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Of the 3,500 species of mosquitoes worldwide, only a small portion carry and transmit the mosquito-borne diseases (MBDs) that cause approximately half a million deaths annually worldwide. The most common exotic MBDs, such as malaria and dengue, are not currently established in Canada, in part because of our relatively harsh climate; however, this situation could evolve with climate change. Mosquitoes native to Canada may become infected with new pathogens and move into new regions within Canada. In addition, new mosquito species may move into Canada from other countries, and these exotic species may bring exotic MBDs as well. With high levels of international travel, including to locations with exotic MBDs, there will be more travel-acquired cases of MBDs. With climate change, there is the potential for exotic mosquito populations to become established in Canada. There is already a small area of Canada where exotic Aedes mosquitoes have become established although, to date, there is no evidence that these carry any exotic (or already endemic) MBDs. The increased risks of spreading MBDs, or introducing exotic MBDs, will need a careful clinical and public health response. Clinicians will need to maintain a high level of awareness of current trends, to promote mosquito bite prevention strategies, and to know the laboratory tests needed for early detection and when to report laboratory results to public health. Public health efforts will need to focus on ongoing active surveillance, public and professional awareness and mosquito control. Canadians need to be aware of the risks of acquiring exotic MBDs while travelling abroad as well as the risk that they could serve as a potential route of introduction for exotic MBDs into Canada when they return home.

Rabies occurs throughout the Arctic, representing an ongoing public health concern for residents of northern communities. The Arctic fox (Vulpes lagopus) is the main reservoir of the Arctic rabies virus variant, yet little is known about the epidemiology of Arctic rabies, such as the ecological mechanisms driving where and when epizootics in fox populations occur. In this study, we provide the first portrait of the spatio-temporal spread of rabies across northern Canada. We also explore the impact of seasonal and multiannual dynamics in Arctic fox populations and climatic factors on rabies transmission dynamics. We analysed data on rabies cases collected through passive surveillance systems in the Yukon, Northwest Territories, Nunavut, Nunavik and Labrador from 1953 to 2014. In addition, we analysed a large and unique database of trapped foxes tested for rabies in the Northwest Territories and Nunavut from 1974 to 1984 as part of active surveillance studies. Rabies cases occurred in all Arctic regions of Canada and were relatively synchronous among foxes and dogs (Canis familiaris). This study highlights the spread of Arctic rabies virus variant across northern Canada, with contrasting rabies dynamics between different yet connected areas. Population fluctuations of Arctic fox populations could drive rabies transmission dynamics in a complex way across northern Canada. Furthermore, this study suggests different impacts of climate and sea ice cover on the onset of rabies epizootics in northern Canada. These results lay the groundwork for the development of epidemiological models to better predict the spatio-temporal dynamics of rabies occurrence in both wild and domestic carnivores, leading to better estimates of human exposure and transmission risk.

Advancements in artificial intelligence (AI), more precisely the subfield of machine learning, and their applications to open-source internet data, such as social media, are growing faster than the management of ethical issues for use in society. An ethical framework helps scientists and policy makers consider ethics in their fields of practice, legitimize their work and protect members of the data-generating public. A central question for advancing the ethical framework is whether or not Tweets, Facebook posts and other open-source social media data generated by the public represent a human or not. The objective of this paper is to highlight ethical issues that the public health sector will be or is already confronting when using social media data in practice. The issues include informed consent, privacy, anonymization and balancing these issues with the benefits of using social media data for the common good. Current ethical frameworks need to provide guidance for addressing issues arising from the use of social media data in the public health sector. Discussions in this area should occur while the application of open-source data is still relatively new, and they should also keep pace as other problems arise from ongoing technological change.

