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了解白尾鹿种群密度的栖息地和环境条件以及公共卫生数据,以协助评估人类蜱传疾病风险。

Understanding Habitats and Environmental Conditions of White-Tailed Deer Population Density and Public Health Data to Aid in Assessing Human Tick-Borne Disease Risk.

作者信息

Maxwell Sarah P, Brooks Chris, Kim Pyung, Kim Dohyeong, McNeely Connie L, Thomas Kevin

机构信息

School of Economic, Political & Policy Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.

Laboratory for Human Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA.

出版信息

Microorganisms. 2023 Mar 28;11(4):865. doi: 10.3390/microorganisms11040865.

Abstract

The extent of tick-borne diseases (TBDs) in the United States is largely unknown and underreported. Equitable diagnostic and treatment options may vary by geographic location. Triangulating multi-modal data sources informed by a One Health approach provides robust proxies for human TBD risk. Using data from the Indiana Department of Natural Resources collected from hunters during the white-tailed deer () hunting season and other sources, we employ a mixed-methods approach based on thematic mapping and mixed effects modelling to determine if deer population density aligns with official disease data at the county level from (1) positive canine serological reports for, anaplasmosis, and Lyme Disease (LD); (2) positive human cases of ehrlichiosis, anaplasmosis, LD, and Spotted Fever rickettsioses; and (3) tick infectivity. We propose the need for multimodal data analysis using a variety of potential proxies to better estimate disease risk and inform public health policy and practice. We find similar spatial distributions between deer population density and human and canine TBDs in northeastern and southern Indiana, which are rural and mixed geographic areas. Overall, LD is more prevalent in the northwest, central-western, and southeastern counties, while ehrlichiosis is more common in the southern counties. These findings hold true across humans, canines, and deer.

摘要

美国蜱传疾病(TBDs)的实际情况很大程度上尚不明确且报告不足。公平的诊断和治疗方案可能因地理位置而异。采用“同一健康”方法整合多模态数据源,可为人类TBD风险提供有力的近似指标。利用印第安纳州自然资源部在白尾鹿狩猎季节从猎人处收集的数据以及其他来源的数据,我们采用基于专题制图和混合效应建模的混合方法,以确定鹿的种群密度是否与县级官方疾病数据相符,这些数据包括:(1)犬类无形体病、莱姆病(LD)血清学检测呈阳性的报告;(2)人类埃立克体病、无形体病、LD和斑点热立克次体病的确诊病例;(3)蜱的感染性。我们提出,需要使用各种潜在的近似指标进行多模态数据分析,以更好地估计疾病风险,并为公共卫生政策和实践提供依据。我们发现,在印第安纳州东北部和南部的农村及混合地理区域,鹿的种群密度与人类和犬类的TBDs呈现出相似的空间分布。总体而言,LD在西北部、中西部和东南部各县更为普遍,而埃立克体病在南部各县更为常见。这些发现在人类、犬类和鹿中均成立。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d7c/10146154/d44047a8ea31/microorganisms-11-00865-g001.jpg

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