Understanding the drivers of seasonal disease outbreaks remains a fundamental challenge in disease ecology. Periodic outbreaks can be driven by several seasonally varying factors, including pulses of susceptible individuals through births, changes in host behaviour and social aggregation and variation in host immunity. However, when these potential drivers overlap temporally, isolating their relative contributions to outbreak patterns becomes challenging. We studied Hendra virus, a zoonotic pathogen with seasonal spillovers from bats to horses and humans. Multiple seasonal factors have been hypothesized to drive Hendra virus transmission, including food shortages, birth pulses and changes in host aggregation, but their temporal overlap has made identifying primary drivers difficult. We conducted a 4-year longitudinal study of Pteropus bats to test whether seasonal birth pulses and the resulting influx of susceptible juveniles drive Hendra virus transmission. Using a Bayesian ageing model, we aged sexually immature bats and placed them into birth cohorts. We used our age predictions to model how viral shedding and antibody responses changed as bats aged. We tracked Bartonella spp. Infection-a bacterial pathogen requiring close contact for transmission-as an indicator of transmission opportunities within each cohort for comparison. We found no evidence that seasonal birth pulses of immunologically naïve juveniles drove Hendra virus transmission. Two out of three cohorts showed substantially reduced maternal antibody transfer compared to the 2018 cohort, with seroprevalence near zero at our earliest sampling timepoints and showed no clear evidence of synchronized seroconversion. Furthermore, Bartonella infection rates were consistent across cohorts, indicating that opportunities for pathogen transmission remained consistent across cohorts despite varying viral shedding patterns. Our findings demonstrate that birth pulses alone cannot explain observed patterns of Hendra virus outbreaks. These results highlight the importance of using multiple lines of evidence to evaluate competing mechanisms underlying seasonal disease dynamics, particularly when potential drivers coincide temporally.

Understanding where and when pathogens occur in the environment has implications for reservoir population health and infection risk. In reservoir hosts, infection status and pathogen shedding are affected by processes interacting across different scales: from landscape features affecting host location and transmission to within‐host processes affecting host immunity and infectiousness. While uncommonly done, simultaneously incorporating processes across multiple scales may improve pathogen shedding predictions. In Australia, the black flying fox Pteropus alecto is a natural host for the zoonotic Hendra virus, which is hypothesized to cause latent infections in bats. Re‐activation and virus shedding may be triggered by poor host condition, leading to virus excretion through urine. Here, we developed a statistical modeling approach that combined data at multiple spatial and temporal scales to capture ecological and biological processes potentially affecting virus shedding. We parameterized these models using existing datasets and compared model performance to under‐roost virus shedding data from 2011–2014 in 23 roosts across a 1200‐km transect. Our approach enabled comparisons among multiple model structures to determine which variables at which scales are most influential for accurate predictions of virus shedding in space and time. We identified environmental predictors and temporal lags of these features that were important for determining where reservoirs are located and multiple independent proxies for reservoir condition. The best‐performing multiscale model delineated periods of low and high virus prevalence, reflecting observed shedding patterns from pooled under‐roost samples. Incorporating regional indicators of food scarcity enhanced model accuracy while incorporating other stress indicators at local scales confounded this signal. This multiscale modeling approach enabled the combination of processes from different ecological scales and identified environmental variables influencing Hendra virus shedding, highlighting how integrating data across scales may improve risk forecasts for other pathogen systems.

Ebola virus (EBOV) and Marburg virus (MARV) are zoonotic filoviruses that cause hemorrhagic fever in humans. Correlative data implicate bats as natural EBOV hosts, but neither a full-length genome nor an EBOV isolate has been found in any bats sampled. Here, we model filovirus infection in the Jamaican fruit bat (JFB), Artibeus jamaicensis, by inoculation with either EBOV or MARV through a combination of oral, intranasal, and subcutaneous routes. Infection with EBOV results in systemic virus replication and oral shedding of infectious virus. MARV replication is transient and does not shed. In vitro, JFB cells replicate EBOV more efficiently than MARV, and MARV infection induces innate antiviral responses that EBOV efficiently suppresses. Experiments using VSV pseudoparticles or replicating VSV expressing the EBOV or MARV glycoprotein demonstrate an advantage for EBOV entry and replication early, respectively, in JFB cells. Overall, this study describes filovirus species-specific phenotypes for both JFB and their cells.

