Dynamic, spatial models of parasite transmission in wildlife: Their structure, applications and remaining challenges

Caterpillar movement mediates spatially local interactions and determines the relationship between population density and contact

BACKGROUND

While interactions in nature are inherently local, ecological models often assume homogeneity across space, allowing for generalization across systems and greater mathematical tractability. Density-dependent disease models are a prominent example of models that assume homogeneous interactions, leading to the prediction that disease transmission will scale linearly with population density. In this study, we examined how the scale of larval butterfly movement interacts with the resource landscape to influence the relationship between larval contact and population density in the Baltimore checkerspot (Euphydryas phaeton). Our study was inspired by the recent discovery of a viral pathogen that is transmitted horizontally among Baltimore checkerspot larvae.

METHODS

We used multi-year larvae location data across six Baltimore checkerspot populations in the eastern U.S. to test whether larval nests are spatially clustered. We then integrated these spatial data with larval movement data in different resource contexts to investigate whether heterogeneity in spatially local interactions alters the assumed linear relationship between larval nest density and contact. We used Correlated Random Walk (CRW) models and field observations of larval movement behavior to construct Probability Distribution Functions (PDFs) of larval dispersal, and calculated the overlap in these PDFs to estimate conspecific contact within each population.

RESULTS

We found that all populations exhibited significant spatial clustering in their habitat use. Subsequent larval movement rates were influenced by encounters with host plants and larval age, and under many movement scenarios, the scale of predicted larval movement was not sufficient to allow for the "homogeneous mixing" assumed in density dependent disease models. Therefore, relationships between population density and larval contact were typically non-linear. We also found that observed use of available habitat patches led to significantly greater contact than would occur if habitat use were spatially random.

CONCLUSIONS

These findings strongly suggest that incorporating larval movement and spatial variation in larval interactions is critical to modeling disease outcomes in E. phaeton. Epidemiological models that assume a linear relationship between population density and larval contact have the potential to underestimate transmission rates, especially in small populations that are already vulnerable to extinction.

A biological invasion modifies the dynamics of a host-parasite arms race

By imposing novel selection pressures on both participants, biological invasions can modify evolutionary 'arms races' between hosts and parasites. A spatially replicated cross-infection experiment reveals strong spatial divergence in the ability of lungworms (Rhabdias pseudosphaerocephala) to infect invasive cane toads (Rhinella marina) in Australia. In areas colonized for longer than 20 years, toads are more resistant to infection by local strains of parasites than by allopatric strains. The situation reverses at the invasion front, where super-infective parasites have evolved. Invasion-induced shifts in genetic diversity and selective pressures may explain why hosts gain advantage over parasites in long-colonized areas, whereas parasites gain advantage at the invasion front.

Novel pathogen introduction triggers rapid evolution in animal social movement strategies

Animal sociality emerges from individual decisions on how to balance the costs and benefits of being sociable. Novel pathogens introduced into wildlife populations should increase the costs of sociality, selecting against gregariousness. Using an individual-based model that captures essential features of pathogen transmission among social hosts, we show how novel pathogen introduction provokes the rapid evolutionary emergence and coexistence of distinct social movement strategies. These strategies differ in how they trade the benefits of social information against the risk of infection. Overall, pathogen-risk-adapted populations move more and have fewer associations with other individuals than their pathogen-risk-naive ancestors, reducing disease spread. Host evolution to be less social can be sufficient to cause a pathogen to be eliminated from a population, which is followed by a rapid recovery in social tendency. Our conceptual model is broadly applicable to a wide range of potential host-pathogen introductions and offers initial predictions for the eco-evolutionary consequences of wildlife pathogen spillover scenarios and a template for the development of theory in the ecology and evolution of animals' movement decisions.

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.

TOXOPLASMA GONDII PREVALENCE, PARTIAL GENOTYPES, AND SPATIAL VARIATION IN NORTH AMERICAN RIVER OTTERS (LONTRA CANADENSIS) IN THE UPPER PENINSULA OF MICHIGAN, USA

Toxoplasma gondii is a ubiquitous parasitic protozoan that poses a health threat to wildlife and human health worldwide. Oocysts shed into the environment in felid host feces may persist for several years. Runoff from rainfall and snowmelt may carry the oocysts into waterways. Semiaquatic mammals such as the Northern American river otter (Lontra canadensis) are particularly at risk of exposure, as they may encounter infective stages in both terrestrial and aquatic environments. Despite this risk, only a small number of studies have examined the prevalence of T. gondii in US river otter populations. Tongue tissue was sampled from 124 otters from the Upper Peninsula of Michigan submitted by trappers to the Michigan Department of Natural Resources in the 2018-19 harvest season. Following DNA extraction, a portion of the B1 T. gondii gene was amplified with PCR. A subset of positive samples was genotyped for comparison with known T. gondii sequences. Of the 124 tongue samples, 35 (28%) were positive for T. gondii. Prevalence did not differ significantly between sexes or age classes across the entire study area. Most (53.8%) of the genotyped samples were type 4 (type 12), a genotype commonly found in North American wildlife. Genotypes 127 and 197 were also found. Three clusters of T. gondii prevalence were identified through SaTScan analysis, although they were not significant. When modeling prevalence of T. gondii with covariates at individual otter locations, the top three models included the presence of Sarcocystis, area of exotic plants, area of agriculture, and sex of the otter. Our results suggest that T. gondii is widespread in otter populations in the Upper Peninsula of Michigan.

