Department of Plant Sciences and Entomology, University of Rhode Island, Kingston, RI.
URI TickEncounter Resource Center, University of Rhode Island, Kingston, RI.
J Med Entomol. 2021 Mar 12;58(2):837-846. doi: 10.1093/jme/tjaa196.
Tick identification is critical for assessing disease risk from a tick bite and for determining requisite treatment. Data from the University of Rhode Island's TickEncounter Resource Center's photo-based surveillance system, TickSpotters, indicate that users incorrectly identified their submitted specimen 83% of the time. Of the top four most commonly submitted tick species, western blacklegged ticks (Ixodes pacificus Cooley & Kohls [Ixodida: Ixodidae]) had the largest proportion of unidentified or misidentified submissions (87.7% incorrectly identified to species), followed by lone star ticks (Amblyomma americanum Linneaus [Ixodida: Ixodidae]; 86.8% incorrect), American dog ticks (Dermacentor variabilis Say [Ixodida: Ixodidae]; 80.7% incorrect), and blacklegged ticks (Ixodes scapularis Say [Ixodida: Ixodidae]; 77.1% incorrect). More than one quarter of participants (26.3%) submitted photographs of ticks that had been feeding for at least 2.5 d, suggesting heightened risk. Logistic regression generalized linear models suggested that participants were significantly more likely to misidentify nymph-stage ticks than adult ticks (odds ratio [OR] = 0.40, 95% confidence interval [CI]: 0.23, 0.68, P < 0.001). Ticks reported on pets were more likely to be identified correctly than those found on humans (OR = 1.07, 95% CI: 1.01-2.04, P < 0.001), and ticks feeding for 2.5 d or longer were more likely to be misidentified than those having fed for one day or less (OR = 0.43, 95% CI: 0.29-0.65, P < 0.001). State and region of residence and season of submission did not contribute significantly to the optimal model. These findings provide targets for future educational efforts and underscore the value of photograph-based tick surveillance to elucidate these knowledge gaps.
蜱虫鉴定对于评估蜱虫叮咬的疾病风险和确定必要的治疗至关重要。罗德岛大学蜱虫监测中心基于照片的监测系统“蜱虫发现者”(TickSpotters)的数据显示,用户对提交的样本识别错误的比例高达 83%。在提交的四种最常见的蜱虫中,西部黑腿蜱(Ixodes pacificus Cooley & Kohls [Ixodida: Ixodidae])的鉴定错误率最高(87.7%),其次是孤星蜱(Amblyomma americanum Linneaus [Ixodida: Ixodidae];86.8%错误),美洲犬蜱(Dermacentor variabilis Say [Ixodida: Ixodidae];80.7%错误)和鹿革蜱(Ixodes scapularis Say [Ixodida: Ixodidae];77.1%错误)。超过四分之一的参与者(26.3%)提交了至少已吸食 2.5 天的蜱虫照片,表明风险较高。逻辑回归广义线性模型表明,参与者识别若虫期蜱虫的错误率显著高于成蜱(比值比[OR] = 0.40,95%置信区间[CI]:0.23,0.68,P < 0.001)。与在人体上发现的蜱虫相比,在宠物身上报告的蜱虫更有可能被正确识别(OR = 1.07,95% CI:1.01-2.04,P < 0.001),而吸食 2.5 天或更长时间的蜱虫更有可能被错误识别,而吸食一天或更短时间的蜱虫则不太可能被错误识别(OR = 0.43,95% CI:0.29-0.65,P < 0.001)。居住州和地区以及提交季节对最优模型没有显著贡献。这些发现为未来的教育工作提供了目标,并强调了基于照片的蜱虫监测在阐明这些知识差距方面的价值。