Abstract

ABSTRACTAim Ixodes scapularis is the most important vector of human tick‐borne pathogens in the United States, which include the agents of Lyme disease, human babesiosis and human anaplasmosis, among others. The density of host‐seeking I. scapularis nymphs is an important component of human risk for acquiring Borrelia burgdorferi, the aetiological agent of Lyme disease. In this study we used climate and field sampling data to generate a predictive map of the density of host‐seeking I. scapularis nymphs that can be used by the public, physicians and public health agencies to assist with the diagnosis and reporting of disease, and to better target disease prevention and control efforts.Location Eastern United States of America.Methods We sampled host‐seeking I. scapularis nymphs in 304 locations uniformly distributed east of the 100th meridian between 2004 and 2006. Between May and September, 1000 m2 were drag sampled three to six times per site. We developed a zero‐inflated negative binomial model to predict the density of host‐seeking I. scapularis nymphs based on altitude, interpolated weather station and remotely sensed data.Results Variables that had the strongest relationship with nymphal density were altitude, monthly mean vapour pressure deficit and spatial autocorrelation. Forest fragmentation and soil texture were not predictive. The best‐fit model identified two main foci – the north‐east and upper Midwest – and predicted the presence and absence of I. scapularis nymphs with 82% accuracy, with 89% sensitivity and 82% specificity. Areas of concordance and discordance with previous studies were discussed. Areas with high predicted but low observed densities of host‐seeking nymphs were identified as potential expansion fronts.Main conclusions This model is unique in its extensive and unbiased field sampling effort, allowing for an accurate delineation of the density of host‐seeking I. scapularis nymphs, an important component of human risk of infection for B. burgdorferi and other I. scapularis‐borne pathogens.

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