Climate change increases cross-species viral transmission risk.

At least 10,000 virus species have the ability to infect humans but, at present, the vast majority are circulating silently in wild mammals1,2. However, changes in climate and land use will lead to opportunities for viral sharing among previously geographically isolated species of wildlife3,4. In some cases, this will facilitate zoonotic spillover-a mechanistic link between global environmental change and disease emergence. Here we simulate potential hotspots of future viral sharing, using a phylogeographical model of the mammal-virus network, and projections of geographical range shifts for 3,139 mammal species under climate-change and land-use scenarios for the year 2070. We predict that species will aggregate in new combinations at high elevations, in biodiversity hotspots, and in areas of high human population density in Asia and Africa, causing the cross-species transmission of their associated viruses an estimated 4,000 times. Owing to their unique dispersal ability, bats account for the majority of novel viral sharing and are likely to share viruses along evolutionary pathways that will facilitate future emergence in humans. Notably, we find that this ecological transition may already be underway, and holding warming under 2 °C within the twenty-first century will not reduce future viral sharing. Our findings highlight an urgent need to pair viral surveillance and discovery efforts with biodiversity surveys tracking the range shifts of species, especially in tropical regions that contain the most zoonoses and are experiencing rapid warming.

Global patterns and correlates in the emergence of antimicrobial resistance in humans.

Antimicrobial resistance (AMR) is a critical global health threat, and drivers of the emergence of novel strains of antibiotic-resistant bacteria in humans are poorly understood at the global scale. We examined correlates of AMR emergence in humans using global data on the origins of novel strains of AMR bacteria from 2006 to 2017, human and livestock antibiotic use, country economic activity and reporting bias indicators. We found that AMR emergence is positively correlated with antibiotic consumption in humans. However, the relationship between AMR emergence and antibiotic consumption in livestock is modified by gross domestic product (GDP), with only higher GDP countries showing a slight positive association, a finding that differs from previous studies on the drivers of AMR prevalence. We also found that human travel may play a role in AMR emergence, likely driving the spread of novel AMR strains into countries where they are subsequently detected for the first time. Finally, we used our model to generate a country-level map of the global distribution of predicted AMR emergence risk, and compared these findings against reported AMR emergence to identify gaps in surveillance that can be used to direct prevention and intervention policies.

Host and viral traits predict zoonotic spillover from mammals.

The majority of human emerging infectious diseases are zoonotic, with viruses that originate in wild mammals of particular concern (for example, HIV, Ebola and SARS). Understanding patterns of viral diversity in wildlife and determinants of successful cross-species transmission, or spillover, are therefore key goals for pandemic surveillance programs. However, few analytical tools exist to identify which host species are likely to harbour the next human virus, or which viruses can cross species boundaries. Here we conduct a comprehensive analysis of mammalian host-virus relationships and show that both the total number of viruses that infect a given species and the proportion likely to be zoonotic are predictable. After controlling for research effort, the proportion of zoonotic viruses per species is predicted by phylogenetic relatedness to humans, host taxonomy and human population within a species range-which may reflect human-wildlife contact. We demonstrate that bats harbour a significantly higher proportion of zoonotic viruses than all other mammalian orders. We also identify the taxa and geographic regions with the largest estimated number of 'missing viruses' and 'missing zoonoses' and therefore of highest value for future surveillance. We then show that phylogenetic host breadth and other viral traits are significant predictors of zoonotic potential, providing a novel framework to assess if a newly discovered mammalian virus could infect people.

Erratum: Host and viral traits predict zoonotic spillover from mammals.

This corrects the article DOI: 10.1038/nature22975.

Nipah virus dynamics in bats and implications for spillover to humans.

