Pathogen spillover driven by rapid changes in bat ecology.

During recent decades, pathogens that originated in bats have become an increasing public health concern. A major challenge is to identify how those pathogens spill over into human populations to generate a pandemic threat1. Many correlational studies associate spillover with changes in land use or other anthropogenic stressors2,3, although the mechanisms underlying the observed correlations have not been identified4. One limitation is the lack of spatially and temporally explicit data on multiple spillovers, and on the connections among spillovers, reservoir host ecology and behaviour and viral dynamics. We present 25 years of data on land-use change, bat behaviour and spillover of Hendra virus from Pteropodid bats to horses in subtropical Australia. These data show that bats are responding to environmental change by persistently adopting behaviours that were previously transient responses to nutritional stress. Interactions between land-use change and climate now lead to persistent bat residency in agricultural areas, where periodic food shortages drive clusters of spillovers. Pulses of winter flowering of trees in remnant forests appeared to prevent spillover. We developed integrative Bayesian network models based on these phenomena that accurately predicted the presence or absence of clusters of spillovers in each of the 25 years. Our long-term study identifies the mechanistic connections between habitat loss, climate and increased spillover risk. It provides a framework for examining causes of bat virus spillover and for developing ecological countermeasures to prevent pandemics.

Ecological conditions predict the intensity of Hendra virus excretion over space and time from bat reservoir hosts.

The ecological conditions experienced by wildlife reservoirs affect infection dynamics and thus the distribution of pathogen excreted into the environment. This spatial and temporal distribution of shed pathogen has been hypothesised to shape risks of zoonotic spillover. However, few systems have data on both long-term ecological conditions and pathogen excretion to advance mechanistic understanding and test environmental drivers of spillover risk. We here analyse three years of Hendra virus data from nine Australian flying fox roosts with covariates derived from long-term studies of bat ecology. We show that the magnitude of winter pulses of viral excretion, previously considered idiosyncratic, are most pronounced after recent food shortages and in bat populations displaced to novel habitats. We further show that cumulative pathogen excretion over time is shaped by bat ecology and positively predicts spillover frequency. Our work emphasises the role of reservoir host ecology in shaping pathogen excretion and provides a new approach to estimate spillover risk.

Comparative Aerosol and Surface Stability of SARS-CoV-2 Variants of Concern.

SARS-CoV-2 transmits principally by air; contact and fomite transmission may also occur. Variants of concern are more transmissible than ancestral SARS-CoV-2. We found indications of possible increased aerosol and surface stability for early variants of concern, but not for the Delta and Omicron variants. Stability changes are unlikely to explain increased transmissibility.

Bartonella Infection in Fruit Bats and Bat Flies, Bangladesh.

Bats harbor diverse intracellular Bartonella bacteria, but there is limited understanding of the factors that influence transmission over time. Investigation of Bartonella dynamics in bats could reveal general factors that control transmission of multiple bat-borne pathogens, including viruses. We used molecular methods to detect Bartonella DNA in paired bat (Pteropus medius) blood and bat flies in the family Nycteribiidae collected from a roost in Faridpur, Bangladesh between September 2020 and January 2021. We detected high prevalence of Bartonella DNA in bat blood (35/55, 64%) and bat flies (59/60, 98%), with sequences grouping into three phylogenetic clades. Prevalence in bat blood increased over the study period (33% to 90%), reflecting an influx of juvenile bats in the population and an increase in the prevalence of bat flies. Discordance between infection status and the clade/genotype of detected Bartonella was also observed in pairs of bats and their flies, providing evidence that bat flies take blood meals from multiple bat hosts. This evidence of bat fly transfer between hosts and the changes in Bartonella prevalence during a period of increasing nycteribiid density support the role of bat flies as vectors of bartonellae. The study provides novel information on comparative prevalence and genetic diversity of Bartonella in pteropodid bats and their ectoparasites, as well as demographic factors that affect Bartonella transmission and potentially other bat-borne pathogens.