Parasitic strongyle nemabiome communities in wild ruminants in Sweden

Background

Wildlife hosts may serve as reservoirs for strongyles, which can be transmitted to domestic livestock. Therefore, studies evaluating nemabiome compositions in wildlife ruminants are of great use in assessing the possibility of transmission of important nematode pathogens to domestic sheep in Sweden.

Methods

First, fecal samples were collected from roe deer (n = 125), fallow deer (n = 106), red deer (n = 18) and mouflon (n = 13) in south central Sweden during the hunting season in 2019. Second, after fecal examination samples were cultured and the larvae were harvested, followed by DNA extractions. Third, all samples were barcoded and processed for sequence analysis on the PacBio platform. Finally, bioinformatic sequence analysis was conducted with DADA2, while species diversity and richness, as well as interactions between the different hosts, were calculated and analyzed in R.

Results

Nematode ITS2 sequences were found in 225 of 262 (86%) samples. In total, 31 taxa were identified, among which 26 (86%) to the species level. These were found in different combinations, among which 24 (77%) occurred in roe deer, 19 (61%) in fallow deer, 20 (65%) in red deer and 10 (32%) in mouflon. Five of the species found are known to be associated with livestock (Chabertia ovina, Haemonchus contortus, Oesophagostomum venulosum, Teladorsagia circumcincta and Trichostrongylus axei). However, in the present study the relative abundance and prevalence of most of these species were low. The most striking exception was T. axei, which was relatively abundant in all wildlife hosts. Mostly a wide range of wildlife specific nematodes such as Ostertagia leptospicularis and Spiculopteragia spp. were identified including the invasive nematode Spiculopteragia houdemeri, which was found for the first time in red deer, fallow deer, and mouflon in Sweden. The difference in the number of shared species between mouflon and all cervids (n = 6) was less than among all three cervids (n = 8).

Conclusion

In this study, we investigated the community structure of parasitic intestinal nematodes in four wildlife hosts, and we found that the majority of the parasite species identified were wildlife specific. We also found a new, potentially invasive species not reported before. After comparing the nemabiome of the wildlife hosts in this study with a previous study in sheep from the same geographical region, we conclude that the horizontal transmission potential appears to be relatively low. Still, cross-infections of nematodes between game and sheep cannot be completely ignored.

Graphical Abstract

Capturing complex interactions in disease ecology with simplicial sets

Network approaches have revolutionized the study of ecological interactions. Social, movement and ecological networks have all been integral to studying infectious disease ecology. However, conventional (dyadic) network approaches are limited in their ability to capture higher-order interactions. We present simplicial sets as a tool that addresses this limitation. First, we explain what simplicial sets are. Second, we explain why their use would be beneficial in different subject areas. Third, we detail where these areas are: social, transmission, movement/spatial and ecological networks and when using them would help most in each context. To demonstrate their application, we develop a novel approach to identify how pathogens persist within a host population. Fourth, we provide an overview of how to use simplicial sets, highlighting specific metrics, generative models and software. Finally, we synthesize key research questions simplicial sets will help us answer and draw attention to methodological developments that will facilitate this.

Accounting for animal movement improves vaccination strategies against wildlife disease in heterogeneous landscapes

