Sheep and Fasciola hepatica in Europe: the GLOWORM experience

Abstract

Abstract.Fasciola hepatica infection challenges health, welfare and productivity of small ruminants throughout the world. The distribution of F. hepatica in sheep in Europe is usually scattered and studies are generally concerned with a single area making it difficult to compare results from different environments, climates and management regimes. In order to elucidate the current scenario in terms of prevalence and intensity of F. hepatica infection in sheep farms across Europe, a standardized cross-sectional survey was conducted in three pilot areas in Ireland, Switzerland and Italy, all part of the EU funded GLOWORM project. Two consecutive field surveys (in 2012 and 2013) were conducted in the three countries in the same period (August-October) in 361 sheep farms in total. Harmonized procedures (from farm to laboratory) based on pooled samples and the highly sensitive and accurate, diagnostic FLOTAC technique were used. The georeferenced parasitological results were modelled (at the pilot area level) following a Bayesian geostatistical approach with correction for preferential sampling and accounting for climatic and environmental covariates. The observed F. hepatica prevalence rates did not differ between the two study years in any of the three pilot areas, but they did vary between the countries showing high values in Ireland (61.6%) compared to Italy (7.9%) and Switzerland (4.0%). Spatial patterns of F. hepatica distribution were detected by the Bayesian geostatistical approach in Ireland with a high risk of infection in the south-western part of the pilot area there. The latent factor analysis highlighted the importance of year-to-year variation of mean temperature, rainfall and seasonality within a country, while long-term trends of temperature and rainfall dominated between countries with respect to prevalence of infection.

Preferential sampling in veterinary parasitological surveillance

“…We believe that this is an effect of the smoothness in the covariates. In fact, F. hepatica is a very rare infection in Italy because of Italy's climate characteristics (in contrast for example to Ireland; Rinaldi et al, 2015a) and given the general smoothness of the covariates included in the geostatistical model for risk infection, we expect some smoothing in the predicted infection probabilities.…”

“…Altogether, the two surveys provide information and data from a total of 89 farms: 50 farms coming from the first aforementioned on-going survey with data collected in 2013, and 39 farms coming from the second survey with data collected in 2014 (Rinaldi et al, 2015a).…”

“…Pooled faecal samples (Rinaldi et al, 2015a) were collected for biological examinations and faecal egg counts (FEC) were determined using the FLOTAC dual technique (Cringoli et al, 2010;Rinaldi et al, 2015a), which has an analytic sensitivity of 6 eggs per gram of faeces (EPG). To detect and count the number F. hepatica eggs, we used a zinc sulphate-based flotation solution (ZnSO4 specific gravity=1.350).…”

“…Using GIS, we derived 19 bioclimatic layers and 30 Moderate-resolution Imaging Spectroradiometer (MODIS) variables that can be used to explain the spatial pattern of the infection (Rinaldi et al, 2015a). To assign a covariate value to each farm, we overimposed a 10x10 km grid on the Campania region, and we identified buffer zones of 3 km around each sampled farm using the geographic information system (GIS).…”

“…Few examples (Zouré et al, 2014;Rinaldi et al, 2015a) are present in the context of veterinary surveillance, where informative or opportunistic sampling is very common. In this paper, we tackle the problem of preferential sampling in parasitological veterinary surveillance and we specify a two-stage hierarchical Bayesian model to adjust for the preferential sampling nature of the data.…”