PDF(Sci-hub)
Abstract：
Baylisascaris procyonis, the roundworm of raccoons (Procyon lotor), is an emerging helminthic zoonosis in North America. Since the larval form is capable of causing neurological disease in more than 150 species of birds and mammals including humans, understanding factors that influence carriage of the parasite by raccoons is important for mitigating risk. This review examines the current literature to identify major demographic and environmental risk factors associated with B. procyonis carriage in wild raccoons. Raccoon age and season of sample collection were most commonly identified as risk factors, with increased prevalence found in juvenile animals and when sample collection occurred in the fall. Human urbanization and agricultural land use were also observed as potential risk factors; however, there are inconsistencies in the direction of influence these risk factors have on the prevalence of infection. Further investigation into the role of environmental risk factors is required to better understand how human activities influence parasite carriage in raccoons. Additionally, future research using multivariable statistical models guided by epidemiological principles to control for confounding variables and identify interaction effects will help clarify the effect of these demographic and environmental factors. Developing a better understanding of the primary risk factors for parasite carriage in raccoons will help identify areas of higher risk for environmental contamination and will aid in the development and refinement of education and management programs to reduce the risk of human exposure.
摘要：
BaylisascarisProcyonis,浣熊的蛔虫（Procyonlotor），是北美新兴的蠕虫动物共患病。由于幼虫形式能够在包括人类在内的150多种鸟类和哺乳动物中引起神经系统疾病，了解影响浣熊携带寄生虫的因素对于降低风险很重要。这篇综述研究了当前的文献，以确定与野生浣熊的B.procyonis运输相关的主要人口和环境风险因素。浣熊的年龄和样本收集的季节是最常见的风险因素，随着在幼年动物中发现的患病率增加，以及在秋季进行样本收集时。人类城市化和农业土地利用也被认为是潜在的风险因素；然而，这些危险因素对感染患病率的影响方向不一致。需要进一步调查环境风险因素的作用，以更好地了解人类活动如何影响浣熊的寄生虫运输。此外,未来的研究使用流行病学原理指导的多变量统计模型来控制混杂变量并确定相互作用效应,这将有助于阐明这些人口统计学和环境因素的影响.更好地了解浣熊携带寄生虫的主要危险因素将有助于确定环境污染风险较高的领域，并有助于制定和完善教育和管理计划，以降低人类暴露的风险。