Oral baiting is used to deliver vaccines to wildlife to prevent, control, and eliminate infectious diseases. A central challenge is how to spatially distribute baits to maximize encounters by target animal populations, particularly in urban and suburban areas where wildlife such as raccoons (Procyon lotor) are abundant and baits are delivered along roads. Methods from movement ecology that quantify movement and habitat selection could help to optimize baiting strategies by more effectively targeting wildlife populations across space. We developed a spatially explicit, individual-based model of raccoon movement and oral rabies vaccine seroconversion to examine whether and when baiting strategies that match raccoon movement patterns perform better than currently used baiting strategies in an oral rabies vaccination zone in greater Burlington, Vermont, USA. Habitat selection patterns estimated from locally radio-collared raccoons were used to parameterize movement simulations. We then used our simulations to estimate raccoon population rabies seroprevalence under currently used baiting strategies (actual baiting) relative to habitat selection-based baiting strategies (habitat baiting). We conducted simulations on the Burlington landscape and artificial landscapes that varied in heterogeneity relative to Burlington in the proportion and patch size of preferred habitats. We found that the benefits of habitat baiting strongly depended on the magnitude and variability of raccoon habitat selection and the degree of landscape heterogeneity within the baiting area. Habitat baiting improved seroprevalence over actual baiting for raccoons characterized as habitat specialists but not for raccoons that displayed weak habitat selection similar to radiocollared individuals, except when baits were delivered off roads where preferred habitat coverage and complexity was more pronounced. In contrast, in artificial landscapes with either more strongly juxtaposed favored habitats and/or higher proportions of favored habitats, habitat baiting performed better than actual baiting, even when raccoons displayed weak habitat preferences and where baiting was constrained to roads. Our results suggest that habitat selection-based baiting could increase raccoon population seroprevalence in urban-suburban areas, where practical, given the heterogeneity and availability of preferred habitat types in those areas. Our novel simulation approach provides a flexible framework to test alternative baiting strategies in multiclass landscapes to optimize bait-distribution strategies.

Social Behavior, Community Composition, Pathogen Strain, and Host Symbionts Influence Fungal Disease Dynamics in Salamanders

The emerging fungal pathogen, Batrachochytrium dendrobatidis (Bd), which can cause a fatal disease called chytridiomycosis, is implicated in the collapse of hundreds of host amphibian species. We describe chytridiomycosis dynamics in two co-occurring terrestrial salamander species, the Santa Lucia Mountains slender salamander, Batrachoseps luciae, and the arboreal salamander, Aneides lugubris. We (1) conduct a retrospective Bd-infection survey of specimens collected over the last century, (2) estimate present-day Bd infections in wild populations, (3) use generalized linear models (GLM) to identify biotic and abiotic correlates of infection risk, (4) investigate susceptibility of hosts exposed to Bd in laboratory trials, and (5) examine the ability of host skin bacteria to inhibit Bd in culture. Our historical survey of 2,866 specimens revealed that for most of the early 20th century (~1920–1969), Bd was not detected in either species. By the 1990s the proportion of infected specimens was 29 and 17% (B. luciae and A. lugubris, respectively), and in the 2010s it was 10 and 17%. This was similar to the number of infected samples from contemporary populations (2014–2015) at 10 and 18%. We found that both hosts experience signs of chytridiomycosis and suffered high Bd-caused mortality (88 and 71% for B. luciae and A. lugubris, respectively). Our GLM revealed that Bd-infection probability was positively correlated with intraspecific group size and proximity to heterospecifics but not to abiotic factors such as precipitation, minimum temperature, maximum temperature, mean temperature, and elevation, or to the size of the hosts. Finally, we found that both host species contain symbiotic skin-bacteria that inhibit growth of Bd in laboratory trials. Our results provide new evidence consistent with other studies showing a relatively recent Bd invasion of amphibian host populations in western North America and suggest that the spread of the pathogen may be enabled both through conspecific and heterospecific host interactions. Our results suggest that wildlife disease studies should assess host-pathogen dynamics that consider the interactions and effects of multiple hosts, as well as the historical context of pathogen invasion, establishment, and epizootic to enzootic transitions to better understand and predict disease dynamics.

Evolution of pathogen tolerance and emerging infections: A missing experimental paradigm

Researchers worldwide are repeatedly warning us against future zoonotic diseases resulting from humankind's insurgence into natural ecosystems. The same zoonotic pathogens that cause severe infections in a human host frequently fail to produce any disease outcome in their natural hosts. What precise features of the immune system enable natural reservoirs to carry these pathogens so efficiently? To understand these effects, we highlight the importance of tracing the evolutionary basis of pathogen tolerance in reservoir hosts, while drawing implications from their diverse physiological and life-history traits, and ecological contexts of host-pathogen interactions. Long-term co-evolution might allow reservoir hosts to modulate immunity and evolve tolerance to zoonotic pathogens, increasing their circulation and infectious period. Such processes can also create a genetically diverse pathogen pool by allowing more mutations and genetic exchanges between circulating strains, thereby harboring rare alive-on-arrival variants with extended infectivity to new hosts (i.e., spillover). Finally, we end by underscoring the indispensability of a large multidisciplinary empirical framework to explore the proposed link between evolved tolerance, pathogen prevalence, and spillover in the wild.

