Xue Ling, Scoglio Caterina, McVey D Scott, Boone Rebecca, Cohnstaedt Lee W
1 Kansas State Epicenter, Department of Electrical and Computer Engineering, Kansas State University , Manhattan, Kansas.
2 Center for Grain and Animal Health Research , ARS, USDA, Manhattan, Kansas.
Vector Borne Zoonotic Dis. 2015 Sep;15(9):523-8. doi: 10.1089/vbz.2015.1791. Epub 2015 Sep 8.
Lyme disease has become the most prevalent vector-borne disease in the United States and results in morbidity in humans, especially children. We used historical case distributions to explain vector-borne disease introductions and subsequent geographic expansion in the absence of disease vector data. We used geographic information system analysis of publicly available Connecticut Department of Public Health case data from 1984, 1985, and 1991 to 2012 for the 169 towns in Connecticut to identify the yearly clusters of Lyme disease cases. Our analysis identified the spatial and temporal origins of two separate introductions of Lyme disease into Connecticut and identified the subsequent direction and rate of spread. We defined both epidemic clusters of cases using significant long-term spatial autocorrelation. The incidence-weighted geographic mean analysis indicates a northern trend of geographic expansion for both epidemic clusters. In eastern Connecticut, as the epidemic progressed, the yearly shift in the geographic mean (rate of epidemic expansion) decreased each year until spatial equilibrium was reached in 2007. The equilibrium indicates a transition from epidemic Lyme disease spread to stable endemic transmission, and we associate this with a reduction in incidence. In western Connecticut, the parabolic distribution of the yearly geographic mean indicates that following the establishment of Lyme disease (1988) the epidemic quickly expanded northward and established equilibrium in 2009.
莱姆病已成为美国最普遍的媒介传播疾病，并导致人类发病，尤其是儿童。在缺乏病媒数据的情况下，我们利用历史病例分布来解释媒介传播疾病的传入及随后的地理扩张情况。我们对康涅狄格州公共卫生部公开提供的1984年、1985年以及1991年至2012年期间康涅狄格州169个城镇的病例数据进行了地理信息系统分析，以确定莱姆病病例的年度聚集情况。我们的分析确定了莱姆病两次分别传入康涅狄格州的时空起源，并确定了随后的传播方向和速度。我们利用显著的长期空间自相关定义了两个病例流行聚集区。发病率加权地理均值分析表明，两个流行聚集区的地理扩张均呈向北趋势。在康涅狄格州东部，随着疫情的发展，地理均值的年度变化（疫情扩张速度）逐年下降，直至2007年达到空间平衡。这种平衡表明莱姆病从流行传播向稳定的地方流行转变，我们将此与发病率下降联系起来。在康涅狄格州西部，年度地理均值的抛物线分布表明，在莱姆病确立（1988年）之后，疫情迅速向北扩张，并于2009年达到平衡。