Animal movement influences the spatial spread of wildlife infectious diseases through host-host contact structure and hence pathogen transmission. Wildlife disease hosts vary in characteristics related to pathogen transmission, which can increase the spread and intensity of disease outbreaks. The consequences of home range size variation on wildlife disease dynamics are poorly understood, but could help to predict disease spread and determine more effective disease management strategies.We developed a spatially-explicit individual-based model to examine the effect of variation in host home range size on the spatial spread rate, persistence, and incidence of rabies virus (RABV) in raccoons (Procyon lotor). We tested the hypothesis that host home range area variation decreases vaccination effectiveness in wildlife host populations following pathogen invasion into a vaccination zone.We simulated raccoon demography and RABV dynamics across a range of magnitudes and variances in weekly home range radius distributions for raccoons, and compared results to conditions that assumed a fixed host home range area. We examined how variable host home range radius distributions influenced the relative effectiveness of three components of orally-baited raccoon RABV vaccination (ORV) programs—timing and frequency of bait delivery, width of the zone where ORV baits were delivered, and proportion of hosts immunized.Variability in home range radius distributions increased RABV spread rates by 1.2 - 5.2-fold compared to simulations with fixed radii. More variable host home range radius distributions decreased relative vaccination effectiveness by 71% compared to less variable host home range radius distributions under conventional vaccination conditions. We found that vaccination timing was more influential for vaccination effectiveness than vaccination frequency or vaccination zone width.Our results suggest that variation in wildlife home range exploration increases the spatial spread and incidence of wildlife disease. Our vaccination results underscore the importance of prioritizing individual-level space use data collection to understand the dynamics of wildlife diseases and plan their effective control and elimination.

We applied the model-guided fieldwork framework to the Caribbean mongoose rabies system by parametrizing a spatially-explicit, individual-based model, and by performing an uncertainty analysis designed to identify parameters for which additional empirical data are most needed. Our analysis revealed important variation in output variables characterizing rabies dynamics, namely rabies persistence, exposure level, spatiotemporal distribution, and prevalence. Among epidemiological parameters, rabies transmission rate was the most influential, followed by rabies mortality and location, and size of the initial infection. The most influential landscape parameters included habitat-specific carrying capacities, landscape heterogeneity, and the level of resistance to dispersal associated with topography. Movement variables, including juvenile dispersal, adult fine-scale movement distances, and home range size, as well as life history traits such as age of independence, birth seasonality, and age- and sex-specific mortality were other important drivers of rabies dynamics. We discuss results in the context of mongoose ecology and its influence on disease transmission dynamics. Finally, we suggest empirical approaches and study design specificities that would provide optimal contributing data addressing the knowledge gaps identified by our approach, and would increase our potential to use epidemiological models to guide mongoose rabies control and management in the Caribbean.

The robust estimate and forecast capability of random forests (RF) has been widely recognized, however this ensemble machine learning method has not been widely used in mosquito-borne disease forecasting. In this study, two sets of RF models were developed at the national (pooled department-level data) and department level in Colombia to predict weekly dengue cases for 12-weeks ahead. A pooled national model based on artificial neural networks (ANN) was also developed and used as a comparator to the RF models. The various predictors included historic dengue cases, satellite-derived estimates for vegetation, precipitation, and air temperature, as well as population counts, income inequality, and education. Our RF model trained on the pooled national data was more accurate for department-specific weekly dengue cases estimation compared to a local model trained only on the department’s data. Additionally, the forecast errors of the national RF model were smaller to those of the national pooled ANN model and were increased with the forecast horizon increasing from one-week-ahead (mean absolute error, MAE: 9.32) to 12-weeks ahead (MAE: 24.56). There was considerable variation in the relative importance of predictors dependent on forecast horizon. The environmental and meteorological predictors were relatively important for short-term dengue forecast horizons while socio-demographic predictors were relevant for longer-term forecast horizons. This study demonstrates the potential of RF in dengue forecasting with a feasible approach of using a national pooled model to forecast at finer spatial scales. Furthermore, including sociodemographic predictors is likely to be helpful in capturing longer-term dengue trends., Author summary Dengue virus has the highest disease burden of all mosquito-borne viral diseases, infecting 390 million people annually in 128 countries. Forecasting is an important warning mechanism that can help with proactive planning and response for clinical and public health services. In this study, we compare two different machine learning approaches to dengue forecasting: random forest (RF) and artificial neural networks (ANN). National (pooling across all departments) and local (department-specific) models were compared and used to predict future dengue cases in Colombia. In Colombia, the departments are administrative divisions formed by a grouping of municipalities. The results demonstrated that the counts of future dengue cases were more accurately estimated by RF than by ANN. It was also shown that environmental and meteorological predictors were more important for forecast accuracy for shorter-term forecasts while socio-demographic predictors were more important for longer-term forecasts. Finally, the national pooled model applied to local data was more accurate in dengue forecasting compared to the department-specific model. This research contributes to the field of disease forecasting and highlights different considerations for future forecasting studies.

