Lyme disease is a tick-borne zoonotic disease endemic to the United States, Europe, and Asia. The causative agent in the United States, Borrelia burgdorferi, is a spirochete that infects a wide range of animals and is transmitted to humans in the eastern and central U.S. by the deer tick, Ixodes scapularis. Disease incidence in humans is highly seasonal, in large part due to the development cycle and activity patterns of I. scapularis. The majority of human infections are transmitted by nymphal ticks, which seek a host in late spring and early summer. Because tick development and host seeking activity are sensitive to environmental conditions, the timing of the onset and peak of seasonal transmission, as well as the duration of the transmission season, may depend on annual variability in climatic variables. We examined the association between climate records and a 16 year time series of human incidence in 12 U.S. states in order to identify which climate variables are related with Lyme disease seasonality. We also developed a population model for I. scapularis to determine whether variability in Lyme disease incidence could be explained by seasonal patterns of tick abundance and activity.
Results/Conclusions
The timing of the beginning and peak of the Lyme disease transmission season varies significantly among the 12 states where Lyme disease is endemic . The timing of seasonal onset is positively associated with the cumulative growing degree days (GDD) through the first 20 weeks of the year, and negatively associated with the mean April saturation deficit. The duration of the Lyme disease season did not vary between states. The timing of seasonality within states was also associated with GDD, but the relationship was not as strong as that observed among states. In the states with the most variability in seasonality, the onset and peak of the Lyme disease season was also associated with either the saturation deficit or amount of precipitation in early spring. These results suggest that meteorological patterns in the winter and early spring could be used to provide an advanced warning of the timing of the seasonal onset of Lyme disease in the most variable states. Simulations of I. scapularis population dynamics indicate that seasonal variability in Lyme occurrence is primarily associated with the timing of nymphal development, and secondarily with the effect of climate on the host seeking activities of nymphs following emergence.