Resistance Correlations Influence Infection by Foreign Pathogens

AbstractReciprocal selection promotes the specificity of host-pathogen associations and resistance polymorphisms in response to disease. However, plants and animals also vary in response to pathogen species not previously encountered in nature, with potential effects on new disease emergence. Using anther smut disease, we show that resistance (measured as infection rates) to foreign pathogens can be correlated with standing variation in resistance to an endemic pathogen. In Silene vulgaris, genetic variation in resistance to its endemic anther smut pathogen correlated positively with resistance variation to an anther smut pathogen from another host, but the relationship was negative between anther smut and a necrotrophic pathogen. We present models describing the genetic basis for assessing resistance relationships between endemic and foreign pathogens and for quantifying infection probabilities on foreign pathogen introduction. We show that even when the foreign pathogen has a lower average infection ability than the endemic pathogen, infection outcomes are determined by the sign and strength of the regression of the host's genetic variation in infection rates by a foreign pathogen on variation in infection rates by an endemic pathogen as well as by resistance allele frequencies. Given that preinvasion equilibria of resistance are determined by factors including resistance costs, we show that protection against foreign pathogens afforded by positively correlated resistances can be lessened or even result in elevated infection risk at the population level, depending on local dynamics. Therefore, a pathogen's emergence potential could be influenced not only by its average infection rate but also by resistance variation resulting from prior selection imposed by endemic diseases.

Stability analysis of the coexistence equilibrium of a balanced metapopulation model

We analyze the stability of a unique coexistence equilibrium point of a system of ordinary differential equations (ODE system) modelling the dynamics of a metapopulation, more specifically, a set of local populations inhabiting discrete habitat patches that are connected to one another through dispersal or migration. We assume that the inter-patch migrations are detailed balanced and that the patches are identical with intra-patch dynamics governed by a mean-field ODE system with a coexistence equilibrium. By making use of an appropriate Lyapunov function coupled with LaSalle's invariance principle, we are able to show that the coexistence equilibrium point within each patch is locally asymptotically stable if the inter-patch dispersal network is heterogeneous, whereas it is neutrally stable in the case of a homogeneous network. These results provide a mathematical proof confirming the existing numerical simulations and broaden the range of networks for which they are valid.

Echinococcoses in Iran, Turkey, and Pakistan: Old Diseases in the New Millennium

Echinococcosis is considered a cosmopolitan zoonosis caused by different species of small taeniid tapeworms of the genus Echinococcus and is regarded as a neglected zoonosis. Cystic and alveolar echinococcoses are endemic diseases of Tibetan, Pamir, and Iranian plateaus. All of the countries within the Iranian plateau are affected by echinococcosis. Pakistan, Turkey, and Iran are the three most populous countries of the region, in which echinococcosis is highly endemic. The three neighboring countries share strong cultural and socioeconomic ties. The present study aimed to provide a broad review of the status of cystic and alveolar echinococcosis, summarizing the current knowledge about geographical distribution, molecular epidemiology, and transmission dynamics of Echinococcus granulosus sensu lato and Echinococcus multilocularis in this region. Additionally, we aimed to understand disease burden and risk factors as basic requirements for establishing a surveillance system and planning prevention and control programs. A considerable body of information is available on different aspects of echinococcosis in this region; however, several information and research gaps need to be filled before planning control programs. None of the countries in the region have an elaborate echinococcosis control program. Effective control programs require multi/intersectoral coordination within a One Health approach with a long-term political and administrative commitment and enhanced international collaboration among the three countries.

The dilution effect behind the scenes: testing the underlying assumptions of its mechanisms through quantifying the long-term dynamics and effects of a pathogen in multiple host species

Disentangling the mechanisms that mediate the relationships between species diversity and disease risk has both theoretical and applied implications. We employed a model system of rodents and their Mycoplasma pathogens, in which an extreme negative diversity-disease relationship was demonstrated, to test the assumptions underlying three mechanisms that may explain this field pattern. Through quantifying the long-term dynamics and effects of the pathogen in its three host species, we estimated the between-host differences in pathogen spreading and transmission potentials, and host recovery potential and vulnerability to infection. The results suggest that one of the hosts is a pathogen amplifier and the other two hosts function as diluters. Considering the similarity in infection success and intensity among hosts, and the failure to detect any pathogen-induced damage, we could not validate the assumption underlying the hypotheses that diluters reduce the overall transmission or increase the mortality of infected hosts in the system. Instead, the results demonstrate that diluters clear the infection faster than amplifiers, supporting the possibility that the addition of diluters to the community may reduce the overall number of infected hosts through this mechanism. This study highlights the contribution of experimental studies that simultaneously explore different aspects of host-pathogen interactions in multiple hosts, in diversity-disease research.

