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两种蜱传疾病在新英格兰地区的入侵:利用人类监测数据捕捉潜在的生态入侵过程。

Invasion of two tick-borne diseases across New England: harnessing human surveillance data to capture underlying ecological invasion processes.

作者信息

Walter Katharine S, Pepin Kim M, Webb Colleen T, Gaff Holly D, Krause Peter J, Pitzer Virginia E, Diuk-Wasser Maria A

机构信息

Department of Epidemiology of Microbial Diseases, Yale School of Public Health, 60 College Street, New Haven, CT 06520, USA

United States Department of Agriculture Animal and Plant Health Inspection Service, National Wildlife Research Center, 4101 LaPorte Avenue, Fort Collins, CO 80521, USA Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA.

出版信息

Proc Biol Sci. 2016 Jun 15;283(1832). doi: 10.1098/rspb.2016.0834.

Abstract

Modelling the spatial spread of vector-borne zoonotic pathogens maintained in enzootic transmission cycles remains a major challenge. The best available spatio-temporal data on pathogen spread often take the form of human disease surveillance data. By applying a classic ecological approach-occupancy modelling-to an epidemiological question of disease spread, we used surveillance data to examine the latent ecological invasion of tick-borne pathogens. Over the last half-century, previously undescribed tick-borne pathogens including the agents of Lyme disease and human babesiosis have rapidly spread across the northeast United States. Despite their epidemiological importance, the mechanisms of tick-borne pathogen invasion and drivers underlying the distinct invasion trajectories of the co-vectored pathogens remain unresolved. Our approach allowed us to estimate the unobserved ecological processes underlying pathogen spread while accounting for imperfect detection of human cases. Our model predicts that tick-borne diseases spread in a diffusion-like manner with occasional long-distance dispersal and that babesiosis spread exhibits strong dependence on Lyme disease.

摘要

对维持在动物流行病传播循环中的媒介传播人畜共患病病原体的空间传播进行建模仍然是一项重大挑战。关于病原体传播的最佳时空数据通常采用人类疾病监测数据的形式。通过将一种经典的生态学方法——占有率建模——应用于疾病传播的流行病学问题,我们利用监测数据来研究蜱传病原体的潜在生态入侵。在过去的半个世纪里,包括莱姆病和人类巴贝斯虫病病原体在内的先前未被描述的蜱传病原体已迅速在美国东北部传播。尽管它们在流行病学上具有重要意义,但蜱传病原体入侵的机制以及共同传播病原体不同入侵轨迹背后的驱动因素仍未得到解决。我们的方法使我们能够估计病原体传播背后未被观察到的生态过程,同时考虑到人类病例检测的不完美性。我们的模型预测,蜱传疾病以类似扩散的方式传播,偶尔会有长距离扩散,并且巴贝斯虫病的传播表现出对莱姆病的强烈依赖性。

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