Nipah virus (NiV) is an emerging bat-borne zoonotic virus that causes near-annual outbreaks of fatal encephalitis in South Asia-one of the most populous regions on Earth. In Bangladesh, infection occurs when people drink date-palm sap contaminated with bat excreta. Outbreaks are sporadic, and the influence of viral dynamics in bats on their temporal and spatial distribution is poorly understood. We analyzed data on host ecology, molecular epidemiology, serological dynamics, and viral genetics to characterize spatiotemporal patterns of NiV dynamics in its wildlife reservoir, Pteropus medius bats, in Bangladesh. We found that NiV transmission occurred throughout the country and throughout the year. Model results indicated that local transmission dynamics were modulated by density-dependent transmission, acquired immunity that is lost over time, and recrudescence. Increased transmission followed multiyear periods of declining seroprevalence due to bat-population turnover and individual loss of humoral immunity. Individual bats had smaller host ranges than other Pteropus species (spp.), although movement data and the discovery of a Malaysia-clade NiV strain in eastern Bangladesh suggest connectivity with bats east of Bangladesh. These data suggest that discrete multiannual local epizootics in bat populations contribute to the sporadic nature of NiV outbreaks in South Asia. At the same time, the broad spatial and temporal extent of NiV transmission, including the recent outbreak in Kerala, India, highlights the continued risk of spillover to humans wherever they may interact with pteropid bats and the importance of limiting opportunities for spillover throughout Pteropus's range.

Promise and Pitfalls of Endemic Resistance for Cultural Resources Threatened by Phytophthora ramorum.

Invasive forest pathogens can harm cultural, economic, and ecological resources. Here, we demonstrate the potential of endemic tree pathogen resistance in forest disease management using Phytophthora ramorum, cause of sudden oak death, in the context of management of tanoak (Notholithocarpus densiflorus), an ecologically unique and highly valued tree within Native American communities of northern California and southern Oregon in the United States. We surveyed resistance to P. ramorum on the Hoopa Valley Indian Reservation and Yurok Indian Reservation in a set of study sites with variable management intensities. Variation in resistance was found at all sites with similar mean and variation across stands, and resistance tended to have a random spatial distribution within stands but was not associated with previous stand management (thinning or prescribed fire) or structural characteristics such as tree density, basal area, or pairwise relatedness among study trees. These results did not suggest host, genetic, management, or environment interactions that could be easily leveraged into treatments to increase the prevalence of resistant trees. We applied epidemiological models to assess the potential application of endemic resistance in this system and to examine our assumption that in planta differences in lesion size-our measure of resistance-reflect linkages between mortality and transmission (resistance) versus reduced mortality with no change in transmission (tolerance). This assumption strongly influenced infection dynamics but changes in host populations-our conservation focus-was dependent on community-level variation in transmission. For P. ramorum, slowing mortality rates (whether by resistance or tolerance) conserves host resources when a second source of inoculum is present; these results are likely generalizable to pathogens with a broader host range. However, when the focal host is the sole source of inoculum, increasing tolerant individuals led to the greatest stand-level pathogen accumulation in our model. When seeking to use variation in mortality rates to affect conservation strategies, it is important to understand how these traits are linked with transmission because tolerance will be more useful for management in mixed-host stands that are already invaded, compared with single-host stands with low or no pathogen presence, where resistance will have the greatest conservation benefits.

Viral maintenance and excretion dynamics of coronaviruses within an Egyptian rousette fruit bat maternal colony: considerations for spillover.

Novel coronavirus species of public health and veterinary importance have emerged in the first two decades of the twenty-first century, with bats identified as natural hosts for progenitors of many coronaviruses. Targeted wildlife surveillance is needed to identify the factors involved in viral perpetuation within natural host populations, and drivers of interspecies transmission. We monitored a natural colony of Egyptian rousette bats at monthly intervals across two years to identify circulating coronaviruses, and to investigate shedding dynamics and viral maintenance within the colony. Three distinct lineages were detected, with different seasonal temporal excretion dynamics. For two lineages, the highest periods of coronavirus shedding were at the start of the year, when large numbers of bats were found in the colony. Highest peaks for a third lineage were observed towards the middle of the year. Among individual bat-level factors (age, sex, reproductive status, and forearm mass index), only reproductive status showed significant effects on excretion probability, with reproductive adults having lower rates of detection, though factors were highly interdependent. Analysis of recaptured bats suggests that viral clearance may occur within one month. These findings may be implemented in the development of risk reduction strategies for potential zoonotic coronavirus transmission.

