No abstract

Old World fruit bats (Chiroptera: Pteropodidae) provide critical pollination and seed dispersal services to forest ecosystems across Africa, Asia, and Australia. In each of these regions, pteropodids have been identified as natural reservoir hosts for henipaviruses. The genus Henipavirus includes Hendra virus and Nipah virus, which regularly spill over from bats to domestic animals and humans in Australia and Asia, and a suite of largely uncharacterized African henipaviruses. Rapid change in fruit bat habitat and associated shifts in their ecology and behavior are well documented, with evidence suggesting that altered diet, roosting habitat, and movement behaviors are increasing spillover risk of bat-borne viruses. We review the ways that changing resource landscapes affect the processes that culminate in cross-species transmission of henipaviruses, from reservoir host density and distribution to within-host immunity and recipient host exposure. We evaluate existing evidence and highlight gaps in knowledge that are limiting our understanding of the ecological drivers of henipavirus spillover. When considering spillover in the context of land-use change, we emphasize that it is especially important to disentangle the effects of habitat loss and resource provisioning on these processes, and to jointly consider changes in resource abundance, quality, and composition.

The prevalence and intensity of parasites in wild hosts varies across space and is a key determinant of infection risk in humans, domestic animals and threatened wildlife. Because the immune system serves as the primary barrier to infection, replication and transmission following exposure, we here consider the environmental drivers of immunity. Spatial variation in parasite pressure, abiotic and biotic conditions, and anthropogenic factors can all shape immunity across spatial scales. Identifying the most important spatial drivers of immunity could help pre‐empt infectious disease risks, especially in the context of how large‐scale factors such as urbanization affect defence by changing environmental conditions. We provide a synthesis of how to apply macroecological approaches to the study of ecoimmunology (i.e. macroimmunology). We first review spatial factors that could generate spatial variation in defence, highlighting the need for large‐scale studies that can differentiate competing environmental predictors of immunity and detailing contexts where this approach might be favoured over small‐scale experimental studies. We next conduct a systematic review of the literature to assess the frequency of spatial studies and to classify them according to taxa, immune measures, spatial replication and extent, and statistical methods. We review 210 ecoimmunology studies sampling multiple host populations. We show that whereas spatial approaches are relatively common, spatial replication is generally low and unlikely to provide sufficient environmental variation or power to differentiate competing spatial hypotheses. We also highlight statistical biases in macroimmunology, in that few studies characterize and account for spatial dependence statistically, potentially affecting inferences for the relationships between environmental conditions and immune defence. We use these findings to describe tools from geostatistics and spatial modelling that can improve inference about the associations between environmental and immunological variation. In particular, we emphasize exploratory tools that can guide spatial sampling and highlight the need for greater use of mixed‐effects models that account for spatial variability while also allowing researchers to account for both individual‐ and habitat‐level covariates. We finally discuss future research priorities for macroimmunology, including focusing on latitudinal gradients, range expansions and urbanization as being especially amenable to large‐scale spatial approaches. Methodologically, we highlight critical opportunities posed by assessing spatial variation in host tolerance, using metagenomics to quantify spatial variation in parasite pressure, coupling large‐scale field studies with small‐scale field experiments and longitudinal approaches, and applying statistical tools from macroecology and meta‐analysis to identify generalizable spatial patterns. Such work will facilitate scaling ecoimmunology from individual‐ to habitat‐level insights about the drivers of immu...

Abstract. Understanding how landscape, host, and pathogen traits contribute to disease exposure requires systematic evaluations of pathogens within and among host species and geographic regions. The relative importance of these attributes is critical for management of wildlife and mitigating domestic animal and human disease, particularly given rapid ecological changes, such as urbanization. We screened >1000 samples from sympatric populations of puma (Puma concolor), bobcat (Lynx rufus), and domestic cat (Felis catus) across urban gradients in six sites, representing three regions, in North America for exposure to a representative suite of bacterial, protozoal, and viral pathogens (Bartonella sp., Toxoplasma gondii, feline herpesvirus-1, feline panleukopenea virus, feline calicivirus, and feline immunodeficiency virus). We evaluated prevalence within each species, and examined host trait and land cover determinants of exposure; providing an unprecedented analysis of factors relating to potential for infections in domesticated and wild felids. Prevalence differed among host species (highest for puma and lowest for domestic cat) and was greater for indirectly transmitted pathogens. Sex was inconsistently predictive of exposure to directly transmitted pathogens only, and age infrequently predictive of both direct and indirectly transmitted pathogens. Determinants of pathogen exposure were widely divergent between the wild felid species. For puma, suburban land use predicted increased exposure to Bartonella sp. in southern California, and FHV-1 exposure increased near urban edges in Florida. This may suggest interspecific transmission with domestic cats via flea vectors (California) and direct contact (Florida) around urban boundaries. Bobcats captured near urban areas had increased exposure to T. gondii in Florida, suggesting an urban source of prey. Bobcats captured near urban areas in Colorado and Florida had higher FIV exposure, possibly suggesting increased intraspecific interactions through pile-up of home ranges. Beyond these regional and pathogen specific relationships, proximity to the wildland-urban interface did not generally increase the probability of disease exposure in wild or domestic felids, emphasizing the importance of local ecological determinants. Indeed, pathogen exposure was often negatively associated with the wildland-urban interface for all felids. Our analyses suggest cross-species pathogen transmission events around this interface may be infrequent, but followed by self-sustaining propagation within the new host species.

One contribution of 20 to a theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'. Subject Areas: health and disease and epidemiologyDose is the nexus between exposure and all upstream processes that determine pathogen pressure, and is thereby an important element underlying disease dynamics. Understanding the relationship between dose and disease is particularly important in the context of spillover, where nonlinearities in the dose -response could determine the likelihood of transmission. There is a need to explore dose -response models for directly transmitted and zoonotic pathogens, and how these interactions integrate within-host factors to consider, for example, heterogeneity in host susceptibility and dosedependent antagonism. Here, we review the dose -response literature and discuss the unique role dose -response models have to play in understanding and predicting spillover events. We present a re-analysis of doseresponse experiments for two important zoonotic pathogens (Middle East respiratory syndrome coronavirus and Nipah virus), to exemplify potential difficulties in differentiating between appropriate models with small exposure experiment datasets. We also discuss the data requirements needed for robust selection between dose -response models. We then suggest how these processes could be modelled to gain more realistic predictions of zoonotic transmission outcomes and highlight the exciting opportunities that could arise with increased collaboration between the virology and epidemiology disciplines.This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.