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Risk factors and geospatial modelling for the presence of Fasciola hepatica infection in sheep and goat farms in the Greek temperate Mediterranean environment

Published online by Cambridge University Press:  17 May 2011

V. KANTZOURA
Affiliation:
Department of Anatomy and Physiology of Farm Animals, Faculty of Animal Science and Hydrobiology, Agricultural University of Athens, 75 Iera Odos, Votanikos, Athens 11855, Greece
M. K. KOUAM
Affiliation:
Department of Anatomy and Physiology of Farm Animals, Faculty of Animal Science and Hydrobiology, Agricultural University of Athens, 75 Iera Odos, Votanikos, Athens 11855, Greece
N. DEMIRIS
Affiliation:
Department of Animal Breeding and Husbandry, Faculty of Animal Science and Hydrobiology, Agricultural University of Athens, 75 Iera Odos St., Votanikos, Athens 11855, Greece
H. FEIDAS
Affiliation:
Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece
G. THEODOROPOULOS*
Affiliation:
Department of Anatomy and Physiology of Farm Animals, Faculty of Animal Science and Hydrobiology, Agricultural University of Athens, 75 Iera Odos, Votanikos, Athens 11855, Greece
*
*Corresponding author: Department of Anatomy and Physiology of Farm Animals, Faculty of Animal Science and Hydrobiology, Agricultural University of Athens, 75 Iera Odos, Votanikos, Athens 11855, Greece. Tel: +30-201-5294387. Fax: +30-201-5294388. E-mail: [email protected]

Summary

Risk factors related to herd and farmer status, farm and pasture management, and environmental factors derived by satellite data were examined for their association with the prevalence of F. hepatica in sheep and goat farms in Thessaly, Greece. Twelve farms (16·2%) and 58 farms (78·4%) of 74 had evidence of infection using coproantigen and serology respectively. The average normalized difference vegetation index (NDVI) of farm location for 12 months before sampling was the most significant environmental risk factor for F. hepatica infection based on high seropositivity. The risk of infection increased by 1% when the value of NDVI increased by 0·01 degree. A geospatial map was constructed to show the relative risk (RR) of Fasciola infection in sheep and goat farms in Thessaly. In addition, geospatial maps of the model-based predicted RR for the presence of Fasciola infection in farms in Thessaly and the entire area of Greece were constructed from the developed model based on NDVI. In conclusion, this study demonstrated that Thessaly should be regarded as an endemic region for Fasciola infection and it represents the first prediction model of Fasciola infection in small ruminants in the Mediterranean basin.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2011

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