Host, environment, and anthropogenic factors drive landscape dynamics of an environmentally transmitted pathogen: Sarcoptic mange in the bare-nosed wombat

Understanding the spatial dynamics and drivers of wildlife pathogens is constrained by sampling logistics, with implications for advancing the field of landscape epidemiology and targeted allocation of management resources. However, visually apparent wildlife diseases, when combined with remote-surveillance and distribution modelling technologies, present an opportunity to overcome this landscape-scale problem. Here, we investigated dynamics and drivers of landscape-scale wildlife disease, using clinical signs of sarcoptic mange (caused by Sarcoptes scabiei) in its bare-nosed wombat (BNW; Vombatus ursinus) host. We used 53,089 camera-trap observations from over 3261 locations across the 68,401 km2 area of Tasmania, Australia, combined with landscape data and ensemble species distribution modelling (SDM). We investigated: (1) landscape variables predicted to drive habitat suitability of the host; (2) host and landscape variables associated with clinical signs of disease in the host; and (3) predicted locations and environmental conditions at greatest risk of disease occurrence, including some Bass Strait islands where BNW translocations are proposed. We showed that the Tasmanian landscape, and ecosystems therein, are nearly ubiquitously suited to BNWs. Only high mean annual precipitation reduced habitat suitability for the host. In contrast, clinical signs of sarcoptic mange disease in BNWs were widespread, but heterogeneously distributed across the landscape. Mange (which is environmentally transmitted in BNWs) was most likely to be observed in areas of increased host habitat suitability, lower annual precipitation, near sources of freshwater and where topographic roughness was minimal (e.g. human modified landscapes, such as farmland and intensive land-use areas, shrub and grass lands). Thus, a confluence of host, environmental and anthropogenic variables appear to influence the risk of environmental transmission of S. scabiei. We identified that the Bass Strait Islands are highly suitable for BNWs and predicted a mix of high and low suitability for the pathogen. This study is the largest spatial assessment of sarcoptic mange in any host species, and advances understanding of the landscape epidemiology of environmentally transmitted S. scabiei. This research illustrates how host-pathogen co-suitability can be useful for allocating management resources in the landscape.

Urban habitat fragmentation and floral resources shape the occurrence of gut parasites in two bumblebee species

Urbanization and the expansion of human activities foster radical ecosystem changes with cascading effects also involving host-pathogen interactions. Urban pollinator insects face several stressors related to landscape and local scale features such as green habitat loss, fragmentation and availability reduction of floral resources with unpredictable effects on parasite transmission. Furthermore, beekeeping may contribute to the spread of parasites to wild pollinators by increasing the number of parasite hosts. Here we used DNA-based diagnostics tools to evaluate how the occurrence of parasites, namely microsporidians (Nosema spp.), trypanosomatids (Crithidia spp.) and neogregarines (Apicystis bombi), is shaped by the above-mentioned stressors in two bumblebee species (i.e. Bombus terrestris and Bombus pascuorum). Infection rates of the two species were different and generally higher in B. terrestris. Moreover, they showed different responses towards the same ecological variables, possibly due to differences in body size and foraging habits supposed to affect their susceptibility to parasite infection. The probability of infection was found to be reduced in B. pascuorum by green habitat fragmentation, while increased along with floral resource availability. Unexpectedly, B. terrestris had a lower parasite richness nearby apiaries maybe due to the fact that parasites are prone to be transmitted among the most abundant species. Our finding supports the need to design proper conservation measures based on species-specific knowledge, as suggested by the variation in the parasite occurrence of the two species. Moreover, conservation policies aiming at safeguarding pollinators through flower planting should consider the indirect effects of these measures for parasite transmission together with pollinator biodiversity issues.

Habitat fragmentation matters more than habitat loss: The case of host-parasite interactions

While ecologists agree that habitat loss has a substantial negative effect on biodiversity it is still very much a matter of debate whether habitat fragmentation has a lesser effect and whether this effect is positive or negative for biodiversity. Here, we assess the relative influence of tropical forest loss and fragmentation on the prevalence of vector-borne blood parasites of the genera Plasmodium and Haemoproteus in six forest bird species. We also determine whether habitat loss and fragmentation are associated with a rise or fall in prevalence. We sample more than 4000 individual birds from 58 forest sites in Guadeloupe and Martinique. Considering 34 host-parasite combinations independently and a fine characterization of the amount and spatial configuration of habitat, we use partial least square regressions to disentangle the relative effects of forest loss, forest fragmentation, landscape heterogeneity, and local weather conditions on spatial variability of parasite prevalence. Then we test for the magnitude and the sign of the effect of each environmental descriptor. Strikingly, we show that forest fragmentation explains twice as much of the variance in prevalence as habitat loss or landscape heterogeneity. In addition, habitat fragmentation leads to an overall rise in prevalence in Guadeloupe, but its effect is variable in Martinique. Both habitat loss and landscape heterogeneity exhibit taxon-specific effects. Our results suggest that habitat loss and fragmentation may have contrasting effects between tropical and temperate regions and that inter-specific interactions may not respond in the same way as more commonly used biodiversity metrics such as abundance and diversity.

