Spatial and temporal patterns in the sex ratio of American lobsters (Homarus americanus) in southwestern Nova Scotia, Canada.

An approximate 1:1 sex ratio of American lobsters can be skewed due to environmental factors or fisheries management. Substantial skewness can impact mating behaviour and lower reproduction which could have far-reaching ecological and economic consequences. The aim was to investigate the sex ratio patterns of lobsters in two lobster fishing areas (LFAs) in southwestern Nova Scotia, Canada and identify factors associated with skewed sex ratios. This study analyzed biological data from more than 270,000 lobsters sampled over ten years (2010-2019) by the Fishermen and Scientists Research Society. A mixed effect logistic regression model evaluated the effect of spatial, temporal and environmental factors as well as size on the sex ratio of lobsters. There were significant temporal patterns in sex ratios that differed by LFA. After the effects of sampling month, year and LFA were accounted for, lower bottom temperature and deeper water depth were associated with a higher prevalence of females, especially in larger lobsters. We present the first long term analyses of sex ratio patterns in H. americanus in Atlantic Canada's most commercially important region for this species and provide evidence that these patterns are influenced by environmental factors and fisheries. In view of future climate change scenarios, monitoring the population dynamics of this iconic fishery species is crucial to ensure sustainable fisheries and healthy lobster stocks.

Connectivity-based risk ranking of infectious salmon anaemia virus (ISAv) outbreaks for targeted surveillance planning in Canada and the USA.

Infectious salmon anaemia (ISA) can be a serious viral disease of farmed Atlantic salmon (Salmo salar). A tool to rank susceptible farms based on the risk of ISA virus (ISAv) infection spread from infectious farms after initial incursion or re-occurrence in an endemic area, can help guide monitoring and surveillance activities. Such a tool could also support the response strategy to contain virus spread, given available resources. We developed a tool to rank ISAv infection risks using seaway distance and hydrodynamic information separately and combined. The models were validated using 2002-2004 ISAv outbreak data for 30 farms (24 in New Brunswick, Canada and 6 in Maine, United States). Time sequence of infection spread was determined from the outbreak data that included monthly infection status of the cages on these farms. The first infected farm was considered as the index site for potential spread of ISAv to all other farms. To assess the risk of ISAv spreading to susceptible farms, the second and subsequent infected farms were identified using the farm status in the given time period and all infected farms from the previous time periods. Using the three models (hydrodynamic only, seaway-distance, and combined hydrodynamic-seaway-distance based models), we ranked susceptible farms within each time interval by adding the transmission risks from surrounding infected farms and sorting them from highest to lowest. To explore the potential efficiency of targeted sampling, we converted rankings to percentiles and assessed the model's predictive performance by comparing farms identified as high risk based on the rank with those that were infected during the next time interval as observed in the outbreak data. The overall predictive ability of the models was compared using area under the ROC curve (AUC). Farms that become infected in the next period were always within the top 65% of the rank predicted by our models. The overall predictive ability of the combined (hydrodynamic-seaway-distance based model) model (AUC = 0.833) was similar to the model that only used seaway distance (AUC = 0.827). Such models can aid in effective surveillance planning by balancing coverage (number of farms included in surveillance) against the desired level of confidence of including all farms that become infected in the next time period. Our results suggest that 100% of the farms that become infected in the next time period could be targeted in a surveillance program, although at a significant cost of including many false positives.

Tool for predicting Caligus rogercresseyi abundance on salt water salmon farms in Chile.

Caligus rogercresseyi is a host-dependent parasite that affects rainbow trout and Atlantic salmon in Chile. Numbers of sea lice on fish increase over time at relatively predictable rates when the environment is conducive to the parasite's survival and fish are not undergoing treatment. We developed a tool for the salmon industry in Chile that predicts the abundance of adult sea lice over time on farms that are relatively isolated. We used data on sea louse abundance collected through the SalmonChile INTESAL sea lice monitoring program to create series of weekly lice counts between lice treatment events on isolated farms. We defined isolated farms as those with no known neighbors within a 10 km seaway distance and no more than two neighbors within a 20 km seaway distance. We defined the time between sea lice treatments as starting the week immediately post treatment and ending the week before a subsequent treatment. Our final dataset of isolated farms consisted of 65 series from 32 farms, between 2009 and 2015. Given an observed abundance at time t = 0, we built a model that predicted 8 consecutive weekly sea louse abundance levels, based on the preceding week's lice prediction. We calibrated the parameters in our model on a randomly selected subset of training data, choosing the parameter combinations that minimized the absolute difference between the predicted and observed sea louse abundance values. We validated the parameters on the remaining, unseen, subset of data. We encoded our model and made it available as a Web-accessible applet for producers. We determined a threshold, based on the upper 97.5% predictive interval, as a guideline for producers using the tool. We hypothesize that if farms exceed this threshold, especially if the sea lice levels are above this threshold 2 and 4 weeks into the model predictions, the sea louse population on the farm is likely influenced by sources other than lice within the farm.

