De Keukeleire Mathilde, Robert Annie, Kabamba Benoît, Dion Elise, Luyasu Victor, Vanwambeke Sophie O
Earth and Life Institute (ELI), Georges Lemaitre Center for Earth and Climate Research, Université catholique de Louvain (UCL), Louvain-la-Neuve, Belgique.
Pôle Epidémiologie et Biostatistique, Institut de Recherche Expérimentale et Clinique (IREC), Faculté de Santé Publique (FSP), Université catholique de Louvain (UCL), Bruxelles, Belgique;
Infect Ecol Epidemiol. 2016 Nov 15;6:32793. doi: 10.3402/iee.v6.32793. eCollection 2016.
Lyme disease (LD) is a common tick-borne disease in Europe. Diverse factors at various scales determine the spatial distribution of infection risk and a better understanding of those factors in a spatially explicit framework is needed for disease management and prevention. While the ecology of ticks and the landscape favoring their abundance have been extensively studied, the environmental conditions favoring an intense contact with susceptible humans, including groups at risk, are sparse. The aim of this study is to assess which individual and environmental factors can favor infection in a Belgian group professionally at risk.
Serological results of 127 veterinarians and farmers enrolled in this study were analyzed, taking into account their municipality of residence. Using binary logistic regression and considering interaction terms, the joint effects of landscape composition and configuration, and forest and wildlife management were examined.
Seven of the 127 workers were seropositive for LD, leading to a seroprevalence of 5.51%. Seropositivity was higher in older persons. The proportion of forest and semi-natural habitats and wetland had a positive impact on LD seroprevalence while arable land-grassland ecotones had a negative one. Our results confirmed the need to consider complex interactions between landscape variables in order to model risk.
Our data show that LD has to be considered as a risk for farmers and veterinarians. Rather than focusing either on ecological aspects of tick and pathogen distribution or on purely epidemiological aspects such as individual risk factors, our model highlights the role of human-environment interactions in LD risk assessment.
莱姆病(LD)是欧洲一种常见的蜱传疾病。不同尺度的多种因素决定了感染风险的空间分布,为了疾病管理和预防,需要在空间明确的框架内更好地理解这些因素。虽然蜱的生态学以及有利于其大量繁殖的景观已得到广泛研究,但有利于与易感人群(包括高危人群)密切接触的环境条件却很少见。本研究的目的是评估哪些个体和环境因素会促使比利时一个职业高危群体感染。
分析了参与本研究的127名兽医和农民的血清学结果,并考虑了他们的居住市镇。使用二元逻辑回归并考虑交互项,研究了景观组成和配置以及森林和野生动物管理的联合效应。
127名工作人员中有7人莱姆病血清学呈阳性,血清阳性率为5.51%。老年人的血清阳性率更高。森林、半自然栖息地和湿地的比例对莱姆病血清阳性率有积极影响,而耕地 - 草地交错带则有负面影响。我们的结果证实,为了对风险进行建模,需要考虑景观变量之间的复杂相互作用。
我们的数据表明,必须将莱姆病视为农民和兽医面临的一种风险。我们的模型并非只关注蜱和病原体分布的生态方面或纯粹的流行病学方面(如个体风险因素),而是突出了人类 - 环境相互作用在莱姆病风险评估中的作用。