The Relationship Between GPS Sampling Interval and Estimated Daily Travel Distances in Chacma Baboons (Papio ursinus)

Modern studies of animal movement use the Global Positioning System (GPS) to estimate animals’ distance traveled. The temporal resolution of GPS fixes recorded should match those of the behavior of interest; otherwise estimates are likely to be inappropriate. Here, we investigate how different GPS sampling intervals affect estimated daily travel distances for wild chacma baboons (Papio ursinus). By subsampling GPS data collected at one fix per second for 143 daily travel distances (12 baboons over 11–12 days), we found that less frequent GPS fixes result in smaller estimated travel distances. Moving from a GPS frequency of one fix every second to one fix every 30 s resulted in a 33% reduction in estimated daily travel distance, while using hourly GPS fixes resulted in a 66% reduction. We then use the relationship we find between estimated travel distance and GPS sampling interval to recalculate published baboon daily travel distances and find that accounting for the predicted effect of sampling interval does not affect conclusions of previous comparative analyses. However, if short-interval or continuous GPS data—which are becoming more common in studies of primate movement ecology—are compared with historical (longer interval) GPS data in future work, controlling for sampling interval is necessary.

Ecology, evolution, and epidemiology of zoonotic and vector-borne infectious diseases in French Guiana: Transdisciplinarity does matter to tackle new emerging threats

French Guiana is a European ultraperipheric region located on the northern Atlantic coast of South America. It constitutes an important forested region for biological conservation in the Neotropics. Although very sparsely populated, with its inhabitants mainly concentrated on the Atlantic coastal strip and along the two main rivers, it is marked by the presence and development of old and new epidemic disease outbreaks, both research and health priorities. In this review paper, we synthetize 15 years of multidisciplinary and integrative research at the interface between wildlife, ecosystem modification, human activities and sociodemographic development, and human health. This study reveals a complex epidemiological landscape marked by important transitional changes, facilitated by increased interconnections between wildlife, land-use change and human occupation and activity, human and trade transportation, demography with substantial immigration, and identified vector and parasite pharmacological resistance. Among other French Guianese characteristics, we demonstrate herein the existence of more complex multi-host disease life cycles than previously described for several disease systems in Central and South America, which clearly indicates that today the greater promiscuity between wildlife and humans due to demographic and economic pressures may offer novel settings for microbes and their hosts to circulate and spread. French Guiana is a microcosm that crystallizes all the current global environmental, demographic and socioeconomic change conditions, which may favor the development of ancient and future infectious diseases.

Quantifying 25 years of disease-caused declines in Tasmanian devil populations: host density drives spatial pathogen spread

Infectious diseases are strong drivers of wildlife population dynamics, however, empirical analyses from the early stages of pathogen emergence are rare. Tasmanian devil facial tumour disease (DFTD), discovered in 1996, provides the opportunity to study an epizootic from its inception. We use a pattern-oriented diffusion simulation to model the spatial spread of DFTD across the species' range and quantify population effects by jointly modelling multiple streams of data spanning 35 years. We estimate the wild devil population peaked at 53 000 in 1996, less than half of previous estimates. DFTD spread rapidly through high-density areas, with spread velocity slowing in areas of low host densities. By 2020, DFTD occupied >90% of the species' range, causing 82% declines in local densities and reducing the total population to 16 900. Encouragingly, our model forecasts the population decline should level-off within the next decade, supporting conservation management focused on facilitating evolution of resistance and tolerance.

Movement can mediate temporal mismatches between resource availability and biological events in host-pathogen interactions

Global change is shifting the timing of biological events, leading to temporal mismatches between biological events and resource availability. These temporal mismatches can threaten species' populations. Importantly, temporal mismatches not only exert strong pressures on the population dynamics of the focal species, but can also lead to substantial changes in pairwise species interactions such as host-pathogen systems. We adapted an established individual-based model of host-pathogen dynamics. The model describes a viral agent in a social host, while accounting for the host's explicit movement decisions. We aimed to investigate how temporal mismatches between seasonal resource availability and host life-history events affect host-pathogen coexistence, that is, disease persistence. Seasonal resource fluctuations only increased coexistence probability when in synchrony with the hosts' biological events. However, a temporal mismatch reduced host-pathogen coexistence, but only marginally. In tandem with an increasing temporal mismatch, our model showed a shift in the spatial distribution of infected hosts. It shifted from an even distribution under synchronous conditions toward the formation of disease hotspots, when host life history and resource availability mismatched completely. The spatial restriction of infected hosts to small hotspots in the landscape initially suggested a lower coexistence probability due to the critical loss of susceptible host individuals within those hotspots. However, the surrounding landscape facilitated demographic rescue through habitat-dependent movement. Our work demonstrates that the negative effects of temporal mismatches between host resource availability and host life history on host-pathogen coexistence can be reduced through the formation of temporary disease hotspots and host movement decisions, with implications for disease management under disturbances and global change.