Novel Hendra Virus Variant Circulating in Black Flying Foxes and Grey-Headed Flying Foxes, Australia.

A novel Hendra virus variant, genotype 2, was recently discovered in a horse that died after acute illness and in Pteropus flying fox tissues in Australia. We detected the variant in flying fox urine, the pathway relevant for spillover, supporting an expanded geographic range of Hendra virus risk to horses and humans.

Nipah Virus Detection at Bat Roosts after Spillover Events, Bangladesh, 2012-2019.

Knowledge of the dynamics and genetic diversity of Nipah virus circulating in bats and at the human-animal interface is limited by current sampling efforts, which produce few detections of viral RNA. We report a series of investigations at Pteropus medius bat roosts identified near the locations of human Nipah cases in Bangladesh during 2012-2019. Pooled bat urine was collected from 23 roosts; 7 roosts (30%) had >1 sample in which Nipah RNA was detected from the first visit. In subsequent visits to these 7 roosts, RNA was detected in bat urine up to 52 days after the presumed exposure of the human case-patient, although the probability of detection declined rapidly with time. These results suggest that rapidly deployed investigations of Nipah virus shedding from bat roosts near human cases could increase the success of viral sequencing compared with background surveillance and could enhance understanding of Nipah virus ecology and evolution.

Novel Hendra Virus Variant Detected by Sentinel Surveillance of Horses in Australia.

We identified and isolated a novel Hendra virus (HeV) variant not detected by routine testing from a horse in Queensland, Australia, that died from acute illness with signs consistent with HeV infection. Using whole-genome sequencing and phylogenetic analysis, we determined the variant had ≈83% nt identity with prototypic HeV. In silico and in vitro comparisons of the receptor-binding protein with prototypic HeV support that the human monoclonal antibody m102.4 used for postexposure prophylaxis and current equine vaccine will be effective against this variant. An updated quantitative PCR developed for routine surveillance resulted in subsequent case detection. Genetic sequence consistency with virus detected in grey-headed flying foxes suggests the variant circulates at least among this species. Studies are needed to determine infection kinetics, pathogenicity, reservoir-species associations, viral-host coevolution, and spillover dynamics for this virus. Surveillance and biosecurity practices should be updated to acknowledge HeV spillover risk across all regions frequented by flying foxes.

Possibility for reverse zoonotic transmission of SARS-CoV-2 to free-ranging wildlife: A case study of bats.

The COVID-19 pandemic highlights the substantial public health, economic, and societal consequences of virus spillover from a wildlife reservoir. Widespread human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) also presents a new set of challenges when considering viral spillover from people to naïve wildlife and other animal populations. The establishment of new wildlife reservoirs for SARS-CoV-2 would further complicate public health control measures and could lead to wildlife health and conservation impacts. Given the likely bat origin of SARS-CoV-2 and related beta-coronaviruses (ß-CoVs), free-ranging bats are a key group of concern for spillover from humans back to wildlife. Here, we review the diversity and natural host range of ß-CoVs in bats and examine the risk of humans inadvertently infecting free-ranging bats with SARS-CoV-2. Our review of the global distribution and host range of ß-CoV evolutionary lineages suggests that 40+ species of temperate-zone North American bats could be immunologically naïve and susceptible to infection by SARS-CoV-2. We highlight an urgent need to proactively connect the wellbeing of human and wildlife health during the current pandemic and to implement new tools to continue wildlife research while avoiding potentially severe health and conservation impacts of SARS-CoV-2 "spilling back" into free-ranging bat populations.

Counterintuitive scaling between population abundance and local density: Implications for modelling transmission of infectious diseases in bat populations.

