Dataset Information

Derivation of the economic value of R₀ for macroparasitic diseases and application to sea lice in salmon.

ABSTRACT:

Background

Macroparasites, such as ticks, lice, and helminths, are a concern in livestock and aquaculture production, and can be controlled by genetic improvement of the host population. Genetic improvement should aim at reducing the rate at which parasites spread across the farmed population. This rate is determined by the basic reproduction ratio, i.e. [Formula: see text], which is the appropriate breeding goal trait. This study aims at providing a method to derive the economic value of [Formula: see text].

Methods

Costs of a disease are the sum of production losses and expenditures on disease control. Genetic improvement of [Formula: see text] lowers the loss-expenditure frontier. Its economic effect depends on whether the management strategy is optimized or not. The economic value may be derived either from the reduction in losses with constant expenditures or from the reduction in expenditures with constant losses.

Results

When [Formula: see text]???1, the economic value of a further reduction is zero because there is no risk of a major epidemic. When [Formula: see text]?>?1 and management is optimized, the economic value increases with decreasing values of [Formula: see text], because both the mean number of parasites per host and frequency of treatments decrease at an increasing rate when [Formula: see text] decreases. When [Formula: see text]?>?1 and management is not optimized, the economic value depends on whether genetic improvement is used for reducing expenditures or losses. For sea lice in salmon, the economic value depends on a reduction in expenditures with constant losses, and is estimated to be 0.065€/unit [Formula: see text]/kg production.

Discussion

Response to selection for measures of disease prevalence cannot be predicted from quantitative genetic theory alone. Moreover, many studies fail to address the issue of whether genetic improvement results in reduced losses or expenditures. Using [Formula: see text] as the breeding goal trait, weighed by its appropriate economic value, avoids these issues.

Conclusion

When management is optimized, the economic value increases with decreasing values of [Formula: see text] (until the threshold of [Formula: see text], where it drops to zero). When management is not optimized, the economic value depends on whether genetic improvement is used for reduced expenditures or production losses. For sea lice in salmon, the economic value is estimated to be 0.065 €/unit [Formula: see text]/kg production.

SUBMITTER: Janssen K

PROVIDER: S-EPMC6171287 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Publications

Derivation of the economic value of R<sub>0</sub> for macroparasitic diseases and application to sea lice in salmon.

Janssen Kasper K Komen Hans H Saatkamp Helmut W HW de Jong Mart C M MCM Bijma Piter P

Genetics, selection, evolution : GSE 20181003 1

<h4>Background</h4>Macroparasites, such as ticks, lice, and helminths, are a concern in livestock and aquaculture production, and can be controlled by genetic improvement of the host population. Genetic improvement should aim at reducing the rate at which parasites spread across the farmed population. This rate is determined by the basic reproduction ratio, i.e. [Formula: see text], which is the appropriate breeding goal trait. This study aims at providing a method to derive the economic value o ...[more]

PMID: 30285629

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Project description:BackgroundSea lice have significant negative economic and welfare impacts on marine Atlantic salmon farming. Since host resistance to sea lice has a substantial genetic component, selective breeding can contribute to control of lice. Genomic selection uses genome-wide marker information to predict breeding values, and can achieve markedly higher accuracy than pedigree-based methods. Our aim was to assess the genetic architecture of host resistance to sea lice, and test the utility of genomic prediction of breeding values. Individual lice counts were measured in challenge experiments using two large Atlantic salmon post-smolt populations from a commercial breeding programme, which had genotypes for ~33 K single nucleotide polymorphisms (SNPs). The specific objectives were to: (i) estimate the heritability of host resistance; (ii) assess its genetic architecture by performing a genome-wide association study (GWAS); (iii) assess the accuracy of predicted breeding values using varying SNP densities (0.5 to 33 K) and compare it to that of pedigree-based prediction; and (iv) evaluate the accuracy of prediction in closely and distantly related animals.ResultsHeritability of host resistance was significant (0.22 to 0.33) in both populations using either pedigree or genomic relationship matrices. The GWAS suggested that lice resistance is a polygenic trait, and no genome-wide significant quantitative trait loci were identified. Based on cross-validation analysis, genomic predictions were more accurate than pedigree-based predictions for both populations. Although prediction accuracies were highest when closely-related animals were used in the training and validation sets, the benefit of having genomic-versus pedigree-based predictions within a population increased as the relationships between training and validation sets decreased. Prediction accuracy reached an asymptote with a SNP density of ~5 K within populations, although higher SNP density was advantageous for cross-population prediction.ConclusionsHost resistance to sea lice in farmed Atlantic salmon has a significant genetic component. Phenotypes relating to host resistance can be predicted with moderate to high accuracy within populations, with a major advantage of genomic over pedigree-based methods, even at relatively sparse SNP densities. Prediction accuracies across populations were low, but improved with higher marker densities. Genomic selection can contribute to lice control in salmon farming.

Project description:This study presents an Agent-Based Model (ABM) simulation to assess the impact of varying migration routes on sea lice (Caligus clemensi) infestation levels in juvenile wild sockeye salmon (Oncorhynchus nerka) in the Discovery Islands, British Columbia, Canada. This research highlights the importance of migratory routes in determining the extent of exposure to sea lice originating from nearby salmon farms. Three northward out-migration routes were modelled, each exposing the fish to different levels of infestation pressure based on proximity to salmon farms. The ABM incorporates spatially explicit migration patterns of juvenile sockeye salmon using a detailed raster map of the Discovery Islands. Key variables such as swimming speed, progression rate, and infestation levels were integrated into the model, offering a comprehensive analysis of migration and infestation dynamics. The study revealed that infestation rate is highly variable, depending on migration routes. Specifically, salmon traveling longer migration routes with lower infestation pressure may experience higher sea lice loads compared to those on shorter routes with higher infestation pressure. This underscores the role of low infestation pressures and the critical influence of swimming speed, which affects exposure time, and thus infestation rates. Additionally, the study conducted a sensitivity analysis to understand the influence of various parameters on infestation rates. This analysis highlighted the importance of swimming speed and progression rate, particularly in routes closer to the farms. The findings suggest that slower swimming speeds and meandering routes increase exposure to lice, thereby elevating infestation levels. The research contributes to understanding the dynamics of sea lice transmission and its relationship with salmon migration patterns. It underscores the necessity of considering migratory routes and farm proximity in managing and mitigating the impact of sea lice infestation on wild salmon populations. This study's insights are crucial for developing strategies to balance aquaculture practices with the conservation of wild salmon.

Dataset Information

Derivation of the economic value of R₀ for macroparasitic diseases and application to sea lice in salmon.

Background

Methods

Results

Discussion

Conclusion

Publications

Derivation of the economic value of R<sub>0</sub> for macroparasitic diseases and application to sea lice in salmon.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

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Dataset Information

Derivation of the economic value of R0 for macroparasitic diseases and application to sea lice in salmon.

Background

Methods

Results

Discussion

Conclusion

Publications

Derivation of the economic value of R<sub>0</sub> for macroparasitic diseases and application to sea lice in salmon.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Derivation of the economic value of R₀ for macroparasitic diseases and application to sea lice in salmon.