Lyme disease, the most commonly reported vector-borne disease in North America, is caused by the spirochete Borrelia burgdorferi sensu stricto, which is transmitted by Ixodes scapularis in eastern Canada and Ixodes pacificus in western Canada. Recently, the northward range expansion of I. scapularis ticks, in south-eastern Canada, has resulted in a dramatic increase in the incidence of human Lyme disease. Detecting emerging areas of Lyme disease risk allows public health to target disease prevention efforts. We analysed passive tick surveillance data from Ontario and Manitoba to i) assess the relationship between the total numbers of I. scapularis submissions in passive surveillance from humans, and the number of human Lyme disease cases, and ii) develop province-specific acarological indicators of risk that can be used to generate surveillance-based risk maps. We also assessed associations between numbers of nymphal I. scapularis tick submissions only and Lyme disease case incidence. Using General Estimating Equation regression, the relationship between I. scapularis submissions (total numbers and numbers of nymphs only) in each census sub-division (CSD) and the number of reported Lyme disease cases was positively correlated and highly significant in the two provinces (P ≤ 0.001). The numbers of I. scapularis submissions over five years discriminated CSDs with ≥ 3 Lyme disease cases from those with < 3 cases with high accuracy when using total numbers of tick submission (Receiver Operating Characteristics area under the curve [AUC] = 0.89) and moderate accuracy (AUC = 0.78) when using nymphal tick submissions only. In Ontario the optimal cut-off point was a total 12 tick submissions from a CSD over five years (Sensitivity = 0.82, Specificity = 0.84), while in Manitoba the cut-off point was five ticks (Sensitivity = 0.71, Specificity = 0.79) suggesting regional variability of the risk of acquiring Lyme disease from an I. scapularis bite. The performances of the acarological indicators developed in this study for Ontario and Manitoba support the ability of passive tick surveillance to provide an early signal of the existence Lyme disease risk areas in regions where ticks and the pathogens they transmit are expanding their range.

Animal movement influences the spatial spread of directly transmitted wildlife disease through host–host contact structure. Wildlife disease hosts vary in home range‐associated foraging and social behaviours, which may increase the spread and intensity of disease outbreaks. The consequences of variation in host home range movement and space use on wildlife disease dynamics are poorly understood, but could help to predict disease spread and determine more effective disease management strategies.We developed a spatially explicit individual‐based model to examine the effect of spatiotemporal variation in host home range size on the spatial spread rate, persistence and incidence of rabies virus (RABV) in raccoons (Procyon lotor). We tested the hypothesis that variation in home range size increases RABV spread and decreases vaccination effectiveness in host populations following pathogen invasion into a vaccination zone.We simulated raccoon demography and RABV dynamics across a range of magnitudes and variances in weekly home range size for raccoons. We examined how variable home range size influenced the relative effectiveness of three components of oral rabies vaccination (ORV) programmes targeting raccoons—timing and frequency of bait delivery, width of the ORV zone and proportion of hosts immunized.Variability in weekly home range size increased RABV spread rates by 1.2‐fold to 5.2‐fold compared to simulations that assumed a fixed home range size. More variable host home range sizes decreased relative vaccination effectiveness by 71% compared to less variable host home range sizes under conventional vaccination conditions. We found that vaccination timing was more influential for vaccination effectiveness than vaccination frequency or vaccination zone width.Our results suggest that variation in wildlife home range movement behaviour increases the spatial spread and incidence of RABV. Our vaccination results underscore the importance of prioritizing individual‐level space use and movement data collection to understand wildlife disease dynamics and plan their effective control and elimination., The authors developed a spatially explicit model of raccoon population and rabies virus infection dynamics, and show that variation in host home range size increases rabies spread and incidence, decreasing the population‐level effectiveness of oral rabies vaccination. The results underscore the importance of host movement and space use heterogeneity on disease dynamics and elimination efforts.