Models of host-pathogen interactions help to explain infection dynamics in wildlife populations and to predict and mitigate the risk of zoonotic spillover. Insights from models inherently depend on the way contacts between hosts are modelled, and crucially, how transmission scales with animal density. Bats are important reservoirs of zoonotic disease and are among the most gregarious of all mammals. Their population structures can be highly heterogeneous, underpinned by ecological processes across different scales, complicating assumptions regarding the nature of contacts and transmission. Although models commonly parameterise transmission using metrics of total abundance, whether this is an ecologically representative approximation of host-pathogen interactions is not routinely evaluated. We collected a 13-month dataset of tree-roosting Pteropus spp. from 2,522 spatially referenced trees across eight roosts to empirically evaluate the relationship between total roost abundance and tree-level measures of abundance and density-the scale most likely to be relevant for virus transmission. We also evaluate whether roost features at different scales (roost level, subplot level, tree level) are predictive of these local density dynamics. Roost-level features were not representative of tree-level abundance (bats per tree) or tree-level density (bats per m2 or m3 ), with roost-level models explaining minimal variation in tree-level measures. Total roost abundance itself was either not a significant predictor (tree-level 3D density) or only weakly predictive (tree-level abundance). This indicates that basic measures, such as total abundance of bats in a roost, may not provide adequate approximations for population dynamics at scales relevant for transmission, and that alternative measures are needed to compare transmission potential between roosts. From the best candidate models, the strongest predictor of local population structure was tree density within roosts, where roosts with low tree density had a higher abundance but lower density of bats (more spacing between bats) per tree. Together, these data highlight unpredictable and counterintuitive relationships between total abundance and local density. More nuanced modelling of transmission, spread and spillover from bats likely requires alternative approaches to integrating contact structure in host-pathogen models, rather than simply modifying the transmission function.

Spatial dynamics of pathogen transmission in communally roosting species: Impacts of changing habitats on bat-virus dynamics.

The spatial organization of populations determines their pathogen dynamics. This is particularly important for communally roosting species, whose aggregations are often driven by the spatial structure of their environment. We develop a spatially explicit model for virus transmission within roosts of Australian tree-dwelling bats (Pteropus spp.), parameterized to reflect Hendra virus. The spatial structure of roosts mirrors three study sites, and viral transmission between groups of bats in trees was modelled as a function of distance between roost trees. Using three levels of tree density to reflect anthropogenic changes in bat habitats, we investigate the potential effects of recent ecological shifts in Australia on the dynamics of zoonotic viruses in reservoir hosts. We show that simulated infection dynamics in spatially structured roosts differ from that of mean-field models for equivalently sized populations, highlighting the importance of spatial structure in disease models of gregarious taxa. Under contrasting scenarios of flying-fox roosting structures, sparse stand structures (with fewer trees but more bats per tree) generate higher probabilities of successful outbreaks, larger and faster epidemics, and shorter virus extinction times, compared to intermediate and dense stand structures with more trees but fewer bats per tree. These observations are consistent with the greater force of infection generated by structured populations with less numerous but larger infected groups, and may flag an increased risk of pathogen spillover from these increasingly abundant roost types. Outputs from our models contribute insights into the spread of viruses in structured animal populations, like communally roosting species, as well as specific insights into Hendra virus infection dynamics and spillover risk in a situation of changing host ecology. These insights will be relevant for modelling other zoonotic viruses in wildlife reservoir hosts in response to habitat modification and changing populations, including coronaviruses like SARS-CoV-2.

Ecological countermeasures for preventing zoonotic disease outbreaks: when ecological restoration is a human health imperative.

Ecological restoration should be regarded as a public health service. Unfortunately, the lack of quantitative linkages between environmental and human health has limited recognition of this principle. The advent of the COVID-19 pandemic provides the impetus for further discussion. We propose ecological countermeasures as highly targeted, landscape-based interventions to arrest the drivers of land use-induced zoonotic spillover. We provide examples of ecological restoration activities that reduce zoonotic disease risk and a five-point action plan at the human-ecosystem health nexus. In conclusion, we make the case that ecological countermeasures are a tenet of restoration ecology with human health goals.

Ecological and evolutionary drivers of haemoplasma infection and bacterial genotype sharing in a Neotropical bat community.

