公民科学为美国东北部的人类蜱虫暴露提供信息。

IF 3 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
W Tanner Porter, Peter J Motyka, Julie Wachara, Zachary A Barrand, Zahraa Hmood, Marya McLaughlin, Kelsey Pemberton, Nathan C Nieto
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引用次数: 0

摘要

背景:蜱传疾病是病原体扩散到人类的结果。传统上,文献主要关注蜱传疾病病原体和蜱在其系统循环中的特征。在这一系统中,尤其是在美国东北部,有关人类与蜱虫接触的研究数量有限。在评估蜱传疾病风险时,人与蜱虫的相互作用是必须考虑的因素,因为蜱虫叮咬是发生外溢的必要条件:方法:公民科学家通过一项免费的全国性计划从美国东北部收集蜱虫。提交的蜱虫均经过物种、阶段和性别鉴定。对黑脚蜱(Ixodes scapularis)进行了检测,以确定其中是否存在普通鲍曼不动杆菌(S.L.)和硬蜱复发热鲍曼不动杆菌。公民科学家记录了蜱虫暴露的季节性和暴露期间的公民科学活动。利用公民科学提交的蜱虫报告、州和县人口作为预测变量,拟合了一个负二项模型来预测2016年县级疾控中心莱姆病病例:美国东北部共提交了 3740 份报告,其中包括 4261 只蜱虫,据报告这些蜱虫寄生在人类身上。在提交的三种蜱虫中,黑腿蜱最常见,其次是美洲犬蜱和孤星蜱。提交的蜱虫数量在 5 月份达到高峰,大部分蜱虫都是在日常活动中被感染的。黑腿蜱中最常见的病原体是伯氏原蜱,其次是硬蜱复发性热波氏杆菌。负二项模型在新英格兰各州表现最佳,其次是中大西洋各州:结论:公民科学为描述人类蜱虫暴露的季节性和特征提供了一种低成本且有效的方法。在美国东北部,日常活动被认为是蜱虫接触的一个主要机制,这支持了蜱虫传播疾病中近家庭接触的作用。公民科学为广泛的病原体和蜱虫监测提供了一种方法,这种方法与人类疾病高度相关,可用于推断蜱虫传播疾病的流行病学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Citizen science informs human-tick exposure in the Northeastern United States.

Citizen science informs human-tick exposure in the Northeastern United States.

Citizen science informs human-tick exposure in the Northeastern United States.

Citizen science informs human-tick exposure in the Northeastern United States.

Background: Tick-borne disease is the result of spillover of pathogens into the human population. Traditionally, literature has focused on characterization of tick-borne disease pathogens and ticks in their sylvatic cycles. A limited amount of research has focused on human-tick exposure in this system, especially in the Northeastern United States. Human-tick interactions are crucial to consider when assessing the risk of tick-borne disease since a tick bite is required for spillover to occur.

Methods: Citizen scientists collected ticks from the Northeastern US through a free nationwide program. Submitted ticks were identified to species, stage, and sex. Blacklegged ticks, Ixodes scapularis, were tested for the presence of Borrelia burgdorferi sensu lato (s.l.) and hard-tick relapsing fever Borrelia. Seasonality of exposure and the citizen science activity during tick exposure was recorded by the citizen scientist. A negative binomial model was fit to predict county level CDC Lyme disease cases in 2016 using citizen science Ixodes scapularis submissions, state, and county population as predictor variables.

Results: A total of 3740 submissions, comprising 4261 ticks, were submitted from the Northeastern US and were reported to be parasitizing humans. Of the three species submitted, blacklegged ticks were the most prevalent followed by American dog ticks and lone star ticks. Submissions peaked in May with the majority of exposure occurring during every-day activities. The most common pathogen in blacklegged ticks was B. burgdorferi s.l. followed by hard-tick relapsing fever Borrelia. Negative binomial model performance was best in New England states followed by Middle Atlantic states.

Conclusions: Citizen science provides a low-cost and effective methodology for describing the seasonality and characteristics of human-tick exposure. In the Northeastern US, everyday activities were identified as a major mechanism for tick exposure, supporting the role of peri-domestic exposure in tick-borne disease. Citizen science provides a method for broad pathogen and tick surveillance, which is highly related to human disease, allowing for inferences to be made about the epidemiology of tick-borne disease.

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来源期刊
International Journal of Health Geographics
International Journal of Health Geographics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
10.20
自引率
2.00%
发文量
17
审稿时长
12 weeks
期刊介绍: A leader among the field, International Journal of Health Geographics is an interdisciplinary, open access journal publishing internationally significant studies of geospatial information systems and science applications in health and healthcare. With an exceptional author satisfaction rate and a quick time to first decision, the journal caters to readers across an array of healthcare disciplines globally. International Journal of Health Geographics welcomes novel studies in the health and healthcare context spanning from spatial data infrastructure and Web geospatial interoperability research, to research into real-time Geographic Information Systems (GIS)-enabled surveillance services, remote sensing applications, spatial epidemiology, spatio-temporal statistics, internet GIS and cyberspace mapping, participatory GIS and citizen sensing, geospatial big data, healthy smart cities and regions, and geospatial Internet of Things and blockchain.
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