Host Spatial Structure Research Articles

Ecology and Chronic Wasting Disease Epidemiology Shape Prion Protein Gene Variation in Rocky Mountain Elk (Cervus elaphus nelsoni).

As chronic wasting disease (CWD) continues to spread across North America, the relationship between CWD and host genetics has become of interest. In Rocky Mountain elk (Cervus elaphus nelsoni), one or two copies of a leucine allele at codon 132 of the prion protein gene (132L*) has been shown to prolong the incubation period of CWD. Our study examined the relationship between CWD epidemiology and codon 132 evolution in elk from Wyoming, USA, from 2011 to 2018. Using PCR and Sanger sequencing, we genotyped 997 elk and assessed the relationship between genotype and CWD prevalence estimated from surveillance data. Using logistic regression, we showed that each 1% increase in CWD prevalence is associated with a 9.6% increase in the odds that an elk would have at least one copy of leucine at codon 132. In some regions, however, 132L* variants were found in the absence of CWD, indicating that evolutionary and epidemiologic patterns can be heterogeneous across space and time. We also provide evidence that naturally occurring CWD is not rare in 132L* elk, which merits the study of shedding kinetics in 132L* elk and the influence of genotype on CWD strain diversity. The management implications of cervid adaptations to CWD are difficult to predict. Studies that investigate the degree to which evolutionary outcomes are shaped by host spatial structure can provide useful epidemiologic insight, which can in turn aid management by informing scale and extent of mitigation actions.

Identifying individual and spatial drivers of heterogeneous transmission and virulence of malaria in Caribbean anoles

AbstractHeterogeneous distributions are a fundamental principle of ecology, manifesting as natural variability within ecological levels of organization from individuals to ecosystems. In disease ecology, variability in biotic and abiotic factors can result in heterogeneous patterns of transmission and virulence—broadly defined here as the negative consequences of infection. Still, our classic theoretical understanding of disease dynamics comes from models that assume homogeneous transmission and virulence. Here, we test this assumption by assessing the contribution of various sources of individual and spatial heterogeneity to patterns of transmission and sublethal measurements of virulence in two lizard–malaria systems: a three‐parasite assemblage (Plasmodium floridense,Plasmodium leukocytica, andPlasmodium azurophilum) infecting the lizardAnolis gundlachiin the rainforest of Puerto Rico and a single‐parasite system (P. floridense–Anolis sagrei) in Florida. Using a Bayesian model selection framework, we evaluated whether individual host differences (i.e., body size and sex) or spatial variability (i.e., habitat type and local‐scale host spatial structure) drive heterogeneity in the probability of infection or its associated health costs (i.e., body condition, blood chemistry). We found that the probability of infection increases with increasing lizard body size in both systems. However, in Florida, we found the relationship to be subdued in deforested habitats compared to the adjacent urban hydric forests. Furthermore, infection was spatially clustered within sampling sites, with “hot” and “cold” spots across the landscape. Nevertheless, we found no clear evidence of costs of infection on lizard health in any of the measures assessed and hence no grounds for inference regarding heterogeneous virulence. Ultimately, the consistency of our results across systems suggests prominent roles of individual and spatial heterogeneities as driving factors of transmission of vector‐borne diseases.

Space matters: host spatial structure and the dynamics of plague transmission

The development of models to elucidate the transmission pathways and dynamics of wildlife diseases remains challenging. Sylvatic plague, caused by the bacterium Yersinia pestis (Yp), is an infectious zoonotic disease that primarily affects wild rodents, including prairie dogs (Cynomys spp.) in North America. Proposed transmission pathways for Yp include flea bites, direct contacts between hosts, and environmental reservoirs (e.g. soil, carcasses). We developed a spatially explicit, agent-based model of Yp transmission to explore the effects of alternative transmission pathways, different disease initiation mechanisms (host or fleas), parameter uncertainty, and spatial structure of hosts. A particularly novel aspect of our model was the integration of ecological models with traditional disease models. Specifically, we used estimates from spatial capture-recapture models to generate data-driven spatial distributions, densities, and contact rates to capture the spatial structure of prairie dogs. We simulated ~9 million scenarios across a wide range of parameter values and conducted sensitivity analyses to determine the most influential parameters on the number of flea-days (sum of the mean number of fleas on hosts each day of the simulation), number of newly infected hosts per day, the time to depopulation (<20 prairie dogs remaining), and the proportion of the prairie dog population remaining at the end of the simulation (after 150 days). When including spatial structure, we found the probability of transmission via environmental sources of Yp (i.e. carcasses) had the greatest influence on model results when Yp infection was initiated in prairie dog hosts, rather than in fleas. Conversely, the mechanism of transmission by fleas to prairie dogs had the greatest influence on model results when Yp infection was initiated in fleas (i.e. via introduction by carnivores, a migrant prairie dog, or other mammalian host). Uncertainty in parameter estimates, particularly those related to the transmission pathways of Yp, continue to hamper efforts to realistically model plague dynamics in wild rodents. Our results elucidate the complexity of the flea-plague-prairie dog system and reiterate the importance of research on Yp transmission mechanisms to provide a full understanding of this disease. Our results also emphasize the importance of realistic estimates of spatial structure for exploring transmission dynamics of wildlife diseases and provide a framework for generating a data-driven description of spatial structure.

