Individual and environmental factors associated with the seroprevalence ofBorrelia burgdorferiin Belgian farmers and veterinarians

Abstract

BackgroundLyme disease (LD) is a common tick-borne disease in Europe. Diverse factors at various scales determine the spatial distribution of Borrelia burgdorferi 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 B. burgdorferi infection in a Belgian group professionally at risk.MethodsSerological 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.ResultsSeven 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.ConclusionsOur 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.

Using volunteered observations to map human exposure to ticks

“…Unfortunately, information on whether the tick bite was acquired during a work-related activity was only available for the TR data and is therefore not incorporated in the model. However, these collectives tend to present a higher seroprevalence for LB 35 , 36 .…”

“…For an instance, activities such as gardening 16 can be linked to the residential exposure, whereas other activities such as scouting 13 , or outdoor sport 15 competitions could be linked to the recreational exposure. Note that a limitation of this work is that we are unable to provide a measure of occupational risk, but farmers 35 , veterinarians 36 , landscapers 37 , or forest workers 38 are known to have an elevated risk of LB infection. Unfortunately, information on whether the tick bite was acquired during a work-related activity was only available for the TR data and is therefore not incorporated in the model.…”

Seroprevalence of Borrelia burgdorferi in Belgian forestry workers and associated risk factors

“…Landscape composition and configuration in each TMU were measured using the Wallonia land cover map [Carte d’occupation du sol de Wallonie (2007) from the “Service public de Wallonie” (Copyright-SPW-n°140225-1407)]. As detailed in a previous study [ 15 ], the proportions of several land cover types were calculated for each TMU (Table 1 ). Landscape configuration was described by using various indices focusing on an aggregated forest class (forest and semi-natural habitats) (Table 1 ).…”

“…We calculated the mean number of animals and the mean number of animals shot by TMU over the 2002–2011 period because the date of infection is unknown. To compare with previous studies, we divided those numbers by the forested area in the direction and obtained the density of game and game shot by TMU [ 13 , 15 ].…”

Tick Bite Risk as a Socio-Spatial Representation—An Exploratory Study in Massif Central, France

“…Moreover, most participants also identified the forest in their drawings. This reflects the statistical reality of an increased risk of tick bites in forests, especially hardwood or mixed (deciduous and coniferous) [12,33,57,58]. However, the difference in risk according to the type of forest appears to be unknown to most individuals.…”