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评估蜱传疾病风险与监测:迈向诊断定位与预测的多模式方法

Assessing Tick-Borne Disease Risk and Surveillance: Toward a Multi-Modal Approach to Diagnostic Positioning and Prediction.

作者信息

Brooks Chris, McNeely Connie L, Maxwell Sarah P, Thomas Kevin C

机构信息

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

Center for Science, Technology, and Innovation Policy, George Mason University, Fairfax, VA 22030, USA.

出版信息

Microorganisms. 2022 Apr 18;10(4):832. doi: 10.3390/microorganisms10040832.

Abstract

The true extent of tick-borne disease (TBD) incidence and risk among humans is largely unknown, posing significant public health challenges. This study offers an exploratory analysis of a multimodal dataset and is part of a larger ongoing project to determine if entomological data, canine serological reports, self-reported human tick bite encounters (TBEs), and/or associated TBD diagnoses can serve as proxies for human disease risk. Focusing on the United States (U.S.), it characterizes self-reported TBD diagnoses (specifically, anaplasmosis, ehrlichiosis, and Lyme disease), co-infections, and their frequency and distribution across U.S. counties in relation to the presence of other factors related to TBD risk. Survey data was used to construct a list of TBEs localizable to individual U.S. counties. National data regarding these counties—namely the presence of official Lyme Disease (LD) case reports from the Centers for Disease Control and Prevention, as well as the tick vectors I. scapularis and I. pacificus within a given county—were then linked with survey-reported TBEs, tabulated by diagnosis (including co-infections), to determine the distribution of county-level endpoints across diagnostic categories. In addition, data on the presence of positive serological diagnostic tests conducted in canines were considered due to their potential utility as a proxy for TBD and TBE risk. The final dataset contained 249 TBEs localized to a total of 144 counties across 30 states. Diagnostic categories included respondents with LD (n = 70) and those with anaplasmosis and ehrlichiosis diagnoses and co-infections (n < 20 per diagnostic category). TBEs also were indicated by respondents who did not report TBD diagnoses, with some indicating uncertainty. The distribution of respondent-reported TBEs varied between canine TBDs, with LD-positive respondents reporting noticeably larger proportions of TBEs in counties with canine LD and smaller proportions in counties with canine anaplasmosis, compared to respondents without an LD diagnosis; a notional logistic regression suggests these differences may be significant (canine LD: Odds Ratio [OR] = 6.04, p = 0.026) (canine anaplasmosis: OR = 0.50, p = 0.095). These results suggest that certain widely available diagnostic TBD data in animals (in this case, domesticated dogs) may be sensitive to differences in human TBD risk factors and thus may have utility as proxies in future research. In the absence of an available standardized, unified, and national TBD database, such proxies, along with relevant surveys and reports, may provide a much-needed working solution for scientists and clinicians studying TBDs.

摘要

蜱传疾病(TBD)在人类中的实际发病率和风险程度很大程度上尚不清楚,这带来了重大的公共卫生挑战。本研究对一个多模态数据集进行了探索性分析,是一个正在进行的更大项目的一部分,该项目旨在确定昆虫学数据、犬类血清学报告、自我报告的人类蜱叮咬经历(TBE)和/或相关的TBD诊断是否可以作为人类疾病风险的替代指标。该研究聚焦于美国,描述了自我报告的TBD诊断(具体为无形体病、埃立克体病和莱姆病)、合并感染及其在美国各县的频率和分布,以及与TBD风险相关的其他因素。调查数据被用于构建一份可定位到美国各县的TBE清单。然后,将这些县的国家数据——即疾病控制与预防中心的官方莱姆病(LD)病例报告,以及特定县内的蜱传播媒介肩突硬蜱和太平洋硬蜱——与调查中报告的TBE相联系,并按诊断(包括合并感染)进行列表,以确定县级终点在各诊断类别中的分布。此外,考虑了犬类血清学诊断检测呈阳性的数据,因为其有可能作为TBD和TBE风险的替代指标。最终数据集包含249次TBE,涉及30个州的144个县。诊断类别包括患有LD的受访者(n = 70)以及患有无形体病、埃立克体病诊断和合并感染的受访者(每个诊断类别n < 20)。未报告TBD诊断的受访者也指出了TBE,有些表示不确定。受访者报告的TBE分布在犬类TBD之间有所不同,与未诊断为LD的受访者相比,LD呈阳性的受访者报告在有犬类LD的县中TBE的比例明显更高,而在有犬类无形体病的县中比例更低;一项名义逻辑回归表明这些差异可能具有显著性(犬类LD:优势比[OR] = 6.04,p = 0.026)(犬类无形体病:OR = 0.50,p = 0.095)。这些结果表明,动物(在本案例中为家养犬)中某些广泛可用的诊断TBD数据可能对人类TBD风险因素的差异敏感,因此在未来研究中可能作为替代指标有用。在缺乏可用的标准化、统一的国家TBD数据库的情况下,这些替代指标以及相关的调查和报告,可能为研究TBD的科学家和临床医生提供急需的可行解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9861/9032041/8d5c16f361bb/microorganisms-10-00832-g001.jpg

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