| Literature DB >> 26880836 |
Maya L Groner1, Luke A Rogers2, Andrew W Bateman3, Brendan M Connors4, L Neil Frazer5, Sean C Godwin6, Martin Krkošek7, Mark A Lewis8, Stephanie J Peacock9, Erin E Rees10, Crawford W Revie10, Ulrike E Schlägel11.
Abstract
Effective disease management can benefit from mathematical models that identify drivers of epidemiological change and guide decision-making. This is well illustrated in the host-parasite system of sea lice and salmon, which has been modelled extensively due to the economic costs associated with sea louse infections on salmon farms and the conservation concerns associated with sea louse infections on wild salmon. Consequently, a rich modelling literature devoted to sea louse and salmon epidemiology has been developed. We provide a synthesis of the mathematical and statistical models that have been used to study the epidemiology of sea lice and salmon. These studies span both conceptual and tactical models to quantify the effects of infections on host populations and communities, describe and predict patterns of transmission and dispersal, and guide evidence-based management of wild and farmed salmon. As aquaculture production continues to increase, advances made in modelling sea louse and salmon epidemiology should inform the sustainable management of marine resources.Entities:
Keywords: Atlantic salmon; Pacific salmon; ecological modelling; emerging infectious disease; fish farm; marine disease
Mesh:
Year: 2016 PMID: 26880836 PMCID: PMC4760134 DOI: 10.1098/rstb.2015.0203
Source DB: PubMed Journal: Philos Trans R Soc Lond B Biol Sci ISSN: 0962-8436 Impact factor: 6.237