Host spatial structure and disperser activity determine mistletoe infection patterns

What processes and factors are responsible for species distribution are long‐standing questions in ecology and a key element for conservation and management. Mistletoes provide the opportunity to study a forest species whose occurrence is expected to be constrained by multiple factors as a consequence of their life form. We studied the mistletoe Tristerix corymbosus (Loranthaceae) on its most common hosts species in northwest Patagonia. The seeds of this mistletoe are almost exclusively dispersed by the small arboreal and endemic marsupial Dromiciops gliroides (Microbiotheridae). We assessed the underlying causes of plant spatial patterns through point pattern analysis and we used different variables that characterize the neighborhood around each host to analyze the relative effect of host availability, potential for disperser movement and canopy light conditions. We found that potential hosts were strongly aggregated and that the three most common host species were distributed independent of each other. Considering all host species together, infected and non‐infected host were individually aggregated but segregated from each other. The aggregated pattern of infected hosts could be explained in part by the template of potential hosts distribution, but was subsequently modulated by the activity of the mistletoe disperser. Potential for disperser movement, the proximity to reproductive mistletoes and habitat complexity, increased mistletoe infection probability. However, neighboring host availability decreased mistletoe infection probability, and tree DBH (used as surrogate for light conditions) had no detectable effect. Our results suggested that the distribution of mistletoe infection was determined by the structure of potential host populations and by the marsupial disperser activity. Compared to bird dispersed mistletoes, the scale of the infection was smaller and the proximity to reproductive mistletoes and habitat complexity were important for seed arrival and infection. The interplay between landscape structure and disperser activity determine the spatial structure of mistletoe future generations.

Mechanisms for lyssavirus persistence in non-synanthropic bats in Europe: insights from a modeling study

Bats are natural reservoirs of the largest proportion of viral zoonoses among mammals, thus understanding the conditions for pathogen persistence in bats is essential to reduce human risk. Focusing on the European Bat Lyssavirus subtype 1 (EBLV-1), causing rabies disease, we develop a data-driven spatially explicit metapopulation model to investigate EBLV-1 persistence in Myotis myotis and Miniopterus schreibersii bat species in Catalonia. We find that persistence relies on host spatial structure through the migratory nature of M. schreibersii, on cross-species mixing with M. myotis, and on survival of infected animals followed by temporary immunity. The virus would not persist in the single colony of M. myotis. Our study provides for the first time epidemiological estimates for EBLV-1 progression in M. schreibersii. Our approach can be readily adapted to other zoonoses of public health concern where long-range migration and habitat sharing may play an important role.

Inbreeding in stochastic subdivided mating systems: the genetic consequences of host spatial structure, aggregated transmission dynamics and life history characteristics in parasite populations.

Inbreeding in parasite populations can have important epidemiological and evolutionary implications. However, theoretical models have predominantly focussed on the evolution of parasite populations under strong selection or in epidemic situations, and our understanding of neutral gene dynamics in parasite populations at equilibrium has been limited to verbal arguments or conceptual models. This study focusses on how host-parasite population dynamics affects observed levels of inbreeding in a random sample of parasites from an infinite population of hosts by bridging traditional genetic and parasitological processes utilizing a backward-forward branching Markov process embedded within a flexible statistical framework, the logarithmic-poisson mixture model. My results indicate that levels of inbreeding in parasites are impacted by demographic and/or transmission dynamics (subdivided mating, aggregated transmission dynamics and host spatial structure), and that this inbreeding is poorly estimated by 'equilibrium' levels of inbreeding calculated assuming regular systems of mating. Specifically, the model reveals that at low levels of inbreeding (F ≤ 0.1), equilibrium levels of inbreeding are lower than those observed, while at high levels of inbreeding the opposite pattern occurs. The model also indicates that inbreeding could have important epidemiological implications (e.g., the spread of recessive drug resistance genes) by directly impacting the observed frequency of rare homozygotes in parasite populations. My results indicate that frequencies of rare homozygotes are affected by aggregated transmission dynamics and host spatial structure, and also that an increase in the frequency of rare homozygotes can be caused by a decrease in effective population size solely due to the presence of a subdivided breeding system.