Elk migration influences the risk of disease spillover in the Greater Yellowstone Ecosystem

Wildlife migrations provide important ecosystem services, but they are declining. Within the Greater Yellowstone Ecosystem (GYE), some elk Cervus canadensis herds are losing migratory tendencies, which may increase spatiotemporal overlap between elk and livestock (domestic bison Bison bison and cattle Bos taurus), potentially exacerbating pathogen transmission risk.

We combined disease, movement, demographic and environmental data from eight elk herds in the GYE to examine the differential risk of brucellosis transmission (through aborted foetuses) from migrant and resident elk to livestock.

For both migrants and residents, we found that transmission risk from elk to livestock occurred almost exclusively on private ranchlands as opposed to state or federal grazing allotments. Weather variability affected the estimated distribution of spillover risk from migrant elk to livestock, with a 7%–12% increase in migrant abortions on private ranchlands during years with heavier snowfall. In contrast, weather variability did not affect spillover risk from resident elk.

Migrant elk were responsible for the majority (68%) of disease spillover risk to livestock because they occurred in greater numbers than resident elk. On a per‐capita basis, however, our analyses suggested that resident elk disproportionately contributed to spillover risk. In five of seven herds, we estimated that the per‐capita spillover risk was greater from residents than from migrants. Averaged across herds, an individual resident elk was 23% more likely than an individual migrant elk to abort on private ranchlands.

Our results demonstrate links between migration behaviour, spillover risk and environmental variability, and highlight the utility of integrating models of pathogen transmission and host movement to generate new insights about the role of migration in disease spillover risk. Furthermore, they add to the accumulating body of evidence across taxa that suggests that migrants and residents should be considered separately during investigations of wildlife disease ecology. Finally, our findings have applied implications for elk and brucellosis in the GYE. They suggest that managers should prioritize actions that maintain spatial separation of elk and livestock on private ranchlands during years when snowpack persists into the risk period.

The role of social structure and dynamics in the maintenance of endemic disease

Social interactions are required for the direct transmission of infectious diseases. Consequently, the social network structure of populations plays a key role in shaping infectious disease dynamics. A huge research effort has examined how specific social network structures make populations more (or less) vulnerable to damaging epidemics. However, it can be just as important to understand how social networks can contribute to endemic disease dynamics, in which pathogens are maintained at stable levels for prolonged periods of time. Hosts that can maintain endemic disease may serve as keystone hosts for multi-host pathogens within an ecological community, and also have greater potential to act as key wildlife reservoirs of agricultural and zoonotic diseases. Here, we examine combinations of social and demographic processes that can foster endemic disease in hosts. We synthesise theoretical and empirical work to demonstrate the importance of both social structure and social dynamics in maintaining endemic disease. We also highlight the importance of distinguishing between the local and global persistence of infection and reveal how different social processes drive variation in the scale at which infectious diseases appear endemic. Our synthesis provides a framework by which to understand how sociality contributes to the long-term maintenance of infectious disease in wildlife hosts and provides a set of tools to unpick the social and demographic mechanisms involved in any given host-pathogen system.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00265-021-03055-8.

Fitness outcomes in relation to individual variation in constitutive innate immune function

Although crucial for host survival when facing persistent parasite pressure, costly immune functions will inevitably compete for resources with other energetically expensive traits such as reproduction. Optimizing, but not necessarily maximizing, immune function might therefore provide net benefit to overall host fitness. Evidence for associations between fitness and immune function is relatively rare, limiting our potential to understand ultimate fitness costs of immune investment. Here, we assess how measures of constitutive immune function (haptoglobin, natural antibodies, complement activity) relate to subsequent fitness outcomes (survival, reproductive success, dominance acquisition) in a wild passerine (Malurus coronatus). Surprisingly, survival probability was not positively linearly predicted by any immune index. Instead, both low and high values of complement activity (quadratic effect) were associated with higher survival, suggesting that different immune investment strategies might reflect a dynamic disease environment. Positive linear relationships between immune indices and reproductive success suggest that individual heterogeneity overrides potential resource reallocation trade-offs within individuals. Controlling for body condition (size-adjusted body mass) and chronic stress (heterophil-lymphocyte ratio) did not alter our findings in a sample subset with available data. Overall, our results suggest that constitutive immune components have limited net costs for fitness and that variation in immune maintenance relates to individual differences more closely.