Determinants of health seeking behaviour following rabies exposure in Ethiopia.

The objective of this study was to identify factors that determine medical treatment seeking behaviour following potential rabies exposure after being bitten by a suspected dog and the likelihood of compliance to receive sufficient doses of post-exposure prophylaxis after the visit to a health centre visit. A detailed survey based on case investigation was conducted on suspected rabid dog bite cases in three areas of Ethiopia. Two multivariable logistic regression models were created with a set of putative variables to explain treatment seeking and compliance outcomes. Based on the registered bite cases at each health centre and the set of unregistered bite cases derived by contact tracing, 655 bite victim cases were identified to have occurred between September 2013 and August 2014. Of these evaluated bite incidences, 465 cases were considered to have been caused by a potentially rabid dog. About 77% of these suspected rabid dog bite victims visited a health centre, while 57% received sufficient doses of PEP. The overall likelihood of seeking medical services following rabies exposure was higher for people bitten by dogs of unknown ownership, where the bite was severe, being bitten on the leg, spend of more than 100 USD per month and where the victim lived close to the nearest health centre, while the likelihood of receiving sufficient doses of PEP was sensitive to monthly spending and distance to health centre. However, the evaluated factors did only explain a part of the variation among the three districts. The district in which victims lived appeared to have a relevant influence on the likelihood of seeking medical treatment but did not improve the prediction on the likelihood of treatment compliance. Given the insights obtained from this study, improvements in the rural districts with regard to accessibility of post-exposure prophylaxis delivering health centres in shorter distance could improve health seeking behaviour. In addition, in rural districts, majority of exposed persons who seek medical treatment tend to comply with treatment regimen, indicating that the promotion of medical treatment through awareness creation campaigns could be beneficial.

Effect of timing of count events on estimates of sea lice abundance and interpretation of effectiveness following bath treatments.

Effectiveness of sea lice bath treatment is often assessed by comparing pre- and post-treatment counts. However, in practice, the post-treatment counting window varies from the day of treatment to several days after treatment. In this study, we assess the effect of post-treatment lag time on sea lice abundance estimates after chemical bath treatment using data from the sea lice data management program (Fish-iTrends) between 2010 and 2014. Data on two life stages, (i) adult female (AF) and (ii) pre-adult and adult male (PAAM), were aggregated at the cage level and log-transformed. Average sea lice counts by post-treatment lag time were computed for AF and PAAM and compared relative to treatment day, using linear mixed models. There were 720 observations (treatment events) that uniquely matched pre- and post-treatment counts from 53 farms. Lag time had a significant effect on the estimated sea lice abundance, which was influenced by season and pre-treatment sea lice levels. During summer, sea lice were at a minimum when counted 1 day post-treatment irrespective of pre-treatment sea lice levels, whereas in the spring and autumn, low levels were observed for PAAM over a longer interval of time, provided the pre-treatment sea lice levels were >5-10.

Evaluating bath treatment effectiveness in the control of sea lice burdens on Atlantic salmon in New Brunswick, Canada.

The use of medicinal bath treatment for sea lice is becoming more common, due to increasing resistance to in-feed treatments with emamectin benzoate. Common treatment modalities in New Brunswick, Canada, include Salmosan administered by tarpaulin or wellboat, and Paramove administered by wellboat. In this study, we assessed the effectiveness of these treatment modalities in the field between 2010 and 2015 using a web-based sea lice data management system (Fish-iTrends© ). Effectiveness was evaluated for adult female (AF) and for pre-adult and adult male (PAAM) life stages separately. We also investigated the impact of variability in pretreatment lead and post-treatment lag time on effectiveness measures. There were 1185 treatment events at 57 farms that uniquely matched our pre- and post-treatment count criteria. The effectiveness of treatment modality was significantly influenced by season, pretreatment level of sea lice and by lead and lag times. In summer, Salmosan administered by tarpaulin had the greatest effectiveness on both AF and PAAM, when pretreatment levels were above 10 sea lice; whereas in autumn, the performance of treatment modalities varied significantly, depending on the pretreatment levels for the life stages. Ignoring the lead or lag time effect generally resulted in an underestimation of treatment effectiveness.

