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Perspectives on using remotely-sensed imagery in predictive veterinary epidemiology and global early warning systems
Author(s) -
Vincent Martin,
Lorenzo De Simone,
Juan Lubroth,
Pietro Ceccato,
Véronique Chevalier
Publication year - 2007
Publication title -
geospatial health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.545
H-Index - 36
eISSN - 1970-7096
pISSN - 1827-1987
DOI - 10.4081/gh.2007.250
Subject(s) - rift valley fever , warning system , livestock , early warning system , outbreak , wildlife , disease , disease surveillance , epidemiology , geography , public health , environmental health , climate change , environmental planning , environmental resource management , business , medicine , ecology , computer science , biology , telecommunications , nursing , environmental science , pathology , virology , forestry
Recent disease epidemics and their spread around the world have illustrated the weaknesses of disease surveillance and early warning systems (EWS), both at national and international levels. These diseases continuously threaten the livestock sector on a worldwide basis, some with major public health impact. EWS and accurate forecasting of new outbreaks of epidemic livestock diseases that may also affect wildlife, and the capacity for spread of such diseases to new areas is an essential pre-requisite to their effective containment and control. Because both the geographical and seasonal distribution of many infectious diseases are linked to climate, the possibility of using climaterelated environmental factors as predictive indicators, in association with regular disease surveillance activities, has proven to be relevant when establishing EWS for climate-related diseases. This article reviews the growing importance of using geographical information systems in predictive veterinary epidemiology and its integration into EWS, with a special focus on Rift Valley fever. It shows that, once fully validated in a country or region, this technology appears highly valuable and could play an increasing role in forecasting major epidemics, providing lead time to national veterinary services to take action to mitigate the impact of the disease in a cost-effective manner.

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