Habitat split as a driver of disease in amphibians

Anthropogenic habitat disturbance is fundamentally altering patterns of disease transmission and immunity across the vertebrate tree of life. Most studies linking anthropogenic habitat change and disease focus on habitat loss and fragmentation, but these processes often lead to a third process that is equally important: habitat split. Defined as spatial separation between the multiple classes of natural habitat that many vertebrate species require to complete their life cycles, habitat split has been linked to population declines in vertebrates, e.g. amphibians breeding in lowland aquatic habitats and overwintering in fragments of upland terrestrial vegetation. Here, we link habitat split to enhanced disease risk in amphibians (i) by reviewing the biotic and abiotic forces shaping elements of immunity and (ii) through a spatially oriented field study focused on tropical frogs. We propose a framework to investigate mechanisms by which habitat split influences disease risk in amphibians, focusing on three broad host factors linked to immunity: (i) composition of symbiotic microbial communities, (ii) immunogenetic variation, and (iii) stress hormone levels. Our review highlights the potential for habitat split to contribute to host-associated microbiome dysbiosis, reductions in immunogenetic repertoire, and chronic stress, that often facilitate pathogenic infections and disease in amphibians and other classes of vertebrates. We highlight that targeted habitat-restoration strategies aiming to connect multiple classes of natural habitats (e.g. terrestrial-freshwater, terrestrial-marine, marine-freshwater) could enhance priming of the vertebrate immune system through repeated low-load exposure to enzootic pathogens and reduced stress-induced immunosuppression.

The effect of spatial dynamics on the behaviour of an environmentally transmitted disease

Understanding the spread of pathogens through the environment is critical to a fuller comprehension of disease dynamics. However, many mathematical models of disease dynamics ignore spatial effects. We seek to expand knowledge around the interaction between the bare-nosed wombat (Vombatus ursinus) and sarcoptic mange (etiologic agent Sarcoptes scabiei), by extending an aspatial mathematical model to include spatial variation. S. scabiei was found to move through our modelled region as a spatio-temporal travelling wave, leaving behind pockets of localized host extinction, consistent with field observations. The speed of infection spread was also comparable with field research. Our model predicts that the inclusion of spatial dynamics leads to the survival and recovery of affected wombat populations when an aspatial model predicts extinction. Collectively, this research demonstrates how environmentally transmitted S. scabiei can result in travelling wave dynamics, and that inclusion of spatial variation reveals a more resilient host population than aspatial modelling approaches.

A biogeographical description of the wild waterbird species associated with high-risk landscapes of Japanese encephalitis virus in India

Wild reservoirs of Japanese encephalitis virus are under-studied globally, which presents critical knowledge gaps for JEV epidemiology and infection ecology despite decades of received wisdom regarding this high-impact mosquito-borne virus. As a result, ardeid birds, generally understood to be the primary reservoirs for JEV, as well as other waterbirds occupying landscapes at high risk for spillover to humans, are frequently ignored by current surveillance mechanisms and infrastructure. This is particularly true in India, which experiences a high annual burden of human outbreaks. Incorporating wild reservoirs into surveillance of human and livestock populations is therefore essential but will first require a data-driven approach to target individual host species. The current study sought to identify preliminary waterbird target species for JEV surveillance development based on species' distributions in high-risk landscapes. Twenty-one target species were identified after adjusting species presence and abundance for the biotic constraints of sympatry. Furthermore, ardeid bird species richness demonstrated a strong non-linear association with the distribution of human JEV outbreaks, which suggested areas with the highest ardeid species richness corresponded to low JEV outbreak risk. No association was identified between JEV outbreaks and anatid or rallid richness. The lack of association between Anatidae and Rallidae family-level diversity and JEV outbreak risk notwithstanding, this study did identify several individual species among these two bird families in high-risk landscapes. The findings from this work provide the first data-driven evidence base to inform wildlife sampling for the monitoring of JEV circulation in outbreak hotspots in India and thus identify good preliminary targets for the development of One Health JEV surveillance.