Variation in pre-treatment count lead time and its effect on baseline estimates of cage-level sea lice abundance.

Treatment efficacy studies typically use pre-treatment sea lice abundance as the baseline. However, the pre-treatment counting window often varies from the day of treatment to several days before treatment. We assessed the effect of lead time on baseline estimates, using historical data (2010-14) from a sea lice data management programme (Fish-iTrends). Data were aggregated at the cage level for three life stages: (i) chalimus, (ii) pre-adult and adult male and (iii) adult female. Sea lice counts were log-transformed, and mean counts by lead time relative to treatment day were computed and compared separately for each life stage, using linear mixed models. There were 1,658 observations (treatment events) from 56 sites in 5 Bay Management Areas. Our study showed that lead time had a significant effect on the estimated sea lice abundance, which was moderated by season. During the late summer and autumn periods, counting on the day of treatment gave significantly higher values than other days and would be a more appropriate baseline estimate, while during spring and early summer abundance estimates were comparable among counts within 5 days of treatment. A season-based lead time window may be most appropriate when estimating baseline sea lice levels.

One-Health Simulation Modelling: Assessment of Control Strategies Against the Spread of Influenza between Swine and Human Populations Using NAADSM.

Simulation models implemented using a range of parameters offer a useful approach to identifying effective disease intervention strategies. The objective of this study was to investigate the effects of key control strategies to mitigate the simultaneous spread of influenza among and between swine and human populations. We used the pandemic H1N1 2009 virus as a case study. The study population included swine herds (488 herds) and households-of-people (29,707 households) within a county in Ontario, Canada. Households were categorized as: (i) rural households with swine workers, (ii) rural households without swine workers and (iii) urban households without swine workers. Seventy-two scenarios were investigated based on a combination of the parameters of speed of detection and control strategies, such as quarantine strategy, effectiveness of movement restriction and ring vaccination strategy, all assessed at three levels of transmissibility of the virus at the swine-human interface. Results showed that the speed of detection of the infected units combined with the quarantine strategy had the largest impact on the duration and size of outbreaks. A combination of fast to moderate speed of the detection (where infected units were detected within 5-10 days since first infection) and quarantine of the detected units alone contained the outbreak within the swine population in most of the simulated outbreaks. Ring vaccination had no added beneficial effect. In conclusion, our study suggests that the early detection (and therefore effective surveillance) and effective quarantine had the largest impact in the control of the influenza spread, consistent with earlier studies. To our knowledge, no study had previously assessed the impact of the combination of different intervention strategies involving the simultaneous spread of influenza between swine and human populations.

Comparison of the h-Index Scores Among Pathogens Identified as Emerging Hazards in North America.

Disease surveillance must assess the relative importance of pathogen hazards. Here, we use the Hirsch index (h-index) as a novel method to identify and rank infectious pathogens that are likely to be a hazard to human health in the North American region. This bibliometric index was developed to quantify an individual's scientific research output and was recently used as a proxy measure for pathogen impact. Analysis of more than 3000 infectious organisms indicated that 651 were human pathogen species that had been recorded in the North American region. The h-index of these pathogens ranged from 0 to 584. The h-index of emerging pathogens was greater than non-emerging pathogens as was the h-index of frequently pathogenic pathogens when compared to non-pathogenic pathogens. As expected, the h-index of pathogens varied over time between 1960 and 2011. We discuss how the h-index can contribute to pathogen prioritization and as an indicator of pathogen emergence.

Analysis of Swine Movement in Four Canadian Regions: Network Structure and Implications for Disease Spread.

