Performance and Cost-Efficiency of Single Hormonal Treatment Protocols in Tropical Anestrous Dairy Cows.

This retrospective study aimed to evaluate the performance of hormone treatment protocols, determine the factors associated with pregnancy success after hormone treatment, and compare the cost-efficiencies of two types of hormone treatment among cyclic and noncyclic anestrous dairy cows. The clinical records of 279 anestrous cows that received hormone treatment for artificial insemination (AI) from 64 herds in the western region of Thailand were obtained from Kasetsart University Veterinary Teaching Hospital from January to August 2017. The performance of the hormone treatment protocols, fixed-time AI (TAI) and estrus detection before AI (EAI), showed that the pregnancy risk for the TAI protocol was higher than that for the EAI protocol, but pregnancy per AI did not differ significantly between the two protocols in cyclic and noncyclic cows. Multivariate logistic regression analysis showed that cows receiving the TAI protocol were more likely to be pregnant compared to those treated with the EAI protocol. Cows with a 3.00 body condition score (BCS) < 3.75 after treatment and loose-housed cows were more likely to become pregnant. Treatment during winter showed higher pregnancy success than that in the summer and rainy seasons. The cost-efficiency analysis showed that the TAI protocol was the most cost-efficient option for noncyclic cows, whereas the EAI protocol was the most cost-efficient option for cyclic cows.

Development of simulation models for transmission of Salmonid Rickettsial Septicaemia between salt water fish farms in Chile.

This study aimed at estimating parameters representing between-farm transmission of Salmonid Rickettsial Septicaemia (SRS) in Chile, and developing and validating simulation models to predict weekly spread of SRS between farms in Los Lagos (Region 10), using InterSpread Plus. The model parameters were estimated by analyses of the historical SRS outbreak data. The models incorporated time and distance-dependent transmission kernels, representing the probabilities of waterborne spread of SRS between farms. Seven candidate transmission kernels were estimated, with varying maximum distance of between-farm SRS spread (15-60 km). Farms were categorized by size (small; medium; large) and species (Coho salmon; Atlantic salmon; rainbow trout). The time that it took a farm to recover from infection was parameterized to be shortest for small Coho farms (median: 7 weeks), followed by medium and large Coho farms (median: 25 weeks), Atlantic salmon farms (median: 42 weeks, any size) and rainbow trout farms (median: 43 weeks, any size). The relative infectiousness parameters of rainbow trout farms were 1.5-6.3 times that of Coho or Atlantic salmon, or those of large farms was 1.3-4.2 times that of small or medium farms. The models predicted SRS prevalence in Region 10 between 2013 and 2015 (79 weeks) with 76.5%-93.0% overall accuracy. The model with a transmission kernel of <20 km (P20) achieved a maximum overall accuracy (93.0%). Within each neighbourhood, the accuracy of P20 varied between 32.4% and 88.1%; 13/20 neighbourhoods had a reasonable temporal agreement between the simulated and actual dynamics of SRS (within 5th-95th percentiles), but 5/20 neighbourhoods underestimated and 2/20 overestimated the SRS spread. The model could be used for evaluation of semi-global control policies in Region 10, while addition of other factors such as seasonality, ocean currents, and movement of infected fish may improve the model performance at a finer scale.

Bayesian risk assessment model of human cryptosporidiosis cases following consumption of raw Eastern oysters (Crassostrea virginica) contaminated with Cryptosporidium oocysts in the Hillsborough River system in Prince Edward Island, Canada.

Cryptosporidium spp. has been associated with foodborne infectious disease outbreaks; however, it is unclear to what extent raw oyster consumption poses a risk to public health. Control of Cryptosporidium in shellfish harvest seawater in Canada is not mandatory and, despite relay/depuration processes, the parasite can remain viable in oysters for at least a month (depending on initial loads and seawater characteristics). Risks of human infection and illness from exposure to oysters contaminated with Cryptosporidium oocysts were assessed in a Bayesian framework. Two data sets were used: counts of oocysts in oysters harvested in Approved, Restricted, and Prohibited zones of the Hillsborough River system; and oocyst elimination rate from oysters exposed to oocysts in laboratory experiments. A total of 20 scenarios were assessed according to number of oysters consumed in a single serving (1, 10 and 30) and different relay times. The median probability of infection and developing cryptosporidiosis (e.g. illness) due to the consumption of raw oysters in Prince Edward Island was zero for all scenarios. However, the 95th percentiles ranged from 2% to 81% and from 1% to 59% for probability of infection and illness, respectively. When relay times were extended from 14 to 30 days and 10 oysters were consumed in one serving from the Restricted zones, these probabilities were reduced from 35% to 16% and from 15% to 7%, respectively. The 14-day relay period established by Canadian authorities for harvesting in Restricted zones seems prudent, though insufficient, as this relay period has been shown to be enough to eliminate fecal coliforms but not Cryptosporidium oocysts, which can remain viable in the oyster for over a month. Extending relay periods of 14 and 21 days for oysters harvested in Restricted zones to 30 days is likely insufficient to substantially decrease the probability of infection and illness. The highest risk was found for oysters that originated in Prohibited zones. Our findings suggest that Cryptosporidium oocysts are a potential cause of foodborne infection and illness when consuming raw oysters from Hillsborough River, one of the most important oyster production bays on Prince Edward Island. We discuss data gaps and limitations of this work in order to identify future research that can be used to reduce the uncertainties in predicted risks.

The Application of a Mathematical Model to Evaluate the Effectiveness of Control Strategies Against Ciona intestinalis in Mussel Production.