Seagrasses are ecosystem engineers of essential marine habitat. Their populations are rapidly declining worldwide. One potential cause of seagrass population declines is wasting disease, which is caused by opportunistic pathogens in the genus Labyrinthula. While infection with these pathogens is common in seagrasses, theory suggests that disease only occurs when environmental stressors cause immunosuppression of the host. Recent evidence suggests that host factors may also contribute to disease caused by opportunistic pathogens. In order to quantify patterns of disease, identify risk factors, and investigate responses to infection, we surveyed shoot density, shoot length, epiphyte load, production of plant defenses (phenols), and wasting disease prevalence in eelgrass Zostera marina across 11 sites in the central Salish Sea (Washington state, USA), a region where both wasting disease and eelgrass declines have been documented. Wasting disease was diagnosed by the presence of necrotic lesions, and Labyrinthula cells were identified with histology. Disease prevalence among sites varied from 6 to 79%. The probability of a shoot being diseased was higher in longer shoots, in patches of higher shoot density, and in shoots with higher levels of biofouling from epiphytes. Phenolic concentration was higher in diseased leaves. We hypothesize that this results from the induction of phenols during infection. Additional research is needed to evaluate whether phenols are an adaptive defense against Labyrinthula infection. The high site-level variation in disease prevalence emphasizes the potential for wasting disease to be causing some of the observed decline in eelgrass beds.

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.

Acquiring antimicrobial-resistant (AMR) bacteria through consuming contaminated animal food products is an emerging public health concern, though the sources of contamination are not always clear. This study characterized the occurrence of AMR in Escherichia coli from bivalve molluscs and assessed for the possible sources in the Hillsborough river complex of Prince Edward Island, Canada in areas overlapping with an oyster fishery. Multivariable statistical analysis indicated that the probability of detecting E. coli increased as the estimated dosage of animal effluent contamination decreased. Isolates with AMR were only found from sampling sites closest to untreated human effluent sources. Twenty-seven percent (n=6 of 22) of the isolates were pathogenic, with virulence factors consistent with extraintestinal E. coli of human origin. Though there is more evidence of contamination arising from human effluent, more research is needed to identify driving sources.

Background: The risk of contracting Lyme disease (LD) can vary spatially because of spatial heterogeneity in risk factors such as social-behavior and exposure to ecological risk factors. Integrating these risk factors to inform decision-making should therefore increase the effectiveness of mitigation interventions. Objectives: The objective of this study was to develop an integrated social-behavioral and ecological risk-mapping approach to identify priority areas for LD interventions. Methods: The study was conducted in the Montérégie region of Southern Quebec, Canada, where LD is a newly endemic disease. Spatial variation in LD knowledge, risk perceptions, and behaviors in the population were measured using web survey data collected in 2012. These data were used as a proxy for the social-behavioral component of risk. Tick vector population densities were measured in the environment during field surveillance from 2007 to 2012 to provide an index of the ecological component of risk. Social-behavioral and ecological components of risk were combined with human population density to create integrated risk maps. Map predictions were validated by testing the association between high-risk areas and the current spatial distribution of human LD cases. Results: Social-behavioral and ecological components of LD risk had markedly different distributions within the study region, suggesting that both factors should be considered for locally adapted interventions. The occurrence of human LD cases in a municipality was positively associated with tick density (p

Zika virus (ZIKV) infection is emerging globally, currently causing outbreaks in the Caribbean, and Central and South America, and putting travellers to affected countries at risk. Model-based estimates for the basic reproduction number (R 0 ) of ZIKV in affected Caribbean and Central and South American countries, obtained from 2015 to 2016 human case surveillance data, were compared by logistic regression and Receiver-Operating Characteristic (ROC), with the prevalence of ZIKV-positive test results in Canadians who travelled to them. Estimates of R 0 for each country were a good predictor of the ZIKV test result (ROC area under the curve = 0.83) and the odds of testing positive was 11-fold greater for travellers visiting countries with estimated R 0 ≥ 2.76, compared to those visiting countries with R 0

