Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada
Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculté de médecine vétérinaire (FMV), Université de Montréal, Saint-Hyacinthe, Québec, Canada
Environ Health Perspect. 2018 Apr 18;126(4):047008. doi: 10.1289/EHP1943.
The risk of contracting Lyme disease (LD) can vary spatially because of spatial heterogeneity in risk factors such as social-behavior and exposure to ecological risk factors. Integrating these risk factors to inform decision-making should therefore increase the effectiveness of mitigation interventions.
The objective of this study was to develop an integrated social-behavioral and ecological risk-mapping approach to identify priority areas for LD interventions.
The study was conducted in the Montérégie region of Southern Quebec, Canada, where LD is a newly endemic disease. Spatial variation in LD knowledge, risk perceptions, and behaviors in the population were measured using web survey data collected in 2012. These data were used as a proxy for the social-behavioral component of risk. Tick vector population densities were measured in the environment during field surveillance from 2007 to 2012 to provide an index of the ecological component of risk. Social-behavioral and ecological components of risk were combined with human population density to create integrated risk maps. Map predictions were validated by testing the association between high-risk areas and the current spatial distribution of human LD cases.
Social-behavioral and ecological components of LD risk had markedly different distributions within the study region, suggesting that both factors should be considered for locally adapted interventions. The occurrence of human LD cases in a municipality was positively associated with tick density (<0.01) but was not significantly associated with social-behavioral risk.
This study is an applied demonstration of how integrated social-behavioral and ecological risk maps can be created to assist decision-making. Social survey data are a valuable but underutilized source of information for understanding regional variation in LD exposure, and integrating this information into risk maps provides a novel approach for prioritizing and adapting interventions to the local characteristics of target populations. https://doi.org/10.1289/EHP1943.
由于社会行为和接触生态风险因素等风险因素存在空间异质性，因此莱姆病（LD）的发病风险会存在空间差异。因此，整合这些风险因素以辅助决策应该会提高缓解干预措施的效果。
本研究旨在开发一种综合的社会行为和生态风险绘图方法，以确定 LD 干预的优先领域。
该研究在加拿大魁北克南部的蒙泰雷吉地区进行，那里 LD 是一种新出现的地方病。使用 2012 年收集的网络调查数据，测量了人群中 LD 知识、风险认知和行为的空间变化。这些数据被用作风险的社会行为部分的代表。在 2007 年至 2012 年的实地监测期间，在环境中测量了蜱虫种群密度，以提供风险的生态部分的指标。将社会行为和生态风险因素与人口密度相结合，创建综合风险图。通过测试高风险区域与当前人类 LD 病例的空间分布之间的相关性，对地图预测进行了验证。
LD 风险的社会行为和生态因素在研究区域内的分布明显不同，这表明应考虑这两个因素来制定适应当地情况的干预措施。一个市镇的人类 LD 病例的发生与蜱密度呈正相关（<0.01），但与社会行为风险无显著相关性。
本研究是如何创建综合的社会行为和生态风险图以辅助决策的应用示范。社会调查数据是了解 LD 暴露的区域差异的有价值但利用不足的信息来源，将这些信息整合到风险图中为根据目标人群的当地特征优先排序和调整干预措施提供了一种新方法。https://doi.org/10.1289/EHP1943.
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