Towards assessing fine-scale indicators for the spatial transmission risk of Fasciola hepatica in cattle

In order to improve the spatial resolution of current risk maps for fasciolosis in cattle, more knowledge is needed with respect to farm-level factors that determine infection risk. In this study, we visited 39 dairy farms within a predefined low- and high-risk area for fasciolosis in Belgium and assessed their infection status by an indirect bulk tank milk enzyme-linked immunosorbent assay (ELISA). Management factors were collected and all pastured lands of the farms were visited to identify and georeference potential snail habitats. The habitats were visually characterised, investigated for the presence of the intermediate host snails of Fasciola hepatica (i.e. Galba truncatula and Radix spp) and used in a geographical information system (GIS) to construct overlays including information on soil and hydrology. A linear regression model was used to evaluate associations between bulk tank milk ELISA results and farm level management and habitat factors. A logistic, mixed model was used to identify possible risk factors for the presence of intermediate host snails on a potential habitat. Potential snail habitats were found in 35 out of 39 farms. A total of 87 potential habitats were identified and on 29% of these, intermediate host snails were found. The number of potential habitats, the presence of snails, drainage of pastures, month of turnout of the cows, stocking rate, type of watering place and risk area were significantly associated with the bulk tank milk ELISA result and explained 85% of the observed variation. Intermediate host snails were more likely to be present with increasing surface of the potential habitat and on loamy soils. This study confirms the importance of farm management factors in the infection risk for F. hepatica in cattle and highlights that the combination of management factors with characterization of snail habitats is a powerful means to predict the infection risk with F. hepatica at the individual farm level. Further research is needed to investigate how this knowledge can be incorporated in nation-wide spatial distribution models of the parasite.