Chronic wasting disease (CWD) is a fatal disease of North American cervids that was first detected in a wild, hunter-shot deer in Saskatchewan along the border with Alberta in Canada in 2000. Spatially explicit models for assessing factors affecting disease detection are needed to guide surveillance and control programs. Spatio-temporal patterns in CWD prevalence can be complicated by variation in individual infection probability and sampling biases. We assessed hunter harvest data of mule deer (Odocoileus hemionus) and white-tailed deer (Odocoileus virginianus) during the early phases of an outbreak in Saskatchewan (i.e., 2002-2007) for targeting the detection of CWD by defining (1) where to look, and (2) how much effort to use. First, we accounted for known demographic heterogeneities in infection to model the probability, P(E), that a harvested deer was infected with CWD given characteristics of the harvest location. Second, in areas where infected deer were harvested we modelled the probability, P(D), of the hunter harvest re-detecting CWD within sample units of varying size (9-54 km(2)) given the demographics of harvested deer and time since first detection in the study area. Heterogeneities in host infection were consistent with those reported elsewhere: mule deer 3.7 timeswhite-tailed deer, males 1.8 timesfemales, and quadratically related to age in both sexes. P(E) increased with number of years since the first detection in our study area (2002) and proximity to known disease sources, and also varied with distance to the South Saskatchewan River and small creek drainages, terrain ruggedness, and extent of agriculture lands within a 3 km radius of the harvest. The majority (75%) of new CWD-positive deer from our sample were found within 20 km of infected deer harvested in the previous year, while approximately 10% were greater than 40 km. P(D) modelled at 18 km(2) was best supported, but for all scales, P(D) depended on the number of harvested deer and time since the first infected deer was harvested. Within an 18 km(2) sampling unit, there was an 80% probability of detecting a CWD-positive deer with 16 harvested deer five years after the initial infected harvest. Identifying where and how much to sample to detect CWD can improve targeted surveillance programs early in the outbreak of the disease when based on hunter harvest.

Data from wildlife disease surveillance programs are used to inform implementation of disease control (e.g., vaccination, population reduction) in space and time. We developed an approach to increase detection of raccoon rabies in raccoons (Procyon lotor) and skunks (Mephitis mephitis) of Quebec, Canada, and we examined the implications of using this approach for targeted surveillance. First we modeled the probability of sampling a rabid animal relative to environmental characteristics of sampling locations. Rabid animals were more likely to be found in low-lying flat landscapes that had higher proportions of corn-forest edge habitat and hay agriculture, and that were within 20 km of one or more known rabies cases. From the model, we created 2 complementary risk maps to identify areas where rabid animals were most likely to be sampled. One map accounted for habitat and known rabies case locations, and can be used to define an infection zone from which surveillance can be targeted along the periph...

A landscape genetic simulation modelling approach is used to understand factors affecting raccoon rabies disease spread in southern Ontario, Canada. Using the Ontario Rabies Model, we test the hypothesis that landscape configuration (shape of available habitat) affects dispersal, as indicated by genetic structuring. We simulated range expansions of raccoons from New York into vacant landscapes in Ontario, in two areas that differed by the presence or absence of a landscape constriction. Our results provide theoretical evidence that landscape constriction acts as a vicariant bottleneck. We discuss implications for raccoon rabies spread.

Epidemiological models are useful tools for management to predict and control wildlife disease outbreaks. Dispersal behaviours of the vector are critical in determining patterns of disease spread, and key variables in epidemiological models, yet they are difficult to measure. Raccoon rabies is enzootic over the eastern seaboard of North America and management actions to control its spread are costly. Understanding dispersal behaviours of raccoons can contribute to refining management protocols to reduce economic impacts. Here, estimates of dispersal were obtained through parentage and spatial genetic analyses of raccoons in two areas at the front of the raccoon rabies epizootic in Ontario; Niagara (N = 296) and St Lawrence (N = 593). Parentage analysis indicated the dispersal distance distribution is highly positively skewed with 85% of raccoons, both male and female, moving < 3 km. The tail of this distribution indicated a small proportion (< 4%) moves more than 20 km. Analysis of spatial genetic structure provided a similar assessment as the spatial genetic correlation coefficient dropped sharply after 1 km. Directionality of dispersal would have important implications for control actions; however, evidence of directional bias was not found. Separating the data into age and sex classes the spatial genetic analyses detected female philopatry. Dispersal distances differed significantly between juveniles and adults, while juveniles in the Niagara region were significantly more related to each other than adults were to each other. Factors that may contribute to these differences include kin association, and spring dispersal. Changes to the timing and area covered by rabies control operations in Ontario are indicated based on these dispersal data.