Bats host a high diversity of coronaviruses, including betacoronaviruses that have caused outbreaks and pandemics in humans and other species. Here, we study the spatiotemporal dynamics of co-circulating coronaviruses in Pteropus spp bats (flying foxes) in eastern Australia over a three-year period across five roost sites (n = 2537 fecal samples). In total, we identify six betacoronavirus clades, all within the nobecovirus subgenus. Genome sequencing supports overall clade assignments, however, also demonstrates the important role recombination has played in both the long-term and contemporary evolution of these viruses. Using a statistical framework that integrates individual and population level data, we assess the variability in prevalence of viral clades over space and time. Coronavirus infections and co-infections are highest among juveniles and subadults, particularly around the time of weaning. The overlapping shedding dynamics across multiple clades suggest opportunities for recombination, especially in younger bats. Understanding the ecological and host-viral drivers of these seasonally dynamic infections, co-infections, and recombination events will inform future predictive frameworks for coronavirus emergence in humans and other animals.

Land-use change may drive viral spillover from bats into humans, partly through dietary shifts caused by decreased availability of native foods and increased availability of cultivated foods. We experimentally manipulated diets of Jamaican fruit bats to investigate whether diet influences viral shedding. To reflect dietary changes experienced by wild bats during periods of nutritional stress, Jamaican fruit bats were fed either a standard diet or a putative suboptimal diet, which was deprived of protein (suboptimal-sugar diet) and/or supplemented with fat (suboptimal-fat diet). Upon H18N11 influenza A-virus infection, bats fed on the suboptimal-sugar diet shed the most viral RNA for the longest period, but bats fed the suboptimal-fat diet shed the least viral RNA for the shortest period. Bats on both suboptimal diets ate more food than the standard diet, suggesting nutritional changes may alter foraging behaviour. This study serves as an initial step in understanding whether and how dietary shifts may influence viral dynamics in bats, which alters the risk of spillover to humans.

Since the COVID-19 pandemic, attention and investment in pandemic preparedness have increased. Although there are many valiant plans around pandemic preparedness, they typically involve slowing the spread or mitigating the effects of a pathogen after it has already entered the human population. The task of stopping the pathogen from entering the human population in the first place, spillover prevention, remains a neglected area in discussions and planning for pandemic risk mitigation. Every spillover offers an opportunity to learn about an emerging public health threat and the conditions that aligned to enable spillover occurrence. In this article, we outline One Health approaches for use in spillover investigations, drawing from our experience investigating Hendra and Nipah virus spillovers. We present a roadmap for how findings from those investigations can lead to the development of interventions for spillover and ultimately pandemic prevention.

We sequenced sarbecovirus from Rhinolophus spp. bats in Bandarban District, Bangladesh, in a genomic surveillance campaign during 2022-2023. Sequences shared identity with SARS-CoV-1 Tor2, which caused an outbreak of human illnesses in 2003. Describing the genetic diversity and zoonotic potential of reservoir pathogens can aid in identifying sources of future spillovers.

Changes in the quality and quantity of food consumed can affect the health of hosts, their ability to control infections and potentially shape the likelihood of pathogen spillover. Dietary shifts have been proposed as one of the factors driving spillovers of zoonotic viruses from bats to humans. In this study, we examined how diet composition alters the immune response to viral shedding and the risk of spillover by developing a mechanistic model fitted to experimental data of Jamaican fruit bats infected with influenza A virus H18N11 and fed different diets. The model selected from alternative immune and metabolic relationships showed that the coupled effects of citrulline and tumour necrosis factor alpha (TNF) affected the control of viral shedding with parameters that varied with diet. Bats on the suboptimal fat diet appeared to control shedding more successfully than bats on suboptimal sugar or optimal protein diets. Yet, bats on the optimal diet could potentially cause lower hazard of spillover because of reduced food consumption, suggesting fewer and/or shorter visits at the feeding sites and thus transmission to secondary hosts. This study provides a parsimonious explanation of the barriers that affect viral shedding by reservoir hosts and the consequences for the hazard of spillover.

We explored the role of black flying foxes (Pteropus alecto) in Australia as reservoirs of Borrelia bacteria. We found bats infected with 2 Borrelia haplotypes phylogenetically distinct from Lyme or relapsing fever clades. Efforts to sample black flying foxes and their ectoparasites are needed to evaluate zoonotic potential of those Borrelia lineages.

