ORIGINAL RESEARCH article
Front. Aquac.
Sec. Disease and Health Management
Volume 4 - 2025 | doi: 10.3389/faquc.2025.1647026
Modeling dynamics of adult female lice at salmon farming sites in Eastern Canada: A Stochastic, State-Based Approach
Provisionally accepted- 1Universidad Adolfo Ibanez Facultad de Ingenieria y Ciencias, Santiago, Chile
- 2Fundación CSIRO Chile Research, Santiago, Chile
- 3Dalhousie University Faculty of Computer Science, Halifax, Canada
- 4Dalhousie University Department of Oceanography, Halifax, Canada
- 5Department of Health Management and Centre for Veterinary Epidemiological Research (CVER), Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada
- 6Innovasea Marine Systems Canada, Bedford, Nova Scotia, Canada
- 7Marine Affairs Program, Dalhousie University, Halifax, Nova Scotia, Canada
- 8Cooke Aquaculture Inc., Saint John, New Brunswick, Canada
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A stochastic, state-based, time-dependent epidemiological model was developed to characterize the dynamics of adult female sea lice (Lepeophtheirus salmonis) infestation in Atlantic salmon farms in New Brunswick, Canada. The model integrated covariates associated to farming practices and environmental conditions (stocking week, farming cycle week as proxy of fish age, sea lice treatments, seaway distance to neighboring farms as a proxy for waterborne transmission, and sea surface temperature). Data from 57 farming sites were used for model training and validation. An initial exploratory analysis assessed the relationship between treatment timing and recovery from infestation. Treatment effects were incorporated into weekly transitions between infestation states, accounting for severity and time-varying environmental factors. Results suggest that spring and summer stocking increases exposure to external infestation pressure and raises the probability of high lice concentrations. Further, reduced winter treatments are associated with elevated infestation levels. Treatment effectiveness appeared to be compromised by continued waterborne transmission from nearby farms. The model achieved an overall likelihood of 59%, reaching up to 74% during the first 10 weeks following stocking. Limitations included the use of proxy connectivity measures, i.e. seaway distance, rather than hydrodynamic connectivity, and the absence of data on fish size, salinity, and other farming practices such as fish density. Additionally, we were unable to include information from all farms in the study area, potentially underestimating transmission risk. Addressing these gaps and integrating hydrodynamic connectivity and fish growth models could improve predictive performance.
Keywords: (Lepeophtheirus salmonis), Stochastic Modeling, Infestation dynamics, Treatment effectiveness, Eastern Canada aquaculture
Received: 14 Jun 2025; Accepted: 05 Sep 2025.
Copyright: © 2025 Bravo, Oliveira, Parent, Korus, Sclodnick, Gardner, Whidden, Filgueira, Hammell, Swanson, Torgo and Grant. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Francisco Bravo, Universidad Adolfo Ibanez Facultad de Ingenieria y Ciencias, Santiago, Chile
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