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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.

The sea louse is considered an important ectoparasite that affects farmed salmonids around the world. Sea lice control relies heavily on pharmacological treatments in several salmon-producing countries, including Chile. Among options for drug administration, immersion treatments represent the majority of antiparasitic control strategies used in Chile. As a topical procedure, immersion treatments do not induce a long lasting effect; therefore, re-infestation from neighbouring farms may undermine their efficacy. Synchronization of treatments has been proposed as a strategy to improve immersion treatment performance, but it has not been evaluated so far. Using a repeated-measures linear mixed-effect model, we evaluated the impact of treatment synchronization of neighbouring farms (within 10km seaway distance) on the adult lice mean abundance from weeks 2 to 8 post-treatment on rainbow trout and Atlantic salmon farms in Chile, while controlling for external and internal sources of lice before the treatments, and also for environmental and fish-related variables. Results indicate that treatment synchronization was significantly associated with lower adult lice levels from weeks 5 to 7 after treatment. This relationship appeared to be linear, suggesting that higher levels of synchronization may result in lower adult sea lice levels during these weeks. These findings suggest that synchronization can improve the performance of immersion delousing treatments by keeping sea lice levels low for a longer period of time. Our results may be applicable to other regions of the world where immersion treatments are widely used.

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.

Background Zika virus (ZIKV) spread rapidly in the Americas in 2015. Targeting effective public health interventions for inhabitants of, and travellers to and from, affected countries depends on understanding the risk of ZIKV emergence (and re-emergence) at the local scale. We explore the extent to which environmental, social and neighbourhood disease intensity variables influenced emergence dynamics. Our objective was to characterise population vulnerability given the potential for sustained autochthonous ZIKV transmission and the timing of emergence. Logistic regression models estimated the probability of reporting at least one case of ZIKV in a given municipality over the course of the study period as an indicator for sustained transmission; while accelerated failure time (AFT) survival models estimated the time to a first reported case of ZIKV in week t for a given municipality as an indicator for timing of emergence. Results Sustained autochthonous ZIKV transmission was best described at the temporal scale of the study period (almost one year), such that high levels of study period precipitation and low mean study period temperature reduced the probability. Timing of ZIKV emergence was best described at the weekly scale for precipitation in that high precipitation in the current week delayed reporting. Both modelling approaches detected an effect of high poverty on reducing/slowing case detection, especially when inter-municipal road connectivity was low. We also found that proximity to municipalities reporting ZIKV had an effect to reduce timing of emergence when located, on average, less than 100 km away. Conclusions The different modelling approaches help distinguish between large temporal scale factors driving vector habitat suitability and short temporal scale factors affecting the speed of spread. We find evidence for inter-municipal movements of infected people as a local-scale driver of spatial spread. The negative association with poverty suggests reduced case reporting in poorer areas. Overall, relatively simplistic models may be able to predict the vulnerability of populations to autochthonous ZIKV transmission at the local scale. Electronic supplementary material The online version of this article (10.1186/s13071-018-2867-8) contains supplementary material, which is available to authorized users.

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.

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.

Climate change is driving emergence and establishment of Ixodes scapularis, the main vector of Lyme disease in Québec, Canada. As for the black-legged tick, I. scapularis Say, global warming may also favor northward expansion of other species of medically important ticks. The aims of this study were to determine (1) current diversity and abundance of ticks of public health significance other than I. scapularis, (2) sex and age of the human population bitten by these ticks (3), and the seasonal and geographic pattern of their occurrence. From 2007 to 2015, twelve tick species other than I. scapularis were submitted in the Québec passive tick surveillance program. Of these 9243 ticks, 91.2% were Ixodes cookei, 4.1% were Dermacentor variabilis, 4.0% were Rhipicephalus sanguineus and 0.7% were Amblyomma americanum. The combined annual proportion of submitted I. cookei, D. variabilis, R. sanguineus and A. americanum ticks in passive surveillance rose from 6.1% in 2007 to 16.0% in 2015 and an annual growing trend was observed for each tick species. The number of municipalities where I. cookei ticks were acquired rose from 104 to 197 during the same period. Of the 862 people bitten by these ticks, 43.3% were I. cookei ticks removed from children aged < 10 years. These findings demonstrate the need for surveillance of all the tick species of medical importance in Québec, particularly because climate may increase their abundance and geographic ranges, increasing the risk to the public of the diseases they transmit.

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.

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.

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.

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, Québec, 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 Québec (RQCHP-Réseau québécois 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.

Effective disease management can benefit from mathematical models that identify drivers of epidemiological change and guide decision-making. This is well illustrated in the host–parasite system of sea lice and salmon, which has been modelled extensively due to the economic costs associated with sea louse infections on salmon farms and the conservation concerns associated with sea louse infections on wild salmon. Consequently, a rich modelling literature devoted to sea louse and salmon epidemiology has been developed. We provide a synthesis of the mathematical and statistical models that have been used to study the epidemiology of sea lice and salmon. These studies span both conceptual and tactical models to quantify the effects of infections on host populations and communities, describe and predict patterns of transmission and dispersal, and guide evidence-based management of wild and farmed salmon. As aquaculture production continues to increase, advances made in modelling sea louse and salmon epidemiology should inform the sustainable management of marine resources.

Landscape barriers influence movement patterns of animals, which in turn, affect spatio-temporal spread of infectious wildlife disease. We compare genetic data from computer simulations to those acquired from field samples to measure the effect of a landscape barrier on raccoon (Procyon lotor) movement, enabling risk assessment of raccoon rabies disease spread across the Niagara River from New York State into Ontario, an area currently uninfected by rabies. An individual-based spatially explicit model is used to simulate the expansion of a raccoon population to cross the Niagara River, for different permeabilities of the river to raccoon crossings. Since the model records individual raccoon genetics, the genetic population structure of neutral mitochondrial DNA haplotypes are characterised in the expanding population, every 25 years, using a genetic distance measure, phi ST, Mantel tests and a gene diversity measure. The river barrier effect is assessed by comparing genetic measures computed from model outputs to those calculated from 166 raccoons recently sampled from the same landscape. The "best fit" between modelled scenarios and field data indicate the river prevents 50% of attempts to cross the river. Founder effects dominated the colonizing genetic population structure, and, as the river barrier effect increased, its genetic diversity decreased. Using gene flow to calibrate the effect of the river as a barrier to movement provides an estimate of the effect of a river in reducing the likelihood of cross-river infection. Including individual genetic markers in simulation modelling benefits investigations of disease spread and control.