Direct and indirect contacts among animal holdings are important in the spread of infectious diseases. The objectives of this study were to describe networks of pig movements and the sharing of trucks used for those movements between swine farms in four Canadian regions using network analysis tools and to obtain contact parameters for infectious disease spread simulation models. Four months of swine movement data from a pilot pig traceability programme were used. Two types of networks were created using three time scales (weekly, monthly and the full study period): one-mode networks of farm-to-farm direct contact representing animal shipments and two-mode networks representing the sharing of trucks between farms. Contact patterns among farms were described by estimating a range of relevant network measures. The overall network neglecting the four regions consisted of 145 farms, which were connected by 261 distinct links. A total of 184 trucks were used to transport 2043 shipments of pigs during the study period. The median in- and out-degree for the overall one-mode network was 1 and ranged from 0 to 26 and 0 to 10, respectively. The overall one-mode network had heterogeneous degree distribution, a high clustering coefficient and shorter average path length than would be expected for randomly generated networks of similar size. On average one truck was shared by four farms in the overall network, or by three farms when considered the monthly and weekly networks. Degree distribution of the two-mode overall network demonstrated characteristics of power-law distribution. For more than 50% of shipments on any given day, the same truck was used for at least one other shipment. Findings from this study are in agreement with previous work, which suggested that swine movement networks exhibit small-world and scale-free topologies. Furthermore, trucks used for the shipment of pigs can play an important role in connecting otherwise unconnected farms and may increase the spread of disease.

One-Health Simulation Modelling: A Case Study of Influenza Spread between Human and Swine Populations using NAADSM.

The circulation of zoonotic influenza A viruses including pH1N1 2009 and H5N1 continue to present a constant threat to animal and human populations. Recently, an H3N2 variant spread from pigs to humans and between humans in limited numbers. Accordingly, this research investigated a range of scenarios of the transmission dynamics of pH1N1 2009 virus at the swine-human interface while accounting for different percentages of swine workers initially immune. Furthermore, the feasibility of using NAADSM (North American Animal Disease Spread Model) applied as a one-health simulation model was assessed. The study population included 488 swine herds and 29, 707 households of people within a county in Ontario, Canada. Households were categorized as follows: (i) rural households with swine workers, (ii) rural households without swine workers, and (iii) urban households without swine workers. Forty-eight scenarios were investigated, based on the combination of six scenarios around the transmissibility of the virus at the interface and four vaccination coverage levels of swine workers (0-60%), all under two settings of either swine or human origin of the virus. Outcomes were assessed in terms of stochastic 'die-out' fraction, size and time to peak epidemic day, overall size and duration of the outbreaks. The modelled outcomes indicated that minimizing influenza transmissibility at the interface and targeted vaccination of swine workers had significant beneficial effects. Our results indicate that NAADSM can be used as a framework to model the spread and control of contagious zoonotic diseases among animal and human populations, under certain simplifying assumptions. Further evaluation of the model is required. In addition to these specific findings, this study serves as a benchmark that can provide useful input to a future one-health influenza modelling studies. Some pertinent information gaps were also identified. Enhanced surveillance and the collection of high-quality information for more accurate parameterization of such models are encouraged.

Syndromic surveillance using laboratory test requests: a practical guide informed by experience with two systems.

Syndromic surveillance systems can enhance early disease warning, endemic disease monitoring, or help to accumulate proof of disease freedom. In order to provide immediate feedback to achieve these goals, the health data sources scanned should be acquired continuously, in an automated fashion, and should be stored electronically. Recognizing that data from diagnostic test requests often meet these requirements, two systems designed to automatically extract surveillance information from animal laboratory databases have been developed and are described in this paper. These systems are designed to contribute to early disease detection, as well as the timely management of epidemiological information, in a province of Canada and in Sweden, the areas served by the diagnostic laboratories concerned. Classifying in-coming requests into syndromes, the first step, was the most time-consuming and the least portable step between the two systems. The remaining steps were more easily adjusted from one system to implementation in the other. These steps included: retrospective evaluation of data to create baseline profiles following the removal of excessive noise and aberrations; the identification of temporal effects; prospective evaluation of detection algorithms; and finally real-time monitoring and implementation. Building upon the institutions' existing data management software, all steps to use those data for the purposes of syndromic surveillance were set up using open source software; as a result this approach could be readily adopted by other institutions. Relatively straight-forward development and maintenance is expected to lead to the incorporation of these systems into each institution's surveillance processes, becoming an indispensable tool for diagnosticians and epidemiologists, as well as stimulating further technical development of such systems.

Network analysis of swine shipments in Ontario, Canada, to support disease spread modelling and risk-based disease management.