Field and Landscape Risk Factors Impacting Flavescence Dorée Infection: Insights from Spatial Bayesian Modeling in the Bordeaux Vineyards

Flavescence dorée (FD) is a quarantine disease threatening European vineyards. Its management is based on mandatory insecticide treatments and the uprooting of infected plants identified during annual surveys. Field surveys are currently not optimized because the drivers affecting FD spread in vineyard landscapes remain poorly understood. We collated a georeferenced dataset of FD detection, collected from 34,581 vineyard plots over 5 years in the South West France wine region. Spatial models fitted with integrated nested Laplace approximation were used to identify local and landscape factors affecting FD detection and infection. Our analysis highlights the importance of sampling period on FD detection and of local practices and landscape context on FD infection. At field scale, altitude and cultivar choice were the main factors affecting FD infection. In particular, the odds ratio of FD infection in fields planted with the susceptible Cabernet Sauvignon, Cabernet Franc, or Muscadelle varieties were approximately twice those in fields planted with the less susceptible Merlot. Field infection was also affected by the field's immediate surroundings (within a circle with a radius of 150 to 200 m), corresponding to landscapes of 7 to 12 ha. In particular, the probability of FD infection increased with the proportions of forest and urban land and with the proportion of susceptible cultivars, demonstrating that the cultivar composition impacts FD epidemiology at landscape scale. The satisfactory predictive performance of the model for identifying districts with a prevalence of FD detection >10% of the fields suggests that it could be used to target areas in which future surveys would be most valuable.

High-risk landscapes of Japanese encephalitis virus outbreaks in India converge on wetlands, rain-fed agriculture, wild Ardeidae, and domestic pigs and chickens

Background

Japanese encephalitis virus (JEV) is a zoonotic mosquito-borne virus that causes a significant burden of disease across Asia, particularly in India, with high mortality in children. JEV circulates in wild ardeid birds and domestic pig reservoirs, both of which generate sufficiently high viraemias to infect vector mosquitoes, which can then subsequently infect humans. The landscapes of these hosts, particularly in the context of anthropogenic ecotones and resulting wildlife–livestock interfaces, are poorly understood and thus significant knowledge gaps in the epidemiology of JEV persist. This study sought to investigate the landscape epidemiology of JEV outbreaks in India over the period 2010–2020 to determine the influence of shared wetland and rain-fed agricultural landscapes and animal hosts on outbreak risk.

Methods

Using surveillance data from India’s National Centre for Disease Control Integrated Disease Surveillance Programme, JEV outbreaks were modelled as an inhomogeneous Poisson point process and externally validated against independently sourced data.

Results

Outbreak risk was strongly associated with the habitat suitability of ardeid birds, both pig and chicken density, and the shared landscapes between fragmented rain-fed agriculture and both river and freshwater marsh wetlands.

Conclusion

The results from this work provide the most complete understanding of the landscape epidemiology of JEV in India to date and suggest important One Health priorities for control and prevention across fragmented terrain comprising a wildlife–livestock interface that favours spillover to humans.

Floral resources shape parasite and pathogen dynamics in bees facing urbanization

Urbanization is associated with increases in impervious land cover, which alters the distribution of resources available to wildlife and concentrates activity in un-built spaces such as parks and gardens. How resource shifts alter the dynamics of parasite and pathogen transmission has not been addressed for many important species in urban systems. We focus on urban gardens, resource-rich "islands" within the urban matrix, to examine how the availability of floral resources at local and landscape scales influences the prevalence of 6 RNA viruses and 3 parasites in honey bees and bumble bees. Because parasites and pathogens are transmitted at flowers between visitors, we expected that floral abundance would concentrate bees within gardens, amplifying infection rates in pollinators, unless increases in floral resources would enhance bee diversity enough to dilute transmission. We found that garden size and flowering perennial plant abundance had a positive, direct effect on parasite and pathogen richness in bumble bees, suggesting that resource provisioning amplifies transmission. We also found that parasitism rates in honey bees were positively associated with parasites and pathogens in bumble bees, suggesting spillover between species. Encouragingly, we found evidence that management may mitigate parasitism through indirect effects: garden size had a positive impact on bee diversity, which in-turn was negatively associated with parasite and pathogen richness in bumble bees. Unexpectedly, we observed that that parasite and pathogen richness in honey bees had no significant predictors, highlighting the complexity of comparing transmission dynamics between species. Although floral resources provide bees with food, we suggest more research on the tradeoffs between resource provisioning and disease transmission to implement conservation plantings in changing landscapes.