Enhanced surveillance of monkeypox in Bas-Uélé, Democratic Republic of Congo: the limitations of symptom-based case definitions.

BACKGROUND: Following an outbreak of cases of vesicular-pustular rash with fever, evocative of human monkeypox, in Bas-Uélé province, Democratic Republic of Congo, surveillance was strengthened. METHODS: Households with at least one active generalized vesicular-pustular rash case were visited, and contact and clinical history information were collected from all household members. Whenever possible, skin lesions were screened by polymerase chain reaction for the monkeypox virus, followed by the varicella-zoster virus, when negative for the former. RESULTS: Polymerase chain reaction results were obtained for 77 suspected cases, distributed in 138 households, of which 27.3% were positive for monkeypox, 58.4% positive for chickenpox, and 14.3% negative for both. Confirmed monkeypox cases presented more often with monomorphic skin lesions on the palms of the hands and on the soles of the feet. Integrating these three features into the case definition raised the specificity to 85% but would miss 50% of true monkeypox cases. A predictive model fit on patient demographics and symptoms had 97% specificity and 80% sensitivity but only 80% and 33% in predicting out-of-sample cases. CONCLUSION: Few discriminating features were identified and the performance of clinical case definitions was suboptimal. Rapid field diagnostics are needed to optimize worldwide early detection and surveillance of monkeypox.

The future of zoonotic risk prediction.

In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges? This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

Predicting the global mammalian viral sharing network using phylogeography.

Understanding interspecific viral transmission is key to understanding viral ecology and evolution, disease spillover into humans, and the consequences of global change. Prior studies have uncovered macroecological drivers of viral sharing, but analyses have never attempted to predict viral sharing in a pan-mammalian context. Using a conservative modelling framework, we confirm that host phylogenetic similarity and geographic range overlap are strong, nonlinear predictors of viral sharing among species across the entire mammal class. Using these traits, we predict global viral sharing patterns of 4196 mammal species and show that our simulated network successfully predicts viral sharing and reservoir host status using internal validation and an external dataset. We predict high rates of mammalian viral sharing in the tropics, particularly among rodents and bats, and within- and between-order sharing differed geographically and taxonomically. Our results emphasize the importance of ecological and phylogenetic factors in shaping mammalian viral communities, and provide a robust, general model to predict viral host range and guide pathogen surveillance and conservation efforts.

United States wildlife and wildlife product imports from 2000-2014.

The global wildlife trade network is a massive system that has been shown to threaten biodiversity, introduce non-native species and pathogens, and cause chronic animal welfare concerns. Despite its scale and impact, comprehensive characterization of the global wildlife trade is hampered by data that are limited in their temporal or taxonomic scope and detail. To help fill this gap, we present data on 15 years of the importation of wildlife and their derived products into the United States (2000-2014), originally collected by the United States Fish and Wildlife Service. We curated and cleaned the data and added taxonomic information to improve data usability. These data include >2 million wildlife or wildlife product shipments, representing >60 biological classes and >3.2 billion live organisms. Further, the majority of species in the dataset are not currently reported on by CITES parties. These data will be broadly useful to both scientists and policymakers seeking to better understand the volume, sources, biological composition, and potential risks of the global wildlife trade.

Farm-Level Risk Factors of Increased Abortion and Mortality in Domestic Ruminants during the 2010 Rift Valley Fever Outbreak in Central South Africa.

