Sharareh Nasser, Behler Rachael P, Roome Amanda B, Shepherd Julian, Garruto Ralph M, Sabounchi Nasim S
Department of Population Health Sciences, University of Utah, Salt Lake City, UT 84108, USA.
Department of Chemistry, the State University of New York at Binghamton, Vestal, NY 13902, USA.
Healthcare (Basel). 2019 Apr 30;7(2):66. doi: 10.3390/healthcare7020066.
Lyme disease (LD) cases have been on the rise throughout the United States, costing the healthcare system up to $1.3 billion per year, and making LD one of the greatest threats to public health. Factors influencing the number of LD cases range from environmental to system-level variables, but little is known about the influence of vegetation (canopy, understory, and ground cover) and human behavioral risk on LD cases and exposure to infected ticks. We determined the influence of various risk factors on the risk of exposure to infected ticks on 22 different walkways using multinomial logistic regression. The model classifies the walkways into high-risk and low-risk categories with 90% accuracy, in which the understory, human risk, and number of rodents are significant indicators. These factors should be managed to control the risk of transmission of LD to humans.
莱姆病（LD）病例在美国各地呈上升趋势，每年给医疗系统造成高达13亿美元的损失，使莱姆病成为对公众健康的最大威胁之一。影响莱姆病病例数量的因素从环境变量到系统层面的变量不等，但对于植被（树冠层、林下植被和地被植物）以及人类行为风险对莱姆病病例和接触感染蜱虫的影响知之甚少。我们使用多项逻辑回归确定了22条不同人行道上各种风险因素对接触感染蜱虫风险的影响。该模型以90%的准确率将人行道分为高风险和低风险类别，其中林下植被、人类风险和啮齿动物数量是重要指标。应管理这些因素以控制莱姆病传播给人类的风险。