A Landscape Epidemiological Approach for Predicting Chronic Wasting Disease: A Case Study in Virginia, US

Many infectious diseases in wildlife occur under quantifiable landscape ecological patterns useful in facilitating epidemiological surveillance and management, though little is known about prion diseases. Chronic wasting disease (CWD), a fatal prion disease of the deer family Cervidae, currently affects white-tailed deer (Odocoileus virginianus) populations in the Mid-Atlantic United States (US) and challenges wildlife veterinarians and disease ecologists from its unclear mechanisms and associations within landscapes, particularly in early phases of an outbreak when CWD detections are sparse. We aimed to provide guidance for wildlife disease management by identifying the extent to which CWD-positive cases can be reliably predicted from landscape conditions. Using the CWD outbreak in Virginia, US from 2009 to early 2020 as a case study system, we used diverse algorithms (e.g., principal components analysis, support vector machines, kernel density estimation) and data partitioning methods to quantify remotely sensed landscape conditions associated with CWD cases. We used various model evaluation tools (e.g., AUC ratios, cumulative binomial testing, Jaccard similarity) to assess predictions of disease transmission risk using independent CWD data. We further examined model variation in the context of uncertainty. We provided significant support that vegetation phenology data representing landscape conditions can predict and map CWD transmission risk. Model predictions improved when incorporating inferred home ranges instead of raw hunter-reported coordinates. Different data availability scenarios identified variation among models. By showing that CWD could be predicted and mapped, our project adds to the available tools for understanding the landscape ecology of CWD transmission risk in free-ranging populations and natural conditions. Our modeling framework and use of widely available landscape data foster replicability for other wildlife diseases and study areas.

Forest loss shapes the landscape suitability of Kyasanur Forest disease in the biodiversity hotspots of the Western Ghats, India

BACKGROUND

Anthropogenic pressure in biodiversity hotspots is increasingly recognized as a major driver of the spillover and expansion of zoonotic disease. In the Western Ghats region of India, a devastating tick-borne zoonosis, Kyasanur Forest disease (KFD), has been expanding rapidly beyond its endemic range in recent decades. It has been suggested that anthropogenic pressure in the form of land use changes that lead to the loss of native forest may be directly contributing to the expanding range of KFD, but clear evidence has not yet established the association between forest loss and KFD risk.

METHODS

The current study sought to investigate the relationship between KFD landscape suitability and both forest loss and mammalian species richness, to inform its epidemiology and infection ecology. A total of 47 outbreaks of KFD between 1 January 2012 and 30 June 2019 were modelled as an inhomogeneous Poisson process.

RESULTS

Both forest loss [relative risk (RR) = 1.83; 95% confidence interval (CI) 1.33-2.51] and mammalian species richness (RR = 1.29; 95% CI 1.16-1.42) were strongly associated with increased risk of KFD and dominated its landscape suitability.

CONCLUSIONS

These results provide the first evidence of a clear association between increasing forest loss and risk for KFD. Moreover, the findings also highlight the importance of forest loss in areas of high biodiversity. Therefore, this evidence provides strong support for integrative approaches to public health which incorporate conservation strategies simultaneously protective of humans, animals and the environment.

Forecasting and control of emerging infectious forest disease through participatory modelling

Epidemiological models are powerful tools for evaluating scenarios and visualizing patterns of disease spread, especially when comparing intervention strategies. However, the technical skill required to synthesize and operate computational models frequently renders them beyond the command of the stakeholders who are most impacted by the results. Participatory modelling (PM) strives to restructure the power relationship between modellers and the stakeholders who rely on model insights by involving these stakeholders directly in model development and application; yet, a systematic literature review indicates little adoption of these techniques in epidemiology, especially plant epidemiology. We investigate the potential for PM to integrate stakeholder and researcher knowledge, using Phytophthora ramorum and the resulting sudden oak death disease as a case study. Recent introduction of a novel strain (European 1 or EU1) in southwestern Oregon has prompted significant concern and presents an opportunity for coordinated management to minimize regional pathogen impacts. Using a PM framework, we worked with local stakeholders to develop an interactive forecasting tool for evaluating landscape-scale control strategies. We find that model co-development has great potential to empower stakeholders in the design, development and application of epidemiological models for disease control.

This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.

The elephant-livestock interface modulates anthrax suitability in India

Anthrax is a potentially life-threatening bacterial disease that can spread between wild and livestock animals and humans. Transmission typically occurs indirectly via environmental exposure, with devastating consequences for human and animal health, as well as pastoralist economies. India has a high annual occurrence of anthrax in some regions, but a country-wide delineation of risk has not yet been undertaken. The current study modelled the geographical suitability of anthrax across India and its associated environmental features using a biogeographic application of machine learning. Both biotic and abiotic features contributed to risk across multiple scales of influence. The elephant-livestock interface was the dominant feature in delineating anthrax suitability. In addition, water-soil balance, soil chemistry and historical forest loss were also influential. These findings suggest that the elephant-livestock interface plays an important role in the cycling of anthrax in India. Livestock prevention efforts targeting this interface, particularly within anthropogenic ecotones, may yield successes in reducing ongoing transmission between animal hosts and subsequent zoonotic transmission to humans.