Host behavior alters spiny lobster-viral disease dynamics: a simulation study.

Social behavior confers numerous benefits to animals but also risks, among them an increase in the spread of pathogenic diseases. We examined the trade-off between risk of predation and disease transmission under different scenarios of host spatial structure and disease avoidance behavior using a spatially explicit, individual-based model of the host pathogen interaction between juvenile Caribbean spiny lobster (Panulirus argus) and Panulirus argus Virus 1 (PaV1). Spiny lobsters are normally social but modify their behavior to avoid diseased conspecifics, a potentially effective means of reducing transmission but one rarely observed in the wild. We found that without lobster avoidance of diseased conspecifics, viral outbreaks grew in intensity and duration in simulations until the virus was maintained continuously at unrealistically high levels. However, when we invoked disease avoidance at empirically observed levels, the intensity and duration of outbreaks was reduced and the disease extirpated within five years. Increased lobster (host) spatial aggregation mimicking that which occurs when sponge shelters for lobsters are diminished by harmful algal blooms, did not significantly increase PaV1 transmission or persistence in lobster populations. On the contrary, behavioral aversion of diseased conspecifics effectively reduced viral prevalence, even when shelters were limited, which reduced shelter availability for all lobsters but increased predation, especially of infected lobsters. Therefore, avoidance of diseased conspecifics selects against transmission by contact, promotes alternative modes of transmission, and results in a more resilient host-pathogen system.

Elevational disease distribution in a natural plant–pathogen system: insights from changes across host populations and climate

Understanding the factors determining the distribution of parasites and pathogens in natural systems is essential for making predictions about the spread of emerging infectious disease. Here, we report the distribution of the fungal anther‐smut disease, caused by Microbotryum spp., on populations of the European wildflower Silene vulgaris over a range of elevations. A survey of several geographically distinct mountains in the southern French alps found that anther‐smut disease was restricted to high elevations, rarely observed below 1300 m despite availability of hosts below this elevation. Anther smut causes host‐sterility, and is recognized as a model system for natural host–pathogen interactions, sharing common features with vector‐borne and sexually‐transmitted disease in animals. In such systems, many biotic and abiotic factors likely to change over ecological gradients can influence disease epidemiology, including host spatial structure, pathogen infectivity, host resistance, and vector behavior. Here, we tested whether host population size, density, or connectivity also declined across elevation, and whether these epidemiologically relevant factors explained the observed disease distribution. We found that while none of these factor means changed across elevation, disease was significantly more likely to occur at both higher elevations and in larger populations, the majority of which were found above 1300 m. The break in disease incidence was also associated with an apparent scarcity of these larger host populations between 1000 and 1300 m in elevation. Examining variation in climatic factors among host populations, we also showed that the probability of disease was higher in areas with historically colder, wetter, and more stable conditions. The restricted distribution of anther‐smut disease in high‐elevation S. vulgaris provides an opportunity for empirical study on range limits and disease distribution in natural alpine communities that are considered particularly sensitive to the effects of climate change.

Effect of host and inoculum patterns on take-all disease of wheat incidence, severity and disease gradient

The importance of the spatial aspect of epidemics has been recognized from the outset of plant disease epidemiology. The objective of this study was to determine if the host spatial structure influenced the spatio-temporal development of take-all disease of wheat, depending on the inoculum spatial structure. Three sowing patterns of wheat (broadcast sowing, line sowing and sowing in hills) and three patterns of inoculum (uniform, aggregated and natural infestation) were tested in a field experiment, repeated over 2 years. Disease (severity, root disease incidence, plant disease incidence and, when applicable, line and hill incidences) was assessed seven times during the course of each season and the spatial pattern was characterized with incidence-incidence relationships. In the naturally infested plots, disease levels at all measurement scales were significantly higher in plots sown in hills, compared to plots sown in line, which were in turn significantly more diseased than plots with broadcast sowing. Disease aggregation within roots and plants was stronger in line and hill sowing than in broadcast sowing. Analysis of the disease gradient in the artificially infested plots showed that the disease intensified (local increase of disease level) more than it extensified (spatial spread of the disease), the effect of the introduced inoculum was reduced by 95% at a distance of 15 cm away from the point of infestation. Yield was not significantly affected by sowing pattern or artificial infestation.