Piscirickettsiosis (SRS) is an endemic bacterial disease of high economic importance and is the primary reason for antibiotic usage in the aquaculture industry in Chile. Understanding the epidemiology of this disease is important in order to develop better control strategies for the Chilean aquaculture industry. The objectives of this project were to 1) describe the epidemiology of SRS on Atlantic salmon and rainbow trout farms, and 2) to identify factors that impact the severity of SRS outbreaks. Special attention was given to vaccine strategies currently used by the industry. Production data from 14 Atlantic salmon farms (252 cages) and 11 rainbow trout farms (216 cages) that had completed their production cycles between 2010 and 2012 were investigated. Regression models were used to evaluate time-to-first outbreak of SRS and total mortality attributed to SRS mortality. The factors evaluated in our models were: vaccine type (control and 5 vaccines), smolt weight and cumulative mortality within the first 4 weeks in saltwater, season of smolt introduction, infection with other pathogens during the production cycle, SRS treatments, and total number of sea lice treatments. The prevalence of SRS-affected cages on infected farms was high for both species; however, outbreaks appeared more severe (i.e. higher mortalities) on rainbow trout farms. Onset of SRS outbreaks was, on average, for fish in different vaccine groups, between 2480 degree-days (dd) and 3829 dd for Atlantic salmon, and between 1696 dd and 2241 dd for rainbow trout. For both species, none of the vaccines evaluated completely prevented SRS, although there were significant variations in the time-to-first outbreak and the severity of SRS outbreaks associated with vaccines after controlling for farm effect and other predictors. Specifically, a booster vaccine strategy in Atlantic salmon had significantly lower mortalities associated with SRS and a delay in the onset of disease compared to several of the other vaccines evaluated. Whether the differences observed between vaccines are economically significant is unknown. In rainbow trout, time-to-first outbreak was significantly delayed for vaccinated fish compared to the unvaccinated fish after we controlled for other factors in our model; however, total SRS mortality of vaccinated rainbow trout was not significantly different than unvaccinated rainbow trout. Consistent for both species was that mortality during the first 4 weeks post-salt water entry was associated with time-to-outbreak of SRS, and this effect was dependent on the vaccine used.

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 de - scribed 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.

Multiple control methods have been used in North America to manage the spread of rabies caused by the raccoon (Procyon lotor) rabies virus variant (RRVV). Recently, oral vaccination with ONRAB(®) vaccine baits, which contain an adenovirus rabies glycoprotein recombinant, has been made available as an additional tool for rabies control. Our objectives were to estimate rabies antibody prevalence in wild-caught raccoons and striped skunks (Mephitis mephitis), and identify factors influencing the probability of being antibody positive at the individual level in these species, following oral rabies vaccination (ORV) campaigns in which ONRAB was distributed aerially in 2007-2009 in southern Québec, Canada. Following the aerial distribution of 43-155 ONRAB baits/km(2), the annual percentages of antibody-positive raccoons and skunks varied between 35% and 56% and 11% and 17%, respectively. In raccoons, the probability of being antibody positive was positively associated with age and density of ONRAB distributed, and influenced by the number of previous ORV campaigns conducted. Conversely, this probability was negatively associated with estimated abundance of raccoons in the trapping cell and proportion of residential areas near the raccoon capture location. None of the variables examined explained variation in the probability of being antibody positive in skunks. Our results indicate that the ONRAB density applied during ORV campaigns should be adjusted to account for variations in raccoon population density and presence of residential areas to increase the likelihood of creating an effective immunological barrier against RRVV. The high percentage of juvenile raccoons (annual mean =45 ± 3 [SE]%) and skunks (66 ± 2%) captured during post-ORV monitoring suggests that ORV campaigns should be conducted at least annually to account for the recruitment of naïve individuals into the populations. In Québec, the increasing use of ONRAB coincided with the elimination of rabies caused by RRVV. Nonetheless, our results indicate that improvements to this vaccine bait and/or the distribution techniques are required to increase its efficacy, especially in striped skunks.