A mechanistic, stigmergy model of territory formation in solitary animals: Territorial behavior can dampen disease prevalence but increase persistence

Although movement ecology has leveraged models of home range formation to explore the effects of spatial heterogeneity and social cues on movement behavior, disease ecology has yet to integrate these potential drivers and mechanisms of contact behavior into a generalizable disease modeling framework. Here we ask how dynamic territory formation and maintenance might contribute to disease dynamics in a territorial, solitary predator for an indirectly transmitted pathogen. We developed a mechanistic individual-based model where stigmergy—the deposition of signals into the environment (e.g., scent marking, scraping)—dictates local movement choices and long-term territory formation, but also the risk of pathogen transmission. Based on a variable importance analysis, the length of the infectious period was the single most important variable in predicting outbreak success, maximum prevalence, and outbreak duration. Host density and rate of pathogen decay were also key predictors. We found that territoriality best reduced maximum prevalence in conditions where we would otherwise expect outbreaks to be most successful: slower recovery rates (i.e., longer infectious periods) and higher conspecific densities. However, for slower pathogen decay rates, stigmergy-driven movement increased outbreak durations relative to random movement simulations. Our findings therefore support a limited version of the “territoriality benefits” hypothesis—where reduced home range overlap leads to reduced opportunities for pathogen transmission, but with the caveat that reduction in outbreak severity may increase the likelihood of pathogen persistence. For longer infectious periods and higher host densities, key trade-offs emerged between the strength of pathogen load, the strength of the stigmergy cue, and the rate at which those two quantities decayed; this finding raises interesting questions about the evolutionary nature of these competing processes and the role of possible feedbacks between parasitism and territoriality. This work also highlights the importance of considering social cues as part of the movement landscape in order to better understand the consequences of individual behaviors on population level outcomes.

Making decisions about conservation and disease management relies on our understanding of what allows animal populations to be successful, which often depends on when and where animals encounter each other. However, disease ecology often focuses on the social behavior of animals without accounting for their individual movement patterns. We developed a simulation model that bridges the fields of disease and movement ecology by allowing hosts to inform their movement based on the past movements of other hosts. As hosts navigate their environment, they leave behind a scent trail while avoiding the scent trails of other individuals. We wanted to know if this means of territory formation could heighten or dampen disease spread when infectious hosts leave pathogens in their wake. We found that territoriality can inhibit disease spread under conditions that we would normally expect pathogens to be most successful: when there are many hosts on the landscape and hosts stay infectious for longer. This work points to how incorporating movement behavior into disease models can provide improved understanding of how diseases spread in wildlife populations; such understanding is particularly important in the face of combatting ongoing and emerging infectious diseases.

Variation in host home range size decreases rabies vaccination effectiveness by increasing the spatial spread of rabies virus

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.

Living with liver flukes: Does migration matter?

Migration is typically thought to be an evolved trait driven by responses to forage or predation, but recent studies have demonstrated avoidance of parasitism can also affect success of migratory tactics within a population. We evaluated hypotheses of how migration alters parasite exposure in a partially migratory elk (Cervus canadensis) population in and adjacent to Banff National Park, Alberta, Canada. Equal numbers of elk remain year-round on the winter range or migrate to summer range. We quantified diversity and abundance of parasites in faecal elk pellets, and prevalence (number of infected individuals) and intensity (egg counts) of giant liver fluke eggs (Fascioloides magna) in faeces across migratory tactics. We tested whether giant liver fluke intensity in faeces was affected by elk use of wetlands, elevation, forage biomass, and elk concentration in the previous summer. We rejected the "migratory escape" hypothesis that suggests migration allowed elk to escape parasite exposure because migrant elk had the highest richness and evenness of parasite groups. We also rejected the hypothesis that prevalence was highest at highest summer densities because higher-density resident elk had the lowest diversity and giant liver fluke egg presence and intensity. Instead, the high prevalence and intensity of giant liver flukes in migrants was consistent with both the hypothesis of "environmental tracking", because elk that migrated earlier may expose themselves to favourable parasite conditions, and with the "environmental sampling" hypothesis, because giant liver fluke intensity increased with increased exposure to secondary host habitat (i.e., wetland). Our results indicate that differential exposure of different migratory tactics that leave the winter range has a greater influence on parasites than the concentration of elk that reside on the winter range year-round.

A unifying framework for the transient parasite dynamics of migratory hosts

Migrations allow animals to track seasonal changes in resources, find mates, and avoid harsh climates, but these regular, long-distance movements also have implications for parasite dynamics and animal health. Migratory animals have been dubbed "superspreaders" of infection, but migration can also reduce parasite burdens within host populations via migratory escape from contaminated habitats and transmission hotspots, migratory recovery due to parasite mortality, and migratory culling of infected individuals. Here, we show that a single migratory host-macroparasite model can give rise to these different phenomena under different parametrizations, providing a unifying framework for a mechanistic understanding of the parasite dynamics of migratory animals. Importantly, our model includes the impact of parasite burden on host movement capability during migration, which can lead to "parasite-induced migratory stalling" due to a positive feedback between increasing parasite burdens and reduced movement. Our results provide general insight into the conditions leading to different health outcomes in migratory wildlife. Our approach lays the foundation for tactical models that can help understand, predict, and mitigate future changes of disease risk in migratory wildlife that may arise from shifting migratory patterns, loss of migratory behavior, or climate effects on parasite development, mortality, and transmission.