Understanding where and when pathogens occur in the environment has implications for reservoir population health and infection risk. In reservoir hosts, infection status and pathogen shedding are affected by processes interacting across different scales: from landscape features affecting host location and transmission to within-host processes affecting host immunity and infectiousness. While uncommonly done, simultaneously incorporating processes across multiple scales may improve pathogen shedding predictions. In Australia, the black flying fox (Pteropus alecto) is a natural host for the zoonotic Hendra virus, which is hypothesized to cause latent infections in bats. Re-activation and virus shedding may be triggered by poor host condition, leading to virus excretion through urine. Here, we developed a statistical modeling approach that combined data at multiple spatial and temporal scales to capture ecological and biological processes potentially affecting virus shedding. We parameterized these models using existing datasets and compared model performance to under-roost virus shedding data from 2011-2014 in 23 roosts across a 1200-km transect. Our approach enabled comparisons among multiple model structures to determine which variables at which scales are most influential for accurate predictions of virus shedding in space and time. We identified environmental predictors and temporal lags of these features that were important for determining where reservoirs are located and multiple independent proxies for reservoir condition. The best-performing multi-scale model delineated periods of low and high virus prevalence, reflecting observed shedding patterns from pooled under-roost samples. Incorporating regional indicators of food scarcity enhanced model accuracy while incorporating other stress indicators at local scales confounded this signal. This multiscale modeling approach enabled the combination of processes from different ecological scales and identified environmental variables influencing Hendra virus shedding, highlighting how integrating data across scales may improve risk forecasts for other pathogen systems. ### Competing Interest Statement The authors have declared no competing interest.

We explore the role of Australian black flying foxes ( Pteropus alecto ) as reservoir hosts of potentially zoonotic Borrelia bacteria. Across six sites, 2% of 840 bats were infected with one of two novel Borrelia haplotypes. Phylogenetic reconstruction indicated these infections are distinct from Lyme or relapsing fever clades. ### Competing Interest Statement The authors have declared no competing interest.

ABSTRACT A novel Hendra virus (HeV) genotype (HeV genotype 2 [HeV-g2]) was recently isolated from a deceased horse, revealing high-sequence conservation and antigenic similarities with the prototypic strain, HeV-g1. As the receptor-binding (G) and fusion (F) glycoproteins of HeV are essential for mediating viral entry, functional characterization of emerging HeV genotypic variants is key to understanding viral entry mechanisms and broader virus-host co-evolution. We first confirmed that HeV-g2 and HeV-g1 glycoproteins share a close phylogenetic relationship, underscoring HeV-g2’s relevance to global health. Our in vitro data showed that HeV-g2 glycoproteins induced cell-cell fusion in human cells, shared receptor tropism with HeV-g1, and cross-reacted with antibodies raised against HeV-g1. Despite these similarities, HeV-g2 glycoproteins yielded reduced syncytia formation compared to HeV-g1. By expressing heterotypic combinations of HeV-g2, HeV-g1, and Nipah virus (NiV) glycoproteins, we found that while HeV-g2 G had strong fusion-promoting abilities, HeV-g2 F consistently displayed hypofusogenic properties. These fusion phenotypes were more closely associated with those observed in the related NiV. Further investigation using HeV-g1 and HeV-g2 glycoprotein chimeras revealed that multiple domains may play roles in modulating these fusion phenotypes. Altogether, our findings may establish intrinsic fusogenic capacities of viral glycoproteins as a potential driver behind the emergence of new henipaviral variants. IMPORTANCE HeV is a zoonotic pathogen that causes severe disease across various mammalian hosts, including horses and humans. The identification of unrecognized HeV variants, such as HeV-g2, highlights the need to investigate mechanisms that may drive their evolution, transmission, and pathogenicity. Our study reveals that HeV-g2 and HeV-g1 glycoproteins are highly conserved in identity, function, and receptor tropism, yet they differ in their abilities to induce the formation of multinucleated cells (syncytia), which is a potential marker of viral pathogenesis. By using heterotypic combinations of HeV-g2 with either HeV-g1 or NiV glycoproteins, as well as chimeric HeV-g1/HeV-g2 glycoproteins, we demonstrate that the differences in syncytial formation can be attributed to the intrinsic fusogenic capacities of each glycoprotein. Our data indicate that HeV-g2 glycoproteins have fusion phenotypes closely related to those of NiV and that fusion promotion may be a crucial factor driving the emergence of new henipaviral variants.

