Perspectives on using remotely-sensed imagery in predictive veterinary epidemiology and global early warning systems

Submitted: 23 December 2014
Accepted: 23 December 2014
Published: 1 November 2007
Abstract Views: 1508
PDF: 795
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

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.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

How to Cite

Martin, V., De Simone, L., Lubroth, J., Ceccato, P., & Chevalier, V. (2007). Perspectives on using remotely-sensed imagery in predictive veterinary epidemiology and global early warning systems. Geospatial Health, 2(1), 3–14. https://doi.org/10.4081/gh.2007.250

Similar Articles

You may also start an advanced similarity search for this article.