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

Mateus, M; Fernandes, JA; Revilla, M; Ferrer, L; Villarreal, MR; Miller, PI; Schmidt, W; Maguire, J; Silva, A; Pinto, L. 2019 Early Warning Systems for Shellfish Safety: The Pivotal Role of Computational Science. Springer Nature, 11539. 361-375. https://doi.org/10.1007/978-3-030-22747-0_28

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

Abstract/Summary

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.

Item Type: Publication - Article
Divisions: Plymouth Marine Laboratory > Science Areas > Earth Observation Science and Applications
Depositing User: S Hawkins
Date made live: 16 Oct 2019 13:33
Last Modified: 25 Apr 2020 10:00
URI: http://plymsea.ac.uk/id/eprint/8252

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