Challenges and Opportunities Developing Mathematical Models of Shared Pathogens of Domestic and Wild Animals

Diseases that affect both wild and domestic animals can be particularly difficult to prevent, predict, mitigate, and control. Such multi-host diseases can have devastating economic impacts on domestic animal producers and can present significant challenges to wildlife populations, particularly for populations of conservation concern. Few mathematical models exist that capture the complexities of these multi-host pathogens, yet the development of such models would allow us to estimate and compare the potential effectiveness of management actions for mitigating or suppressing disease in wildlife and/or livestock host populations. We conducted a workshop in March 2014 to identify the challenges associated with developing models of pathogen transmission across the wildlife-livestock interface. The development of mathematical models of pathogen transmission at this interface is hampered by the difficulties associated with describing the host-pathogen systems, including: (1) the identity of wildlife hosts, their distributions, and movement patterns; (2) the pathogen transmission pathways between wildlife and domestic animals; (3) the effects of the disease and concomitant mitigation efforts on wild and domestic animal populations; and (4) barriers to communication between sectors. To promote the development of mathematical models of transmission at this interface, we recommend further integration of modern quantitative techniques and improvement of communication among wildlife biologists, mathematical modelers, veterinary medicine professionals, producers, and other stakeholders concerned with the consequences of pathogen transmission at this important, yet poorly understood, interface.

Disease outbreak thresholds emerge from interactions between movement behavior, landscape structure, and epidemiology

Disease models have provided conflicting evidence as to whether spatial heterogeneity promotes or impedes pathogen persistence. Moreover, there has been limited theoretical investigation into how animal movement behavior interacts with the spatial organization of resources (e.g., clustered, random, uniform) across a landscape to affect infectious disease dynamics. Importantly, spatial heterogeneity of resources can sometimes lead to nonlinear or counterintuitive outcomes depending on the host and pathogen system. There is a clear need to develop a general theoretical framework that could be used to create testable predictions for specific host-pathogen systems. Here, we develop an individual-based model integrated with movement ecology approaches to investigate how host movement behaviors interact with landscape heterogeneity (in the form of various levels of resource abundance and clustering) to affect pathogen dynamics. For most of the parameter space, our results support the counterintuitive idea that fragmentation promotes pathogen persistence, but this finding was largely dependent on perceptual range of the host, conspecific density, and recovery rate. For simulations with high conspecific density, slower recovery rates, and larger perceptual ranges, more complex disease dynamics emerged, and the most fragmented landscapes were not necessarily the most conducive to outbreaks or pathogen persistence. These results point to the importance of interactions between landscape structure, individual movement behavior, and pathogen transmission for predicting and understanding disease dynamics.

HexSim: a modeling environment for ecology and conservation

CONTEXT

Simulation models are increasingly used in both theoretical and applied studies to explore system responses to natural and anthropogenic forcing functions, develop defensible predictions of future conditions, challenge simplifying assumptions that facilitated past research, and to train students in scientific concepts and technology. Researcher's increased use of simulation models has created a demand for new platforms that balance performance, utility, and flexibility.

OBJECTIVES

We describe HexSim, a powerful new spatially-explicit, individual-based modeling framework that will have applications spanning diverse landscape settings, species, stressors, and disciplines (e.g. ecology, conservation, genetics, epidemiology). We begin with a model overview and follow-up with a discussion of key formative studies that influenced HexSim's development. We then describe specific model applications of relevance to readers of Landscape Ecology. Our goal is to introduce readers to this new modeling platform, and to provide examples characterizing its novelty and utility.

CONCLUSIONS

With this publication, we conclude a >10 year development effort, and assert that our HexSim model is mature, robust, extremely well tested, and ready for adoption by the research community. The HexSim model, documentation, worked examples, and other materials can be freely obtained from the website www.hexsim.net.

Quantifying direct and indirect contacts for the potential transmission of infection between species using a multilayer contact network

Detecting opportunities for between-species transmission of pathogens can be challenging, particularly if rare behaviours or environmental transmission are involved. We present a multilayer network framework to quantify transmission potential in multi-host systems, incorporating environmental transmission, by using empirical data on direct and indirect contacts between European badgers Meles meles and domestic cattle. We identify that indirect contacts via the environment at badger latrines on pasture are likely to be important for transmission within badger populations and between badgers and cattle. We also find a positive correlation between the role of individual badgers within the badger social network, and their role in the overall badger-cattle-environment network, suggesting that the same behavioural traits contribute to the role of individual badgers in within- and between-species transmission. These findings have implications for disease management interventions in this system, and our novel network approach can provide general insights into transmission in other multi-host disease systems.