Guillot Camille, Bouchard Catherine, Buhler Kayla, Dumas Ariane, Milord François, Ripoche Marion, Pelletier Roxane, Leighton Patrick A
Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Departement of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Montreal, QC J2S 2M1, Canada.
Faculty of Medicine and Health Sciences, University of Sherbrooke, Sherbrooke, QC J1H 5N4, Canada.
Pathogens. 2022 May 2;11(5):531. doi: 10.3390/pathogens11050531.
Lyme disease (LD) is a tick-borne disease which has been emerging in temperate areas in North America, Europe, and Asia. In Quebec, Canada, the number of human LD cases is increasing rapidly and thus surveillance of LD risk is a public health priority. In this study, we aimed to evaluate the ability of active sentinel surveillance to track spatiotemporal trends in LD risk. Using drag flannel data from 2015-2019, we calculated density of nymphal ticks (DON), an index of enzootic hazard, across the study region (southern Quebec). A Poisson regression model was used to explore the association between the enzootic hazard and LD risk (annual number of human cases) at the municipal level. Predictions from models were able to track both spatial and interannual variation in risk. Furthermore, a risk map produced by using model predictions closely matched the official risk map published by provincial public health authorities, which requires the use of complex criteria-based risk assessment. Our study shows that active sentinel surveillance in Quebec provides a sustainable system to follow spatiotemporal trends in LD risk. Such a network can support public health authorities in informing the public about LD risk within their region or municipality and this method could be extended to support Lyme disease risk assessment at the national level in Canada.
莱姆病(LD)是一种由蜱传播的疾病,已在北美、欧洲和亚洲的温带地区出现。在加拿大魁北克省,人类莱姆病病例数量正在迅速增加,因此对莱姆病风险的监测是公共卫生的优先事项。在本研究中,我们旨在评估主动哨兵监测追踪莱姆病风险时空趋势的能力。利用2015年至2019年的拖布绒布数据,我们计算了整个研究区域(魁北克省南部)若蜱密度(DON),这是一种动物疫病流行危害指标。采用泊松回归模型探讨市级层面动物疫病流行危害与莱姆病风险(人类病例年数)之间的关联。模型预测能够追踪风险的空间和年际变化。此外,使用模型预测生成的风险地图与省级公共卫生当局发布的官方风险地图密切匹配,后者需要使用基于复杂标准的风险评估。我们的研究表明,魁北克省的主动哨兵监测提供了一个可持续的系统来跟踪莱姆病风险的时空趋势。这样一个网络可以支持公共卫生当局向其所在地区或城市的公众通报莱姆病风险,并且这种方法可以扩展到支持加拿大国家层面的莱姆病风险评估。