Wildlife Management Practices Associated with Pathogen Exposure in Non-Native Wild Pigs in Florida, U.S

Land use influences disease emergence by changing the ecological dynamics of humans, wildlife, domestic animals, and pathogens. This is a central tenet of One Health, and one that is gaining momentum in wildlife management decision-making in the United States. Using almost 2000 serological samples collected from non-native wild pigs (Sus scrofa) throughout Florida (U.S.), we compared the prevalence and exposure risk of two directly transmitted pathogens, pseudorabies virus (PrV) and Brucella spp., to test the hypothesis that disease emergence would be positively correlated with one of the most basic wildlife management operations: Hunting. The seroprevalence of PrV-Brucella spp. coinfection or PrV alone was higher for wild pigs in land management areas that allowed hunting with dogs than in areas that culled animals using other harvest methods. This pattern did not hold for Brucella alone. The likelihood of exposure to PrV, but not Brucella spp., was also significantly higher among wild pigs at hunted sites than at sites where animals were culled. By failing to consider the impact of dog hunting on the emergence of non-native pathogens, current animal management practices have the potential to affect public health, the commercial livestock industry, and wildlife conservation.

Pathogens in space: Advancing understanding of pathogen dynamics and disease ecology through landscape genetics

Landscape genetics has provided many insights into how heterogeneous landscape features drive processes influencing spatial genetic variation in free-living organisms. This rapidly developing field has focused heavily on vertebrates, and expansion of this scope to the study of infectious diseases holds great potential for landscape geneticists and disease ecologists alike. The potential application of landscape genetics to infectious agents has garnered attention at formative stages in the development of landscape genetics, but systematic examination is lacking. We comprehensively review how landscape genetics is being used to better understand pathogen dynamics. We characterize the field and evaluate the types of questions addressed, approaches used and systems studied. We also review the now established landscape genetic methods and their realized and potential applications to disease ecology. Lastly, we identify emerging frontiers in the landscape genetic study of infectious agents, including recent phylogeographic approaches and frameworks for studying complex multihost and host-vector systems. Our review emphasizes the expanding utility of landscape genetic methods available for elucidating key pathogen dynamics (particularly transmission and spread) and also how landscape genetic studies of pathogens can provide insight into host population dynamics. Through this review, we convey how increasing awareness of the complementarity of landscape genetics and disease ecology among practitioners of each field promises to drive important cross-disciplinary advances.

Mosaics often outperform pyramids: insights from a model comparing strategies for the deployment of plant resistance genes against viruses in agricultural landscapes

The breakdown of plant virus resistance genes is a major issue in agriculture. We investigated whether a set of resistance genes would last longer when stacked into a single plant cultivar (pyramiding) or when deployed individually in regional mosaics (mosaic strategy). We modeled the genetic and epidemiological processes shaping the demogenetic dynamics of viruses under a multilocus gene-for-gene system, from the plant to landscape scales. The landscape consisted of many fields, was subject to seasonality, and of a reservoir hosting viruses year-round. Strategy performance depended principally on the fitness costs of adaptive mutations, epidemic intensity before resistance deployment and landscape connectivity. Mosaics were at least as good as pyramiding strategies in most production situations tested. Pyramiding strategies performed better only with slowly changing virus reservoir dynamics. Mosaics are more versatile than pyramiding strategies, and we found that deploying a mosaic of three to five resistance genes generally provided effective disease control, unless the epidemics were driven mostly by within-field infections. We considered the epidemiological and evolutionary mechanisms underlying the greater versatility of mosaics in our case study, with a view to providing breeders and growers with guidance as to the most appropriate deployment strategy.

Prospects and Challenges towards Sustainable Liver Fluke Control

The liver fluke Opisthorchis viverrini (Ov) is endemic in Southeast Asia where more than 10 million people are estimated to be infected. The infection is associated with several hepatobiliary diseases, including cholangiocarcinoma (CCA). Northeast Thailand is a hotspot for Ov transmission, and, despite extensive public health prevention campaigns led by the government, the prevalence of Ov infection is still high. High infection rates result from cultural and ecological complexities where wet-rice agrarian habitats, centuries-old raw-food culture, and the parasite's complex biology combine to create an ideal transmission arena. Here we review the state of our knowledge regarding the social-ecological determinants underlying Ov transmission. We also describe an integrative research rationale for liver fluke control better aligned with sustainable health development.

The landscape epidemiology of echinococcoses

Echinococcoses are parasitic diseases of major public health importance globally. Human infection results in chronic disease with poor prognosis and serious medical, social and economic consequences for vulnerable populations. According to recent estimates, the geographical distribution of Echinococcus spp. infections is expanding and becoming an emerging and re-emerging problem in several regions of the world. Echinococcosis endemicity is geographically heterogeneous and over time it may be affected by global environmental change. Therefore, landscape epidemiology offers a unique opportunity to quantify and predict the ecological risk of infection at multiple spatial and temporal scales. Here, we review the most relevant environmental sources of spatial variation in human echinococcosis risk, and describe the potential applications of landscape epidemiological studies to characterise the current patterns of parasite transmission across natural and human-altered landscapes. We advocate future work promoting the use of this approach as a support tool for decision-making that facilitates the design, implementation and monitoring of spatially targeted interventions to reduce the burden of human echinococcoses in disease-endemic areas.

