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1.
Geospat Health ; 9(2): 309-17, 2015 Mar 19.
Artigo em Inglês | MEDLINE | ID: mdl-25826312

RESUMO

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.


Assuntos
Agricultura , Fasciolíase/veterinária , Análise Espacial , Fatores Etários , Animais , Teorema de Bayes , Estudos Transversais , Ensaio de Imunoadsorção Enzimática , Europa (Continente)/epidemiologia , Fezes/parasitologia , Feminino , Sistemas de Informação Geográfica , Prevalência , Ovinos , Doenças dos Ovinos
2.
Geospat Health ; 9(2): 325-31, 2015 Mar 19.
Artigo em Inglês | MEDLINE | ID: mdl-25826314

RESUMO

Haemonchus contortus is a species of gastrointestinal strongyles of primary concern for sheep. This highly pathogenic, blood-feeding helminth negatively influences animal health, welfare and productivity. In order to elucidate the current scenario in terms of prevalence and intensity of H. contortus infection in sheep farms across Europe, a standardized crosssectional 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 259 sheep farms in total. Harmonized, diagnostic procedures (from farm to laboratory) based on pooled samples, the FLOTAC technique and coproculture 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 H. contortus prevalence rates did vary between the countries showing high values in Switzerland (77%) and Italy (73%) compared to Ireland (4%). Spatial patterns of H. contortus distribution were detected in Switzerland and Italy with a north-south gradient. The latent factor analysis highlighted the importance of seasonality and annual cyclicity within country (particularly in southern Italy), while mean temperature and rainfall dominated between country variations in the prevalence of H. contortus infection.


Assuntos
Hemoncose/veterinária , Análise Espacial , Animais , Teorema de Bayes , Estudos Transversais , Europa (Continente)/epidemiologia , Fezes/parasitologia , Sistemas de Informação Geográfica , Prevalência , Chuva , Estações do Ano , Ovinos , Doenças dos Ovinos , Temperatura
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