Bats are reservoirs of many zoonotic viruses that are fatal in humans but do not cause disease in bats. Moreover, bats generate low neutralizing antibody titers in response to experimental viral infection, although more robust antibody responses have been observed in wild-caught bats during times of food stress. Here, we compared the antibody titers and B cell receptor (BCR) diversity of Jamaican fruit bats (Artibeus jamaicensis; JFBs) and BALB/c mice generated in response to T-dependent and T-independent antigens. We then manipulated the diet of JFBs and challenged them with H18N11 influenza A-like virus or a replication incompetent Nipah virus VSV (Nipah-riVSV). Under standard housing conditions, JFBs generated a lower avidity antibody response and possessed more BCR mRNA diversity compared to BALB/c mice. However, withholding protein from JFBs improved serum neutralization in response to Nipah-riVSV and improved serum antibody titers specific to H18 but reduced BCR mRNA diversity.

Pathogen transmission studies require sample collection over extended periods, which can be challenging and costly, especially in the case of wildlife. A useful strategy can be to collect pooled samples, but this presents challenges when the goal is to estimate prevalence. This is because pooling can introduce a dilution effect where pathogen concentration is lowered by the inclusion of negative or lower-concentration samples, while at the same time a pooled sample can test positive even when some of the contributing samples are negative. If these biases are taken into account, the concentration of a pooled sample can be leveraged to infer the most likely proportion of positive individuals, and thus improve overall prevalence reconstruction, but few methods exist that account for the sample mixing process. We present a Bayesian multilevel model that estimates prevalence dynamics over time using pooled and individual samples in a wildlife setting. The model explicitly accounts for the complete mixing process that determines pooled sample concentration, thus enabling accurate prevalence estimation even from pooled samples only. As it is challenging to link individual-level metrics such as age, sex, or immune markers to infection status when using pooled samples, the model also allows the incorporation of individual-level samples. Crucially, when individual samples can test false negative, a potentially strong bias is introduced that results in incorrect estimates of regression coefficients. The model, however, can account for this by leveraging the combination of pooled and individual samples. Last, the model en- ables estimation of extrinsic environmental effects on prevalence dynamics. Using a simulated dataset inspired by virus transmission in flying foxes, we show that the model is able to accurately estimate prevalence dynamics, false negative rate, and covariate effects. We test model performance for a range of realistic sampling scenarios and find that while it is generally robust, there are a number of factors that should be considered in order to maximize performance. The model presents an important advance in the use of pooled samples for estimating prevalence dynamics in a wildlife setting, can be used with any biomarker of infection (Ct values, antibody levels, other infection biomarkers) and can be applied to a wide range of host-pathogen systems.

Flying birds and bats have simplified gastrointestinal tracts (GITs) and low intestinal mass to facilitate flight. Previous work showed reduced GIT transit times in birds relative to other vertebrates-but GIT transit has never been collectively quantified for bats. Unique among mammals, bat GIT microbiomes are dominated by Pseudomonadota bacteria (previously Proteobacteria), which also dominate the microbiomes of flying birds - we hypothesized this convergence to result from rapid GIT transit times for both volant taxa. We conducted a meta-analysis of vertebrate GIT transit times which showed that bats and flying birds have significantly faster transit times relative to nonvolant vertebrates. Additionally, within the bat order (Chiroptera), we demonstrated decreasing transit times associated with increasing body mass, a pattern contrasting other vertebrates (including volant birds) and possibly influencing GIT microbiome composition. This inverted mass-transit association is likely driven by diet as fruit- and nectar-consuming Pteropodids are the largest of all bats.

Substantial global attention is focused on how to reduce the risk of future pandemics. Reducing this risk requires investment in prevention, preparedness, and response. Although preparedness and response have received significant focus, prevention, especially the prevention of zoonotic spillover, remains largely absent from global conversations. This oversight is due in part to the lack of a clear definition of prevention and lack of guidance on how to achieve it. To address this gap, we elucidate the mechanisms linking environmental change and zoonotic spillover using spillover of viruses from bats as a case study. We identify ecological interventions that can disrupt these spillover mechanisms and propose policy frameworks for their implementation. Recognizing that pandemics originate in ecological systems, we advocate for integrating ecological approaches alongside biomedical approaches in a comprehensive and balanced pandemic prevention strategy.

Nipah virus spillovers via consumption of date palm sap in Bangladesh vary substantially between years and have been associated with lower winter temperatures and precipitation. However, the mechanisms driving the interannual variation and the influence of weather remain unexplained. Here we investigated the hypothesis that weather patterns change human sap consumption and explain interannual variation in observed spillovers. We analyzed responses from a nationally representative survey conducted in Bangladesh in 2013-2016 on household date palm sap consumption and weather data for each division of Bangladesh, using logistic regression to examine whether sap consumption is associated with weather variability. We found significant associations of lower minimum temperatures and precipitation with increased household sap consumption during the sap harvesting season. This relationship was largely similar within all months and divisions, and strong associations of temperature (χ2 (1, n = 5,027) = 7.74, p < 0.01) and, independently, precipitation (χ2 = 8.00, p < 0.01) remained strong after accounting for month, location, and annual sap season. Interannual variation in date palm sap consumption in Bangladesh is likely best explained by temperature and precipitation patterns, where colder, drier winter days pose a higher risk for Nipah virus spillover. The knowledge gained in this study may be valuable for targeting timing of future behavioral interventions against consumption of date palm sap in Bangladesh.