Increasing virulence, but not infectivity, associated with serially emergent virus strains of a fish rhabdovirus

Surveillance and genetic typing of field isolates of a fish rhabdovirus, infectious hematopoietic necrosis virus (IHNV), has identified four dominant viral genotypes that were involved in serial viral emergence and displacement events in steelhead trout (Oncorhynchus mykiss) in western North America. To investigate drivers of these landscape-scale events, IHNV isolates designated 007, 111, 110, and 139, representing the four relevant genotypes, were compared for virulence and infectivity in controlled laboratory challenge studies in five relevant steelhead trout populations. Viral virulence was assessed as mortality using lethal dose estimates (LD50), survival kinetics, and proportional hazards analysis. A pattern of increasing virulence for isolates 007, 111, and 110 was consistent in all five host populations tested, and correlated with serial emergence and displacements in the virus-endemic lower Columbia River source region during 1980-2013. The fourth isolate, 139, did not have higher virulence than the previous isolate 110. However, the mG139M genotype displayed a conditional displacement phenotype in that it displaced type mG110M in coastal Washington, but not in the lower Columbia River region, indicating that factors other than evolution of higher viral virulence were involved in some displacement events. Viral infectivity, measured as infectious dose (ID50), did not correlate consistently with virulence or with viral emergence, and showed a narrow range of variation relative to the variation observed in virulence. Comparison among the five steelhead trout populations confirmed variation in resistance to IHNV, but correlations with previous history of virus exposure or with sites of viral emergence varied between IHNV source and sink regions. Overall, this study indicated increasing viral virulence over time as a potential driver for emergence and displacement events in the endemic Lower Columbia River source region where these IHNV genotypes originated, but not in adjacent sink regions.

Epidemiological and evolutionary management of plant resistance: optimizing the deployment of cultivar mixtures in time and space in agricultural landscapes

The management of genes conferring resistance to plant–pathogens should make it possible to control epidemics (epidemiological perspective) and preserve resistance durability (evolutionary perspective). Resistant and susceptible cultivars must be strategically associated according to the principles of cultivar mixture (within a season) and rotation (between seasons). We explored these questions by modeling the evolutionary and epidemiological processes shaping the dynamics of a pathogen population in a landscape composed of a seasonal cultivated compartment and a reservoir compartment hosting pathogen year-round. Optimal deployment strategies depended mostly on the molecular basis of plant–pathogen interactions and on the agro-ecological context before resistance deployment, particularly epidemic intensity and landscape connectivity. Mixtures were much more efficient in landscapes in which between-field infections and infections originating from the reservoir were more prevalent than within-field infections. Resistance genes requiring two mutations of the pathogen avirulence gene to be broken down, rather than one, were particularly useful when infections from the reservoir predominated. Combining mixture and rotation principles were better than the use of the same mixture each season as (i) they controlled epidemics more effectively in situations in which within-field infections or infections from the reservoir were frequent and (ii) they fulfilled the epidemiological and evolutionary perspectives.

Spatial distribution patterns of plague hosts: point pattern analysis of the burrows of great gerbils in Kazakhstan

AIM

The spatial structure of a population can strongly influence the dynamics of infectious diseases, yet rarely is the underlying structure quantified. A case in point is plague, an infectious zoonotic disease caused by the bacterium Yersinia pestis. Plague dynamics within the Central Asian desert plague focus have been extensively modelled in recent years, but always with strong uniformity assumptions about the distribution of its primary reservoir host, the great gerbil (Rhombomys opimus). Yet, while clustering of this species' burrows due to social or ecological processes could have potentially significant effects on model outcomes, there is currently nothing known about the spatial distribution of inhabited burrows. Here, we address this knowledge gap by describing key aspects of the spatial patterns of great gerbil burrows in Kazakhstan.

LOCATION

Kazakhstan.

METHODS

Burrows were classified as either occupied or empty in 98 squares of four different sizes: 200 m (side length), 250 m, 500 m and 590-1020 m. We used Ripley's K statistic to determine whether and at what scale there was clustering of occupied burrows, and semi-variograms to quantify spatial patterns in occupied burrows at scales of 250 m to 9 km.

RESULTS

Significant spatial clustering of occupied burrows occurred in 25% and 75% of squares of 500 m and 590-1020 m, respectively, but not in smaller squares. In clustered squares, the clustering criterion peaked around 250 m. Semi-variograms showed that burrow density was auto-correlated up to a distance of 7 km and occupied density up to 2.5 km.