Disease Spread Across Multiple Scales in a Spatial Hierarchy: Effect of Host Spatial Structure and of Inoculum Quantity and Distribution

Spatial patterns of both the host and the disease influence disease spread and crop losses. Therefore, the manipulation of these patterns might help improve control strategies. Considering disease spread across multiple scales in a spatial hierarchy allows one to capture important features of epidemics developing in space without using explicitly spatialized variables. Thus, if the system under study is composed of roots, plants, and planting hills, the effect of host spatial pattern can be studied by varying the number of plants per planting hill. A simulation model based on hierarchy theory was used to simulate the effects of large versus small planting hills, low versus high level of initial infections, and aggregated versus uniform distribution of initial infections. The results showed that aggregating the initially infected plants always resulted in slower epidemics than spreading out the initial infections uniformly. Simulation results also showed that, in most cases, disease epidemics were slower in the case of large host aggregates (100 plants/hill) than with smaller aggregates (25 plants/hill), except when the initially infected plants were both numerous and spread out uniformly. The optimal strategy for disease control depends on several factors, including initial conditions. More importantly, the model offers a framework to account for the interplay between the spatial characteristics of the system, rates of infection, and aggregation of the disease.

Transmission of the microsporidian Glugoides intestinalis in relation to spatial structure of the host Daphnia magna

Daphnia magna selects different depths according to its genotype, its size or infection by a parasite. As a result, waterflea populations are often vertically structured. This vertical structure, i. e. different distances between waterfleas, might slow the progress of microparasite epidemics. This would enable avoidance behaviour to evolve. I tested in a set of experiments for both, distance effects and avoidance behaviour. The experiments were performed with the host-parasite system of D. magna and its microsporidian gut-parasite Glugoides intestinalis. Infection depended on spore loads in infected waterfleas. Transmission, however, was not affected by distance to infected animals. Avoidance behaviour was absent. The results suggest that the host's spatial structure does not influence the transmission of G. intestinalis in the populations of Daphnia magna living in shallow water. Rather, successful transmission depends on the dynamics of the water.

Avoid, attack or do both? Behavioral and physiological adaptations in natural enemies faced with novel hosts

BackgroundConfronted with well-defended, novel hosts, should an enemy invest in avoidance of these hosts (behavioral adaptation), neutralization of the defensive innovation (physiological adaptation) or both? Although simultaneous investment in both adaptations may first appear to be redundant, several empirical studies have suggested a reinforcement of physiological resistance to host defenses with additional avoidance behaviors. To explain this paradox, we develop a mathematical model describing the joint evolution of behavioral and physiological adaptations on the part of natural enemies to their host defenses. Our specific goals are (i) to derive the conditions that may favor the simultaneous investment in avoidance and physiological resistance and (ii) to study the factors that govern the relative investment in each adaptation mode.ResultsOur results show that (i) a simultaneous investment may be optimal if the fitness costs of the adaptive traits are accelerating and the probability of encountering defended hosts is low. When (i) holds, we find that (ii) the more that defended hosts are rare and/or spatially aggregated, the more behavioral adaptation is favored.ConclusionDespite their interference, physiological resistance to host defensive innovations and avoidance of these same defenses are two strategies in which it may be optimal for an enemy to invest in simultaneously. The relative allocation to each strategy greatly depends on host spatial structure. We discuss the implications of our findings for the management of invasive plant species and the management of pest resistance to new crop protectants or varieties.

Extinction times for closed epidemics: the effects of host spatial structure

AbstractAlthough of practical importance, the relationship between the duration of an epidemic and host spatial structure is poorly understood. Here we use a stochastic metapopulation model for the transmission of infection in a spatially structured host population. There are three qualitatively different regimes for the extinction time, which depend on patch population size, the within‐patch basic reproductive number and the strength of coupling between patches. In the first regime, the extinction time for the metapopulation (i.e. from all patches) is approximately equal to the extinction time for a single patch. In the second regime, the metapopulation extinction time is maximal but also highly variable. In the third regime, the extinction time for the metapopulation (TE) is given by TE = a + bn1/2 where a is the local extinction time (i.e. from last patch), b is the transit time (i.e. the time taken for infection to spread from one patch to another) and n is the total number of patches.