The Prince Edward Island (PEI) mussel industry has faced challenges associated with invasive tunicate species over the past two decades. Field experiments to find suitable mitigation strategies require considerable time and are resource intensive. This study demonstrates the application of a mathematical model to assess several control strategies against Ciona intestinalis populations under different temperature conditions in a mussel production area in PEI. A temperature dependent compartmental model was used to model the total abundance of C. intestinalis. Each mitigation strategy was defined in terms of a combination of timing and frequency of treatments. Various strategies were explored to obtain the combination that maximized the difference in predicted abundances between the control (untreated) and the different mitigation strategies. Treatment frequency was allowed to vary between one and four times over a given production year. The model was assessed under baseline conditions, which mimicked water temperatures from Georgetown Harbor, PEI, in 2008; as well as under scenarios that reflected prolonged summer or warm spring temperatures. Furthermore, the sensitivity of the model to variations in presumed treatment efficacy was evaluated. The use of all four available treatments, starting around the first week of July and correctly timed thereafter, provided the most effective strategy, assuming the baseline temperature scenario. However, the effectiveness of this mitigation strategy depended on temperature conditions. The mathematical model developed in this study allows decision makers to explore different strategies to control the abundance of C. intestinalis in mussel production areas under different environmental conditions. In addition, the modeling framework developed could be adapted to simulate comparable ectoparasitic infestation in aquatic environments.

Association between sea lice (Lepeophtheirus salmonis) infestation on Atlantic salmon farms and wild Pacific salmon in Muchalat Inlet, Canada.

Growth in salmon aquaculture over the past two decades has raised concerns regarding the potential impacts of the industry on neighboring ecosystems and wild fish productivity. Despite limited evidence, sea lice have been identified as a major cause for the decline in some wild Pacific salmon populations on the west coast of Canada. We used sea lice count and management data from farmed and wild salmon, collected over 10 years (2007-2016) in the Muchalat Inlet region of Canada, to evaluate the association between sea lice recorded on salmon farms with the infestation levels on wild out-migrating Chum salmon. Our analyses indicated a significant positive association between the sea lice abundance on farms and the likelihood that wild fish would be infested. However, increased abundance of lice on farms was not significantly associated with the levels of infestation observed on the wild salmon. Our results suggest that Atlantic salmon farms may be an important source for the introduction of sea lice to wild Pacific salmon populations, but that the absence of a dose response relationship indicates that any estimate of farm impact requires more careful evaluation of causal inference than is typically seen in the extant scientific literature.

Space-time cluster analysis of sea lice infestation (Caligus clemensi and Lepeophtheirus salmonis) on wild juvenile Pacific salmon in the Broughton Archipelago of Canada.

Sea lice infestation levels on wild chum and pink salmon in the Broughton Archipelago region are known to vary spatially and temporally; however, the locations of areas associated with a high infestation level had not been investigated yet. In the present study, the multivariate spatial scan statistic based on a Poisson model was used to assess spatial clustering of elevated sea lice (Caligus clemensi and Lepeophtheirus salmonis) infestation levels on wild chum and pink salmon sampled between March and July of 2004 to 2012 in the Broughton Archipelago and Knight Inlet regions of British Columbia, Canada. Three covariates, seine type (beach and purse seining), fish size, and year effect, were used to provide adjustment within the analyses. The analyses were carried out across the five months/datasets and between two fish species to assess the consistency of the identified clusters. Sea lice stages were explored separately for the early life stages (non-motile) and the late life stages of sea lice (motile). Spatial patterns in fish migration were also explored using monthly plots showing the average number of each fish species captured per sampling site. The results revealed three clusters for non-motile C. clemensi, two clusters for non-motile L. salmonis, and one cluster for the motile stage in each of the sea lice species. In general, the location and timing of clusters detected for both fish species were similar. Early in the season, the clusters of elevated sea lice infestation levels on wild fish are detected in areas closer to the rivers, with decreasing relative risks as the season progresses. Clusters were detected further from the estuaries later in the season, accompanied by increasing relative risks. In addition, the plots for fish migration exhibit similar patterns for both fish species in that, as expected, the juveniles move from the rivers toward the open ocean as the season progresses The identification of space-time clustering of infestation on wild fish from this study can help in targeting investigations of factors associated with these infestations and thereby support the development of more effective sea lice control measures.

Sea lice infestations on juvenile chum and pink salmon in the Broughton Archipelago, Canada, from 2003 to 2012.

Juvenile pink salmon Oncorhynchus gorbuscha and chum salmon O. keta were sampled by beach or purse seine to assess levels of sea lice infestation in the Knight Inlet and Broughton Archipelago regions of coastal British Columbia, Canada, during the months of March to July from 2003 to 2012. Beach seine data were analyzed for sea lice infestation that was described in terms of prevalence, abundance, intensity, and intensity per unit length. The median annual prevalence for chum was 30%, ranging from 14% (in 2008 and 2009) to 73% (in 2004), while for pink salmon, the median was 27% and ranged from 10% (in 2011) to 68% (in 2004). Annual abundance varied from 0.2 to 5 sea lice per fish with a median of 0.47 for chum and from 0.1 to 3 lice (median 0.42) for pink salmon. Annual infestation followed broadly similar trends for both chum and pink salmon. However, the abundance and intensity of Lepeophtheirus salmonis and Caligus clemensi, the 2 main sea lice species of interest, were significantly greater on chum than on pink salmon in around half of the years studied. Logistic regression with random effect was used to model prevalence of sea lice infestation for the combined beach and purse seine data. The model suggested inter-annual variation as well as a spatial clustering effect on the prevalence of sea lice infestation in both chum and pink salmon. Fish length had an effect on prevalence, although the nature of this effect differed according to host species.