MAIN CONCLUSIONS

These results demonstrate that there is statistically significant spatial clustering of occupied burrows and that the uniformity assumptions of previous plague models should be reconsidered to assess its significance for plague transmission. This field evidence will allow for more realistic approaches to disease ecology models for both this system and for other structured host populations.

Crop pathogen emergence and evolution in agro-ecological landscapes

Remnant areas hosting natural vegetation in agricultural landscapes can impact the disease epidemiology and evolutionary dynamics of crop pathogens. However, the potential consequences for crop diseases of the composition, the spatial configuration and the persistence time of the agro-ecological interface - the area where crops and remnant vegetation are in contact - have been poorly studied. Here, we develop a demographic-genetic simulation model to study how the spatial and temporal distribution of remnant wild vegetation patches embedded in an agricultural landscape can drive the emergence of a crop pathogen and its subsequent specialization on the crop host. We found that landscape structures that promoted larger pathogen populations on the wild host facilitated the emergence of a crop pathogen, but such landscape structures also reduced the potential for the pathogen population to adapt to the crop. In addition, the evolutionary trajectory of the pathogen population was determined by interactions between the factors describing the landscape structure and those describing the pathogen life histories. Our study contributes to a better understanding of how the shift of land-use patterns in agricultural landscapes might influence crop diseases to provide predictive tools to evaluate management practices.

Disease risk in a dynamic environment: the spread of tick-borne pathogens in Minnesota, USA

As humans and climate change alter the landscape, novel disease risk scenarios emerge. Understanding the complexities of pathogen emergence and subsequent spread as shaped by landscape heterogeneity is crucial to understanding disease emergence, pinpointing high-risk areas, and mitigating emerging disease threats in a dynamic environment. Tick-borne diseases present an important public health concern and incidence of many of these diseases are increasing in the United States. The complex epidemiology of tick-borne diseases includes strong ties with environmental factors that influence host availability, vector abundance, and pathogen transmission. Here, we used 16 years of case data from the Minnesota Department of Health to report spatial and temporal trends in Lyme disease (LD), human anaplasmosis, and babesiosis. We then used a spatial regression framework to evaluate the impact of landscape and climate factors on the spread of LD. Finally, we use the fitted model, and landscape and climate datasets projected under varying climate change scenarios, to predict future changes in tick-borne pathogen risk. Both forested habitat and temperature were important drivers of LD spread in Minnesota. Dramatic changes in future temperature regimes and forest communities predict rising risk of tick-borne disease.

Degree of host susceptibility in the initial disease outbreak influences subsequent epidemic spread

Disease epidemics typically begin as an outbreak of a relatively small, spatially explicit population of infected individuals (focus), in which disease prevalence increases and rapidly spreads into the uninfected, at-risk population. Studies of epidemic spread typically address factors influencing disease spread through the at-risk population, but the initial outbreak may strongly influence spread of the subsequent epidemic.We initiated wheat stripe rust Puccinia striiformis f. sp. tritici epidemics to assess the influence of the focus on final disease prevalence when the degree of disease susceptibility differed between the at-risk and focus populations.When the focus/at-risk plantings consisted of partially genetic resistant and susceptible cultivars, final disease prevalence was statistically indistinguishable from epidemics produced by the focus cultivar in monoculture. In these experimental epidemics, disease prevalence was not influenced by the transition into an at-risk population that differed in disease susceptibility. Instead, the focus appeared to exert a dominant influence on the subsequent epidemic.Final disease prevalence was not consistently attributable to either the focus or the at-risk population when focus/at-risk populations were planted in a factorial set-up with a mixture (~28% susceptible and 72% resistant) and susceptible individuals. In these experimental epidemics, spatial heterogeneity in disease susceptibility within the at-risk population appeared to counter the dominant influence of the focus.Cessation of spore production from the focus (through fungicide/glyphosate application) after 1.3 generations of stripe rust spread did not reduce final disease prevalence, indicating that the focus influence on disease spread is established early in the epidemic.Synthesis and applications. Our experiments indicated that outbreak conditions can be highly influential on epidemic spread, even when disease resistance in the at-risk population is greater than that of the focus. Disease control treatments administered shortly after the initial outbreak within the focus may either prevent an epidemic from occurring or reduce its severity.