Understanding contact networks are important for modelling and managing the spread and control of communicable diseases in populations. This study characterizes the swine shipment network of a multi-site production system in southwestern Ontario, Canada. Data were extracted from a company's database listing swine shipments among 251 swine farms, including 20 sow, 69 nursery and 162 finishing farms, for the 2-year period of 2006 to 2007. Several network metrics were generated. The number of shipments per week between pairs of farms ranged from 1 to 6. The medians (and ranges) of out-degree were: sow 6 (1-21), nursery 8 (0-25), and finishing 0 (0-4), over the entire 2-year study period. Corresponding estimates for in-degree of nursery and finishing farms were 3 (0-9) and 3 (0-12) respectively. Outgoing and incoming infection chains (OIC and IIC), were also measured. The medians (ranges) of the monthly OIC and IIC were 0 (0-8) and 0 (0-6), respectively, with very similar measures observed for 2-week intervals. Nursery farms exhibited high measures of centrality. This indicates that they pose greater risks of disease spread in the network. Therefore, they should be given a high priority for disease prevention and control measures affecting all age groups alike. The network demonstrated scale-free and small-world topologies as observed in other livestock shipment studies. This heterogeneity in contacts among farm types and network topologies should be incorporated in simulation models to improve their validity. In conclusion, this study provided useful epidemiological information and parameters for the control and modelling of disease spread among swine farms, for the first time from Ontario, Canada.

Understanding sources of sea lice for salmon farms in Chile.

The decline of fisheries over recent decades and a growing human population has coincided with an increase in aquaculture production. As farmed fish densities increase, so have their rates of infectious diseases, as predicted by the theory of density-dependent disease transmission. One of the pathogen that has increased with the growth of salmon farming is sea lice. Effective management of this pathogen requires an understanding of the spatial scale of transmission. We used a two-part multi-scale model to account for the zero-inflated data observed in weekly sea lice abundance levels on rainbow trout and Atlantic salmon farms in Chile, and to assess internal (farm) and external (regional) sources of sea lice infection. We observed that the level of juvenile sea lice was higher on farms that were closer to processing plants with fish holding facilities. Further, evidence for sea lice exposure from the surrounding area was supported by a strong positive correlation between the level of juvenile sea lice on a farm and the number of gravid females on neighboring farms within 30 km two weeks prior. The relationship between external sources of sea lice from neighboring farms and juvenile sea lice on a farm was one of the strongest detected in our multivariable model. Our findings suggest that the management of sea lice should be coordinated between farms and should include all farms and processing plants with holding facilities within a relatively large geographic area. Understanding the contribution of pathogens on a farm from different sources is an important step in developing effective control strategies.

Detection of emamectin benzoate tolerance emergence in different life stages of sea lice, Lepeophtheirus salmonis, on farmed Atlantic salmon, Salmo salar L.

Emamectin benzoate has been used to treat sea lice, Lepeophtheirus salmonis, infestations on farmed Atlantic salmon, Salmo salar. Recent evidence suggests a reduction in effectiveness in some locations. A major challenge in the detection of tolerance emergence can be the typically low proportion of resistant individuals in a population during the early phases. The objectives of this study were to develop a method for determining differences in temporal development of tolerance between sea lice life stages and to explore how these differences might be used to improve the monitoring of treatment effectiveness in a clinical setting. This study examined two data sets based on records of sea lice abundance following emamectin benzoate treatments from the west coast of Scotland (2002-2006) and from New Brunswick, Canada (2004-2008). Life stages were categorized into two groups (adult females and the remaining mobile stages) to examine the trends in mean abundance and treatment effectiveness. Differences in emamectin benzoate effectiveness were found between the two groups by year and location, suggesting that an important part of monitoring drug resistance development in aquatic ectoparasites may be the need to focus on key life stages.

A fixed-dose approach to conducting emamectin benzoate tolerance assessments on field-collected sea lice, Lepeophtheirus salmonis.

In New Brunswick, Canada, the sea louse, Lepeophtheirus salmonis, poses an on-going management challenge to the health and productivity of commercially cultured Atlantic salmon, Salmo salar. While the in-feed medication, emamectin benzoate (SLICE® ; Merck), has been highly effective for many years, evidence of increased tolerance has been observed in the field since late 2008. Although bioassays on motile stages are a common tool to monitor sea lice sensitivity to emamectin benzoate in field-collected sea lice, they require the collection of large numbers of sea lice due to inherent natural variability in the gender and stage response to chemotherapeutants. In addition, sensitive instruments such as EC(50) analysis may be unnecessarily complex to characterize susceptibility subsequent to a significant observed decline in efficacy. This study proposes an adaptation of the traditional, dose-response format bioassay to a fixed-dose method. Analysis of 657 bioassays on preadult and adult stages of sea lice over the period 2008-2011 indicated a population of sea lice in New Brunswick with varying degrees of susceptibility to emamectin benzoate. A seasonal and spatial effect was observed in the robustness of genders and stages of sea lice, which suggest that mixing different genders and stages of lice within a single bioassay may result in pertinent information being overlooked. Poor survival of adult female lice in bioassays, particularly during May/June, indicates it may be prudent to consider excluding this stage from bioassays conducted at certain times of the year. This work demonstrates that fixed-dose bioassays can be a valuable technique in detecting reduced sensitivity in sea lice populations with varying degrees of susceptibility to emamectin benzoate treatments.