Most emerging pathogens can infect multiple species, underlining the importance of understanding the ecological and evolutionary factors that allow some hosts to harbour greater infection prevalence and share pathogens with other species. However, our understanding of pathogen jumps is based primarily around viruses, despite bacteria accounting for the greatest proportion of zoonoses. Because bacterial pathogens in bats (order Chiroptera) can have conservation and human health consequences, studies that examine the ecological and evolutionary drivers of bacterial prevalence and barriers to pathogen sharing are crucially needed. Here were studied haemotropic Mycoplasma spp. (i.e., haemoplasmas) across a species-rich bat community in Belize over two years. Across 469 bats spanning 33 species, half of individuals and two-thirds of species were haemoplasma positive. Infection prevalence was higher for males and for species with larger body mass and colony sizes. Haemoplasmas displayed high genetic diversity (21 novel genotypes) and strong host specificity. Evolutionary patterns supported codivergence of bats and bacterial genotypes alongside phylogenetically constrained host shifts. Bat species centrality to the network of shared haemoplasma genotypes was phylogenetically clustered and unrelated to prevalence, further suggesting rare-but detectable-bacterial sharing between species. Our study highlights the importance of using fine phylogenetic scales when assessing host specificity and suggests phylogenetic similarity may play a key role in host shifts not only for viruses but also for bacteria. Such work more broadly contributes to increasing efforts to understand cross-species transmission and the epidemiological consequences of bacterial pathogens.

Macroimmunology: The drivers and consequences of spatial patterns in wildlife immune defence.

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 immune defence and help predict where environmental change may most alter infectious disease risk.

Temporal and spatial limitations in global surveillance for bat filoviruses and henipaviruses.

Sampling reservoir hosts over time and space is critical to detect epizootics, predict spillover and design interventions. However, because sampling is logistically difficult and expensive, researchers rarely perform spatio-temporal sampling of many reservoir hosts. Bats are reservoirs of many virulent zoonotic pathogens such as filoviruses and henipaviruses, yet the highly mobile nature of these animals has limited optimal sampling of bat populations. To quantify the frequency of temporal sampling and to characterize the geographical scope of bat virus research, we here collated data on filovirus and henipavirus prevalence and seroprevalence in wild bats. We used a phylogenetically controlled meta-analysis to next assess temporal and spatial variation in bat virus detection estimates. Our analysis shows that only one in four bat virus studies report data longitudinally, that sampling efforts cluster geographically (e.g. filovirus data are available across much of Africa and Asia but are absent from Latin America and Oceania), and that sampling designs and reporting practices may affect some viral detection estimates (e.g. filovirus seroprevalence). Within the limited number of longitudinal bat virus studies, we observed high heterogeneity in viral detection estimates that in turn reflected both spatial and temporal variation. This suggests that spatio-temporal sampling designs are important to understand how zoonotic viruses are maintained and spread within and across wild bat populations, which in turn could help predict and preempt risks of zoonotic viral spillover.

Bats are not squirrels: Revisiting the cost of cooling in hibernating mammals.

Many species use stored energy to hibernate through periods of resource limitation. Hibernation, a physiological state characterized by depressed metabolism and body temperature, is critical to winter survival and reproduction, and therefore has been extensively quantified and modeled. Hibernation consists of alternating phases of extended periods of torpor (low body temperature, low metabolic rate), and energetically costly periodic arousals to normal body temperature. Arousals consist of multiple phases: warming, euthermia, and cooling. Warming and euthermic costs are regularly included in energetic models, but although cooling to torpid body temperature is an important phase of the torpor-arousal cycle, it is often overlooked in energetic models. When included, cooling cost is assumed to be 67% of warming cost, an assumption originally derived from a single study that measured cooling cost in ground squirrels. Since this study, the same proportional value has been assumed across a variety of hibernating species. However, no additional values have been derived. We derived a model of cooling cost from first principles and validated the model with empirical energetic measurements. We compared the assumed 67% proportional cooling cost with our model-predicted cooling cost for 53 hibernating mammals. Our results indicate that using 67% of warming cost only adequately represents cooling cost in ground squirrel-sized mammals. In smaller species, this value overestimates cooling cost and in larger species, the value underestimates cooling cost. Our model allows for the generalization of energetic costs for multiple species using species-specific physiological and morphometric parameters, and for predictions over variable environmental conditions.