Comparison of the vector potential of different mosquito species for the transmission of heartworm, Dirofilaria immitis, in rural and urban areas in and surrounding Stillwater, Oklahoma, U.S.A

Dirofilaria immitis Leidy (Spirurida: Onchocercidae), or heartworm, is a mosquito-borne nematode that causes a fatal disease in carnivores. Although infection is preventable through prophylactic drugs, compliance and the spectre of resistance suggest vector control is a viable alternative. There were two main objectives in this study: (a) to evaluate the relationships between landscape and social factors and the number and species of heartworm-positive mosquitoes, with a specific focus on the importance of the invasive Asian tiger mosquito, Aedes albopictus (Skuse) (Stegomyia albopicta) (Diptera: Culicidae), and (b) to test the hypothesis that dog heartworm is more prevalent in suburban than in rural areas. To achieve these objectives, mosquitoes were collected from May to November 2010 at 16 rural and 16 urban locations in Payne County, Oklahoma, U.S.A. using three trapping methods that utilized, respectively, resting boxes, carbon dioxide traps and BG Sentinel traps. Urban areas showed greater numbers of Ae. albopictus and a higher overall likelihood of infection with D. immitis. Because many species of mosquito are responsible for heartworm transmission, current prophylactic treatment remains the best method of controlling this parasite.

Co-occurrence patterns of the dengue vector Aedes aegypti and Aedes mediovitattus, a dengue competent mosquito in Puerto Rico

Aedes aegypti is implicated in dengue transmission in tropical and subtropical urban areas around the world. Ae. aegypti populations are controlled through integrative vector management. However, the efficacy of vector control may be undermined by the presence of alternative, competent species. In Puerto Rico, a native mosquito, Ae. mediovittatus, is a competent dengue vector in laboratory settings and spatially overlaps with Ae. aegypti. It has been proposed that Ae. mediovittatus may act as a dengue reservoir during inter-epidemic periods, perpetuating endemic dengue transmission in rural Puerto Rico. Dengue transmission dynamics may therefore be influenced by the spatial overlap of Ae. mediovittatus, Ae. aegypti, dengue viruses, and humans. We take a landscape epidemiology approach to examine the association between landscape composition and configuration and the distribution of each of these Aedes species and their co-occurrence. We used remotely sensed imagery from a newly launched satellite to map landscape features at very high spatial resolution. We found that the distribution of Ae. aegypti is positively predicted by urban density and by the number of tree patches, Ae. mediovittatus is positively predicted by the number of tree patches, but negatively predicted by large contiguous urban areas, and both species are predicted by urban density and the number of tree patches. This analysis provides evidence that landscape composition and configuration is a surrogate for mosquito community composition, and suggests that mapping landscape structure can be used to inform vector control efforts as well as to inform urban planning.

Spatial analysis of feline immunodeficiency virus infection in cougars

The cougar (Puma concolor) is a large predatory feline found widely in the Americas that is susceptible to feline immunodeficiency virus (FIV), a fast-evolving lentivirus found in wild feline species that is analogous to simian immunodeficiency viruses in wild primates and belongs to the same family of viruses as human immunodeficiency virus. FIV infection in cougars can lead to a weakened immune system that creates opportunities for other infecting agents. FIV prevalence and lineages have been studied previously in several areas in the western United States, but typically without spatially explicit statistical techniques. To describe the distribution of FIV in a sample of cougars located in the northern Rocky Mountain region of North America, we first used kernel density ratio estimation to map the log relative risk of FIV. The risk surface showed a significant cluster of FIV in northwestern Montana. We also used Bayesian cluster models for genetic data to investigate the spatial structure of the feline immunodeficiency virus with virus genetic sequence data. A result of the models was two spatially distinct FIV lineages that aligned considerably with an interstate highway in Montana. Our results suggest that the use of spatial information and models adds novel insight when investigating an infectious animal disease. The results also suggest that the influence of landscape features likely plays an important role in the spatiotemporal spread of an infectious disease within wildlife populations.

Stratifying land use/land cover for spatial analysis of disease ecology and risk: an example using object-based classification techniques

Landscape epidemiology has made significant strides recently, driven in part by increasing availability of land cover data derived from remotely-sensed imagery. Using an example from a study of land cover effects on hantavirus dynamics at an Atlantic Forest site in eastern Paraguay, we demonstrate how automated classification methods can be used to stratify remotely-sensed land cover for studies of infectious disease dynamics. For this application, it was necessary to develop a scheme that could yield both land cover and land use data from the same classification. Hypothesizing that automated discrimination between classes would be more accurate using an object-based method compared to a per-pixel method, we used a single Landsat Enhanced Thematic Mapper+ (ETM+) image to classify land cover into eight classes using both per-pixel and object-based classification algorithms. Our results show that the object-based method achieves 84% overall accuracy, compared to only 43% using the per-pixel method. Producer's and user's accuracies for the object-based map were higher for every class compared to the per-pixel classification. The Kappa statistic was also significantly higher for the object-based classification. These results show the importance of using image information from domains beyond the spectral domain, and also illustrate the importance of object-based techniques for remote sensing applications in epidemiological studies.