The health and economic impacts from infectious disease emergence are substantial. 1 Bernstein AS Ando AW Loch-Temzelides T et al. The costs and benefits of primary prevention of zoonotic pandemics. Sci Adv. 2022; 8eabl4183 Crossref Scopus (89) Google Scholar Pathogens that are transmitted, or spill over, between animals and people are the source of most emerging infectious diseases in humans. 2 Jones KE Patel NG Levy MA et al. Global trends in emerging infectious diseases. Nature. 2008; 451: 990-993 Crossref PubMed Scopus (5197) Google Scholar Indeed, spillovers sparked five viral pandemics from 1918 through to 2009 (1918 influenza, 1957–58 influenza, 1968 influenza, 2009 influenza, and HIV), and peer-reviewed evidence strongly suggests that COVID-19 was the result of spillovers too. 3 US Centers for Disease Control and PreventionPast pandemics. https://www.cdc.gov/flu/pandemic-resources/basics/past-pandemics.htmlDate accessed: August 7, 2023 Google Scholar , 4 Worobey M Han G-Z Rambaut A Genesis and pathogenesis of the 1918 pandemic H1N1 influenza A virus. Proc Natl Acad Sci USA. 2014; 111: 8107-8112 Crossref PubMed Scopus (170) Google Scholar , 5 Kawaoka Y Krauss S Webster RG Avian-to-human transmission of the PB1 gene of influenza A viruses in the 1957 and 1968 pandemics. J Virol. 1989; 63: 4603-4608 Crossref PubMed Scopus (0) Google Scholar , 6 Mena I Nelson MI Quezada-Monroy F et al. Origins of the 2009 H1N1 influenza pandemic in swine in Mexico. eLife. 2016; 5e16777 Crossref Scopus (201) Google Scholar , 7 Sharp PM Hahn BH Origins of HIV and the AIDS pandemic. Cold Spring Harb Perspect Med. 2011; 1a006841 Crossref PubMed Scopus (819) Google Scholar , 8 Pekar JE Magee A Parker E et al. The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2. Science. 2022; 377: 960-966 Crossref PubMed Scopus (93) Google Scholar , 9 Worobey M Levy JI Malpica Serrano L et al. The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic. Science. 2022; 377: 951-959 Crossref PubMed Scopus (149) Google Scholar Spillovers are a reminder that humans are inherently part of nature and that human wellbeing is intertwined with that of animals and the environment. As such, adopting a One Health approach when addressing viral pandemic threats is imperative. 10 Keusch GT Amuasi JH Anderson DE et al. Pandemic origins and a One Health approach to preparedness and prevention: solutions based on SARS-CoV-2 and other RNA viruses. Proc Natl Acad Sci USA. 2022; 119e2202871119 Crossref PubMed Scopus (38) Google Scholar

Ebola virus (EBOV) and Marburg virus (MARV) are zoonotic filoviruses that cause hemorrhagic fever in humans. Bat species in both Chiropteran suborders host filoviruses, suggesting that bats may have coevolved with this viral family. Correlative data implicate bats as natural EBOV hosts, but neither a full-length genome nor an EBOV isolate has been found in any bats sampled. Here, we modelled filovirus infection in the Jamaican fruit bat (JFB), Artibeus jamaicensis. Bats were inoculated with either EBOV or MARV through a combination of oral, intranasal, and subcutaneous routes. EBOV-infected bats supported systemic virus replication and shed infectious virus orally. In contrast, MARV replicated only transiently and was not shed. In vitro, JFB cells replicate EBOV more efficiently than MARV, and MARV infection induced innate antiviral responses that EBOV efficiently suppressed. Experiments using VSV pseudoparticles or replicating VSV expressing the EBOV or MARV glycoprotein demonstrated an advantage for EBOV entry and replication early, respectively, in JFB cells. Overall, this study describes filovirus species-specific phenotypes for both JFB and their cells. ### Competing Interest Statement The authors have declared no competing interest.