Pathogen spillover during land conversion.

Pathogen spillover from wildlife to domestic animals and humans, and the reverse, has caused significant epidemics and pandemics worldwide. Although pathogen emergence has been linked to anthropogenic land conversion, a general framework to disentangle underlying processes is lacking. We develop a multi-host model for pathogen transmission between species inhabiting intact and converted habitat. Interspecies contacts and host populations vary with the proportion of land converted; enabling us to quantify infection risk across a changing landscape. In a range of scenarios, the highest spillover risk occurs at intermediate levels of habitat loss, whereas the largest, but rarest, epidemics occur at extremes of land conversion. This framework provides insights into the mechanisms driving disease emergence and spillover during land conversion. The finding that the risk of spillover is highest at intermediate levels of habitat loss provides important guidance for conservation and public health policy.

Age-specific infectious period shapes dynamics of pneumonia in bighorn sheep.

Superspreading, the phenomenon where a small proportion of individuals contribute disproportionately to new infections, has profound effects on disease dynamics. Superspreading can arise through variation in contacts, infectiousness or infectious periods. The latter has received little attention, yet it drives the dynamics of many diseases of critical public health, livestock health and conservation concern. Here, we present rare evidence of variation in infectious periods underlying a superspreading phenomenon in a free-ranging wildlife system. We detected persistent infections of Mycoplasma ovipneumoniae, the primary causative agent of pneumonia in bighorn sheep (Ovis canadensis), in a small number of older individuals that were homozygous at an immunologically relevant genetic locus. Interactions among age-structure, genetic composition and infectious periods may drive feedbacks in disease dynamics that determine the magnitude of population response to infection. Accordingly, variation in initial conditions may explain divergent population responses to infection that range from recovery to catastrophic decline and extirpation.

Contact and contagion: Probability of transmission given contact varies with demographic state in bighorn sheep.

Understanding both contact and probability of transmission given contact are key to managing wildlife disease. However, wildlife disease research tends to focus on contact heterogeneity, in part because the probability of transmission given contact is notoriously difficult to measure. Here, we present a first step towards empirically investigating the probability of transmission given contact in free-ranging wildlife. We used measured contact networks to test whether bighorn sheep demographic states vary systematically in infectiousness or susceptibility to Mycoplasma ovipneumoniae, an agent responsible for bighorn sheep pneumonia. We built covariates using contact network metrics, demographic information and infection status, and used logistic regression to relate those covariates to lamb survival. The covariate set contained degree, a classic network metric describing node centrality, but also included covariates breaking the network metrics into subsets that differentiated between contacts with yearlings, ewes with lambs, and ewes without lambs, and animals with and without active infections. Yearlings, ewes with lambs, and ewes without lambs showed similar group membership patterns, but direct interactions involving touch occurred at a rate two orders of magnitude higher between lambs and reproductive ewes than between any classes of adults or yearlings, and one order of magnitude higher than direct interactions between multiple lambs. Although yearlings and non-reproductive bighorn ewes regularly carried M. ovipneumoniae, our models suggest that a contact with an infected reproductive ewe had approximately five times the odds of producing a lamb mortality event of an identical contact with an infected dry ewe or yearling. Consequently, management actions targeting infected animals might lead to unnecessary removal of young animals that carry pathogens but rarely transmit. This analysis demonstrates a simple logistic regression approach for testing a priori hypotheses about variation in the odds of transmission given contact for free-ranging hosts, and may be broadly applicable for investigations in wildlife disease ecology.