K D C Staerk
Use of molecular and genomic data for disease surveillance in aquaculture: Towards improved evidence for decision making
Staerk, K D C; Pekala, A; Muellner, P
Authors
A Pekala
P Muellner
Abstract
Diagnostic tools for the identification and confirmation of animal diseases have been evolving rapidly over the last decade, with diseases of aquatic animals being no exception. Hence, case definitions used in surveillance may now include molecular and genomic components and ultimately be based on the entire genome of a pathogen. While the opportunities brought on by this change in our ability to define and differentiate organisms are manifold, there are also challenges. These include the need to consider typing tool characteristics during sampling design, but also the re-thinking of diagnostic protocols and standards for the meaningful interpretation of the increasingly complex data presented to surveillance managers. These issues are illustrated for aquaculture using the example of multi-country surveillance of antimicrobial resistance of Aeromonas spp. strains isolated from rainbow trouts (Oncorhynchus mykiss) in Europe. In order to fully exploit the opportunities of molecular and genomic information, a multi-disciplinary approach is needed to develop harmonised diagnostic procedures and modified surveillance designs for aquaculture as well as for terrestrial animal production. This will require adjustments in the relevant standards applicable to assess food safety and trade risks.
Citation
Staerk, K. D. C., Pekala, A., & Muellner, P. (2019). Use of molecular and genomic data for disease surveillance in aquaculture: Towards improved evidence for decision making. Preventive Veterinary Medicine, 167, 190-195. https://doi.org/10.1016/j.prevetmed.2018.04.011
Journal Article Type | Article |
---|---|
Acceptance Date | Apr 17, 2018 |
Publication Date | Apr 18, 2019 |
Deposit Date | Apr 26, 2018 |
Publicly Available Date | May 1, 2019 |
Journal | Preventive Veterinary Medicine |
Print ISSN | 0167-5877 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 167 |
Pages | 190-195 |
DOI | https://doi.org/10.1016/j.prevetmed.2018.04.011 |
Public URL | https://rvc-repository.worktribe.com/output/1382776 |
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