Over the past two decades Lyme disease has emerged as the most common vector-borne disease in the United States. It is currently endemic in ~12 states, from Virginia in the South to Maine in the North, and Minnesota and Wisconsin in the West. The majority of cases are believed to be transmitted by nymphal ticks during late spring and early summer months of June, July, and August. Control methods currently focus on the application of synthetic or natural acaracides during periods of peak nymphal activity and raising public awareness for greater caution during periods of high risk. Both methods require knowing when the Lyme disease season starts, peaks and ends, all of which vary on a yearly and regional scale.
A recent study by Moore et al. (2014) analyzed human Lyme disease occurrence in 12 states between 1992 - 2007 relative to local meteorological variables. The focus of the study was to examine statistical relations between meteorology and the timing of the start, peak, and end of the Lyme disease season and the likely duration. Several meteorological variables were considered, including Growth Degree Days (GDD, number of degree days above a threshold temperature), saturation deficit, cumulative precipitation. South, Northeast, Midwest, and Northwest regions of the U.S. were evaluated together and separately to evaluate potential regional correlations.
Combinations of various meteorological variables were examined to determine the best fit with observed timing of Lyme disease cases. The best correlations were found between the beginning of Lyme disease season and cumulative growth degree days (with a threshold temperature of 10ºC), lower saturation deficit, and lower precipitation. It is proposed that warmer temperatures (and fewer heavy rainfall events) promote growth and pursuit of hosts, or “questing” activity, of nymphs, resulting in an earlier start to the disease season. The impact of other factors, such as human activity linked to meteorological parameters (e.g., people spending more time outdoors in response to early Springtime warming, increasing their susceptibility to infection) is also discussed. Regional variations in the Lyme disease season are also found with the disease season starting earlier (and lasting longer) in the South compared to the North. Small correlations with the same meteorological variables are also found with occurrence of the peak season and its duration. No correlation was detected between any of the meteorological variables and the end of the disease season.
Since the best predictor of the start of the season was found to be cumulative meteorological variables, this model cannot be used for forecasting when the disease season starts. But it can potentially be used to predict the timing of the peak, and the likely duration of the disease season. Knowledge of these variables is important so that effective measures can be taken to prevent disease spread and raise timely awareness of precautionary steps that should be taken by the public.
Moore, S.M., R.J. Eisen, A. Monaghan, and P. Mead, 2014: Meteorological influences on the seasonality of Lyme disease in the United States. American Journal of Tropical Medicine and Hygiene, 90, 486-496, DOI: 10.4269/ajtmh.13-0180.