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

被引：12

作者：

Mateus, Marcos ^{[1
]}

Fernandes, Jose ^{[2
]}

Revilla, Marta ^{[2
]}

Ferrer, Luis ^{[2
]}

Villarreal, Manuel Ruiz ^{[3
]}

Miller, Peter ^{[4
]}

Schmidt, Wiebke ^{[5
]}

Maguire, Julie ^{[6
]}

Silva, Alexandra ^{[7
]}

Pinto, Ligia ^{[1
]}

机构：

[1] Univ Lisbon, Inst Super Tecn, MARETEC, Lisbon, Portugal

[2] AZTI, Portualdea Z-G, Pasaia 20110, Gipuzkoa, Spain

[3] Inst Espanol Oceanog, La Coruna 15011, Galicia, Spain

[4] Plymouth Marine Lab, Prospect Pl, Plymouth PL1 3DH, Devon, England

[5] Marine Inst Rinville, Marine Environm & Food Safety Serv, Oranmore H91 R673, Co Galway, Ireland

[6] Bantry Marine Res Stn, Bantry P75 AX07, Co Cork, Ireland

[7] IP Inst Portugues Mar & Atmosfera, IPMA, R Alfredo Magalhaes Ramalho 6, P-1495006 Lisbon, Portugal

来源：

COMPUTATIONAL SCIENCE - ICCS 2019, PT IV | 2019年 / 11539卷

关键词：

Shellfish safety; Early warning systems; Aquaculture; HARMFUL ALGAL BLOOMS; KARENIA-MIKIMOTOI; NOROVIRUS; TIDE; CLASSIFICATION; TRANSMISSION; OUTBREAK; MODELS; WATERS;

D O I：

10.1007/978-3-030-22747-0_28

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：361 / 375

页数：15

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