Hayes Laura E, Scott Jennifer A, Stafford Kirby C
Department of Entomology, The Connecticut Agricultural Experiment Station, 123 Huntington Street, New Haven, CT 06504-1106, United States.
Department of Community Medicine, University of Connecticut Health Center, 263 Farmington Avenue, Farmington, CT 06030-6325, United States.
Ticks Tick Borne Dis. 2015 Apr;6(3):258-66. doi: 10.1016/j.ttbdis.2015.01.006. Epub 2015 Feb 14.
Tick species worldwide are implicated in transmission of pathogens that cause mild to severe diseases in humans and livestock. Although tick population densities are often highly correlated with tick-borne disease rates, we currently know little about which factors underlie annual changes in those tick population densities. We used a 25-year dataset of Ixodes scapularis drag-sampling surveys at two locations in CT, USA, to investigate the relationship between average nymphal density from mid-May to mid-August and monthly, lagged regional weather variables. The dataset was randomly split into two data subsets, one for hypothesis development and one for hypothesis testing. Nymphal density showed the strongest association with the Standardized Precipitation Index for January of the same year that density data were collected in the analysis based on the hypothesis development data subset. This association was positive; nymphal tick density increased with regional winter precipitation. Nymphal density was positively associated with this same weather variable in the hypothesis testing data subset. Weather conditions during the coldest months of the year may serve as a bottleneck to tick populations, thereby functioning as an important correlate of not only annual blacklegged tick nymphal densities the following summer, but also entomological risk associated with tick-borne pathogens transmitted by this species.
全世界的蜱虫种类都与病原体的传播有关,这些病原体可导致人类和牲畜患上从轻度到重度的疾病。尽管蜱虫种群密度通常与蜱传疾病发病率高度相关,但我们目前对导致这些蜱虫种群密度年度变化的因素知之甚少。我们使用了在美国康涅狄格州两个地点进行的为期25年的肩突硬蜱拖网采样调查数据集,来研究5月中旬至8月中旬若虫平均密度与每月滞后的区域天气变量之间的关系。该数据集被随机分为两个数据子集,一个用于假设开发,一个用于假设检验。在基于假设开发数据子集的分析中,若虫密度与收集密度数据的同一年1月的标准化降水指数显示出最强的关联。这种关联是正相关的;若虫蜱密度随区域冬季降水量增加。在假设检验数据子集中,若虫密度与这个相同的天气变量呈正相关。一年中最寒冷月份的天气状况可能成为蜱虫种群的一个瓶颈,因此不仅作为次年夏天黑腿蜱若虫年度密度的一个重要相关因素,而且作为与该物种传播的蜱传病原体相关的昆虫学风险的一个重要相关因素。