This chapter reviews the evidence for the impact of natural and anthropogenic barriers on the spread of rabies using evidence mainly drawn from the epidemics of fox and raccoon variant rabies virus over the past 60 years in North America. Those barriers have both directed and inhibited the spread of rabies and, at a regional scale, have been integrated with rabies control efforts in North America. Few studies have been done, however, to examine how the texture (grain) and configuration of the habitat at finer scales affect rabies control, particularly the massive oral vaccination campaigns in operation along the Atlantic coast and southeastern Canada (Ontario, Quebec, New Brunswick). To explore these questions, the authors used stochastic simulation. The model of choice was the Ontario Rabies Model (ORM) adapted for use on the high performance computing resources network in Quebec (RQCHP—Reseau quebecois de calcul de haute performance; http://rqchp.qc.ca ). The combination of the ORM and RQCHP allowed us to run many thousands of experiments to explore interactions between nine landscape grain/configuration combinations and vaccination barriers with varying widths and immunity levels. Our results show that breaches of vaccine barriers increase as the grain size of the landscape increases and as the landscape becomes more structured. We caution that mid levels of vaccination can be counterproductive resulting in rabies persistence rather than control. We also note that our model/computing system has the flexibility and capacity to explore a wide range of questions pertinent to improving the efficacy of rabies control.

The correlation of landscape features with genetic discontinuities reveals barriers to dispersal that can contribute to understanding present and future spread of wildlife diseases. This knowledge can then be used for targeting control efforts. The impact of natural barriers on raccoon dispersal was assessed through genetic analysis of samples from two regions, Niagara (N = 666) and St. Lawrence (N = 802). These areas are transected by major rivers and are at the northern front of a raccoon rabies epizootic. Genetic clusters were identified in each region using Bayesian clustering algorithms. In the Niagara region, two clusters were identified corresponding to either side of the Niagara River. For the St. Lawrence region, spatially congruent clusters were not identified, despite the presence of the intervening St. Lawrence River. These genetic data are consistent with raccoon rabies incidence data where rabies has been detected across the St. Lawrence River in Ontario while no cases have been detected in Ontario across the Niagara River. This is despite expectations of rabies incidence in Niagara before the St. Lawrence based on the progression of rabies from New York. The results from the two regions suggest different permeabilities to raccoons between New York and Ontario that may be attributed to the rivers. However, other factors have also been explored that could contribute to this difference between these study sites including the shape of the landscape and resource distribution.

Background Protection of public health from rabies is informed by the analysis of surveillance data from human and animal populations. In Canada, public health, agricultural and wildlife agencies at the provincial and federal level are responsible for rabies disease control, and this has led to multiple agency-specific data repositories. Aggregation of agency-specific data into one database application would enable more comprehensive data analyses and effective communication among participating agencies. In Québec, RageDB was developed to house surveillance data for the raccoon rabies variant, representing the next generation in web-based database applications that provide a key resource for the protection of public health. Results RageDB incorporates data from, and grants access to, all agencies responsible for the surveillance of raccoon rabies in Québec. Technological advancements of RageDB to rabies surveillance databases include 1) automatic integration of multi-agency data and diagnostic results on a daily basis; 2) a web-based data editing interface that enables authorized users to add, edit and extract data; and 3) an interactive dashboard to help visualize data simply and efficiently, in table, chart, and cartographic formats. Furthermore, RageDB stores data from citizens who voluntarily report sightings of rabies suspect animals. We also discuss how sightings data can indicate public perception to the risk of racoon rabies and thus aid in directing the allocation of disease control resources for protecting public health. Conclusions RageDB provides an example in the evolution of spatio-temporal database applications for the storage, analysis and communication of disease surveillance data. The database was fast and inexpensive to develop by using open-source technologies, simple and efficient design strategies, and shared web hosting. The database increases communication among agencies collaborating to protect human health from raccoon rabies. Furthermore, health agencies have real-time access to a wide assortment of data documenting new developments in the raccoon rabies epidemic and this enables a more timely and appropriate response.