Early Warning Systems for Shellfish Safety: The Pivotal Role of Computational Science View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019-06-08

AUTHORS

Marcos Mateus , Jose Fernandes , Marta Revilla , Luis Ferrer , Manuel Ruiz Villarreal , Peter Miller , Wiebke Schmidt , Julie Maguire , Alexandra Silva , Lígia Pinto

ABSTRACT

Toxins from harmful algae and certain food pathogens (Escherichia coli and Norovirus) found in shellfish can cause significant health problems to the public and have a negative impact on the economy. For the most part, these outbreaks cannot be prevented but, with the right technology and know-how, they can be predicted. These Early Warning Systems (EWS) require reliable data from multiple sources: satellite imagery, in situ data and numerical tools. The data is processed and analyzed and a short-term forecast is produced. Computational science is at the heart of any EWS. Current models and forecast systems are becoming increasingly sophisticated as more is known about the dynamics of an outbreak. This paper discusses the need, main components and future challenges of EWS. More... »

PAGES

361-375

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-22747-0_28

DOI

http://dx.doi.org/10.1007/978-3-030-22747-0_28

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1117250247


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