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An online operational alert system for the early detection of shrimp epidemics at the regional level based on real-time production
Bayot, B.; Sonnenholzner, S.; Ochoa, X.; Guerrerro, J.; Vera, T.; Calderon, J.; de Blas, I.; Cornejo-Grunauer, M.D.; Stern, S.; Ollevier, F. (2008). An online operational alert system for the early detection of shrimp epidemics at the regional level based on real-time production. Aquaculture 277(3-4): 164-173. dx.doi.org/10.1016/j.aquaculture.2008.02.035
In: Aquaculture. Elsevier: Amsterdam; London; New York; Oxford; Tokyo. ISSN 0044-8486, more
Peer reviewed article  

Available in Authors 
    VLIZ: Open Repository 280334 [ OMA ]

Author keywords
    early detection system; veterinary disease surveillance; online alertsystem; shrimp epidemics; Ecuador; aquatic epidemiology

Authors  Top 
  • Bayot, B., more
  • Sonnenholzner, S.
  • Ochoa, X.
  • Guerrerro, J.
  • Vera, T.
  • Calderon, J.
  • de Blas, I.
  • Cornejo-Grunauer, M.D.
  • Stern, S.
  • Ollevier, F., more

Abstract
    Diseases are among the greatest threats affecting the sustainability of shrimp aquaculture. In Ecuador, diseases of cultured shrimp have been quickly transmitted from one region to another. Therefore, an early detection system of impending epidemics could serve as an important management tool for the aquaculture sector. We developed a system for the early detection of shrimp epidemics for the largest shrimp zone of Ecuador based on production surveillance. The system, called Epidemiological Alert System and Aquaculture Management (SAEMA), uses a geographical information system (GIS) with an imaginary grid cartography (12,860 ha per grid) dividing the study area. A production and management index is calculated with the harvest data of each pond. A standardized deviation around the historical averages and an alert level is calculated per grid and month. Normal conditions of production and therefore the absence of disease are depicted in green and yellow. While, orange and red colours express a disease warning manifested through suboptimal production levels. As a result, a map of the study area with grid divisions is displayed, with a specific alert colour for each grid where information is available. SAEMA was developed as a Web application (http://www.saema.espol.edu.ec) that enables producers to record data via a worksheet format using any web browser. Instantaneously, the applications perform a calculation of the alert index and provide feedback to the alert levels displayed in an interactive map. A feedback process was initiated in May 2006 with 19 participating shrimp farms. The objective of this research is to develop a platform for an early detection of shrimp epidemics on a regional scale. The detection of an epidemic, expressed as suboptimal production in a specific region, can provide producers from other zones and government authorities to engage in time preventive and control measures in order to reduce the spread of diseases.

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