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The ecology of Lyme disease: Long-term data, surprises, and a synthesis.

| Source: Proceedings of the National Academy of Sciences of the United States of America

Risk of human exposure to Lyme disease and other tick-borne zoonoses is affected by interactions between ticks, pathogens, vertebrate hosts for ticks and pathogens, and abiotic conditions. Inherent complexities in these ecological systems present challenges to the development of a predictive understanding useful for reducing exposure risk. Here we evaluate a conceptual model of the Lyme disease system using long-term monitoring (>30 y) at sites within an endemic region of New York State, Unit

Risk of human exposure to Lyme disease and other tick-borne zoonoses is affected by interactions between ticks, pathogens, vertebrate hosts for ticks and pathogens, and abiotic conditions. Inherent complexities in these ecological systems present challenges to the development of a predictive understanding useful for reducing exposure risk. Here we evaluate a conceptual model of the Lyme disease system using long-term monitoring (>30 y) at sites within an endemic region of New York State, United States. Contrary to conventional wisdom, we found that the abundance of nymphal black-legged ticks-a key risk factor for humans-was not correlated with the abundance of white-tailed deer, the prior abundance of larval ticks, or seasonal temperature extremes. Instead, the abundance of nymphal ticks was correlated with prior abundance of white-footed mice, which in turn was driven by production of acorns by red oak trees. Infection prevalence with zoonotic pathogens at our relatively intact forest sites was not associated with the abundance of white-footed mice, a species known to transmit infection with high efficiency, but instead appeared to arise from the distribution of larval ticks across the entire community of larval hosts. High densities of mice strongly reduced the tick burdens on individual mice and chipmunks, suggesting intraguild competition for parasites. Lyme disease risk arises from the dynamics of the ecological community, rather than from the dynamics of any single population of hosts or from extreme seasonal weather. These dynamics are complex but predictable, such that understanding them can facilitate improvements in management and education aimed at protecting public health.

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