dramatic increase in the incidence of sporadic legionnaires' disease in Connecticut since 1999, but the exact reasons for this are unknown. Therefore, there is a growing need to understand the drivers of legionnaires' disease in the community. In this study, we explored the relationship between the natural environment and the spatial and temporal distribution of legionellosis cases in Connecticut. Methods: We used spatial models and time series methods to evaluate factors associated with the increase and clustering of legionellosis in Connecticut. Stream flow, proximity to rivers, and residence in regional watersheds were explored as novel predictors of disease, while controlling for testing intensity and correlates of urbanization. Results: In Connecticut, legionellosis incidence exhibited a strong pattern of spatial clustering. Proximity to several rivers and residence in the corresponding watersheds were associated with increased incidence of the disease. Elevated rainfall and stream flow rate were associated with increases in incidence 2 weeks later. Conclusions: We identified a novel relationship between the natural aquatic environment and the spatial distribution of sporadic cases of legionellosis. These results suggest that natural environmental reservoirs may have a greater influence on the spatial distribution of sporadic legionellosis cases than previously thought.
Background: There has been a dramatic increase in the incidence of sporadic legionnaires' disease in Connecticut since 1999, but the exact reasons for this are unknown. Therefore, there is a growing need to understand the drivers of legionnaires' disease in the community. In this study, we explored the relationship between the natural environment and the spatial and temporal distribution of legionellosis cases in Connecticut. Methods: We used spatial models and time series methods to evaluate factors associated with the increase and clustering of legionellosis in Connecticut. Stream flow, proximity to rivers, and residence in regional watersheds were explored as novel predictors of disease, while controlling for testing intensity and correlates of urbanization. Results: In Connecticut, legionellosis incidence exhibited a strong pattern of spatial clustering. Proximity to several rivers and residence in the corresponding watersheds were associated with increased incidence of the disease. Elevated rainfall and stream flow rate were associated with increases in incidence 2 weeks later. Conclusions: We identified a novel relationship between the natural aquatic environment and the spatial distribution of sporadic cases of legionellosis. These results suggest that natural environmental reservoirs may have a greater influence on the spatial distribution of sporadic legionellosis cases than previously thought.
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