Sea lice monitoring on Atlantic salmon farms in New Brunswick, Canada: comparing audit and farm staff counts.

Sea lice audits were performed by the Atlantic Veterinary College on commercial aquaculture sites in New Brunswick, Canada, in 2011. Although the primary objective was to verify that farms were reporting similar lice counts to third-party counts, more detailed comparisons were made to identify when lice counts were more likely to differ between the audit team and farm employees. A total of 28 sea lice audits were conducted on 16 sites between June and December 2011. During each audit, 10 cages were evaluated per site where possible, with ten fish per cage being evaluated by an audit technician and a further ten by a farm employee. Data analysis included descriptive statistics of lice counts by stage and limits of agreement plots. A random effects negative binomial model that accounted for clustering of cages within sites was applied to assess the effect of counter type and season on lice counts by stage. The results indicate that farms counts were generally in agreement with audit counts. However, when the average counts for chalimus and preadult (male and female) and adult male lice stages were high, farm counters were more likely to report a lower value. Higher lice counts were observed during autumn compared to summer especially for the adult female stage. Finally, there was a significant clustering effect for site and cage, with most of the variation attributable to site.

A review of simulation modelling approaches used for the spread of zoonotic influenza viruses in animal and human populations.

Increasing incidences of emerging and re-emerging diseases that are mostly zoonotic (e.g. severe acute respiratory syndrome, avian influenza H5N1, pandemic influenza) has led to the need for a multidisciplinary approach to tackling these threats to public and animal health. Accordingly, a global movement of 'One-Health/One-Medicine' has been launched to foster collaborative efforts amongst animal and human health officials and researchers to address these problems. Historical evidence points to the fact that pandemics caused by influenza A viruses remain a major zoonotic threat to mankind. Recently, a range of mathematical and computer simulation modelling methods and tools have increasingly been applied to improve our understanding of disease transmission dynamics, contingency planning and to support policy decisions on disease outbreak management. This review provides an overview of methods, approaches and software used for modelling the spread of zoonotic influenza viruses in animals and humans, particularly those related to the animal-human interface. Modelling parameters used in these studies are summarized to provide references for future work. This review highlights the limited application of modelling research to influenza in animals and at the animal-human interface, in marked contrast to the large volume of its research in human populations. Although swine are widely recognized as a potential host for generating novel influenza viruses, and that some of these viruses, including pandemic influenza A/H1N1 2009, have been shown to be readily transmissible between humans and swine, only one study was found related to the modelling of influenza spread at the swine-human interface. Significant gaps in the knowledge of frequency of novel viral strains evolution in pigs, farm-level natural history of influenza infection, incidences of influenza transmission between farms and between swine and humans are clearly evident. Therefore, there is a need to direct additional research to the study of influenza transmission dynamics in animals and at the animal-human interface.

Use of agent-based modelling to predict benefits of cleaner fish in controlling sea lice, Lepeophtheirus salmonis, infestations on farmed Atlantic salmon, Salmo salar L.

Sea lice, Lepeophtheirus salmonis, are ectoparasites of farmed and wild salmonids. Infestations can result in significant morbidity and mortality of hosts in addition to being costly to control. Integrated pest management programmes have been developed to manage infestations, and in some salmon farming areas, these programmes include the use of wrasse. Wrasse prey upon the parasitic life stages of L. salmonis and can be stocked on farms at varying densities. Despite considerable variation in the usage of wrasse, there are few quantitative estimates of how well they can control sea lice and how best to optimize their use. To explore at what densities wrasse should be stocked in order to meet specific control targets, we built an individual-based model that simulates sea lice infestation patterns on a representative salmonid host. Sea lice can be controlled through the use of chemical treatments as well as by wrasse predators. We found that the wrasse can effectively control sea lice, and the densities of wrasse needed for effective control depend upon the source of the infestation and the targeted level of control. Effective usage of wrasse can result in decreased use of chemical treatments and improved control of sea lice.