(1) Background: Rift Valley fever (RVF) outbreaks in domestic ruminants have severe socio-economic impacts. Climate-based continental predictions providing early warnings to regions at risk for RVF outbreaks are not of a high enough resolution for ruminant owners to assess their individual risk. (2) Methods: We analyzed risk factors for RVF occurrence and severity at the farm level using the number of domestic ruminant deaths and abortions reported by farmers in central South Africa during the 2010 RVF outbreaks using a Bayesian multinomial hurdle framework. (3) Results: We found strong support that the proportion of days with precipitation, the number of water sources, and the proportion of goats in the herd were positively associated with increased severity of RVF (the numbers of deaths and abortions). We did not find an association between any risk factors and whether RVF was reported on farms. (4) Conclusions: At the farm level we identified risk factors of RVF severity; however, there was little support for risk factors of RVF occurrence. The identification of farm-level risk factors for Rift Valley fever virus (RVFV) occurrence would support and potentially improve current prediction methods and would provide animal owners with critical information needed in order to assess their herd's risk of RVFV infection.

A global repository of novel antimicrobial emergence events.

Despite considerable global surveillance of antimicrobial resistance (AMR), data on the global emergence of new resistance genotypes in bacteria has not been systematically compiled. We conducted a study of English-language scientific literature (2006-2017) and ProMED-mail disease surveillance reports (1994-2017) to identify global events of novel AMR emergence (first clinical reports of unique drug-bacteria resistance combinations). We screened 24,966 abstracts and reports, ultimately identifying 1,757 novel AMR emergence events from 268 peer-reviewed studies and 26 disease surveillance reports (294 total). Events were reported in 66 countries, with most events in the United States (152), China (128), and India (127). The most common bacteria demonstrating new resistance were Klebsiella pneumoniae (344) and Escherichia coli (218). Resistance was most common against antibiotic drugs imipenem (89 events), ciprofloxacin (84) and ceftazidime (83). We provide an open-access database of emergence events with standardized fields for bacterial species, drugs, location, and date. We discuss the impact of reporting and surveillance bias on database coverage, and we suggest guidelines for data analysis. This database may be broadly useful for understanding rates and patterns of AMR evolution, identifying global drivers and correlates, and targeting surveillance and interventions.

Hierarchical generalized additive models in ecology: an introduction with mgcv.

In this paper, we discuss an extension to two popular approaches to modeling complex structures in ecological data: the generalized additive model (GAM) and the hierarchical model (HGLM). The hierarchical GAM (HGAM), allows modeling of nonlinear functional relationships between covariates and outcomes where the shape of the function itself varies between different grouping levels. We describe the theoretical connection between HGAMs, HGLMs, and GAMs, explain how to model different assumptions about the degree of intergroup variability in functional response, and show how HGAMs can be readily fitted using existing GAM software, the mgcv package in R. We also discuss computational and statistical issues with fitting these models, and demonstrate how to fit HGAMs on example data. All code and data used to generate this paper are available at: github.com/eric-pedersen/mixed-effect-gams.

Human-animal interactions and bat coronavirus spillover potential among rural residents in Southern China.

Human interaction with animals has been implicated as a primary risk factor for several high impact zoonoses, including many bat-origin viral diseases. However the animal-to-human spillover events that lead to emerging diseases are rarely observed or clinically examined, and the link between specific interactions and spillover risk is poorly understood. To investigate this phenomenon, we conducted biological-behavioral surveillance among rural residents in Yunnan, Guangxi, and Guangdong districts of Southern China, where we have identified a number of SARS-related coronaviruses in bats. Serum samples were tested for four bat-borne coronaviruses using newly developed enzyme-linked immunosorbent assays (ELISA). Survey data were used to characterize associations between human-animal contact and bat coronavirus spillover risk. A total of 1,596 residents were enrolled in the study from 2015 to 2017. Nine participants (0.6%) tested positive for bat coronaviruses. 265 (17%) participants reported severe acute respiratory infections (SARI) and/or influenza-like illness (ILI) symptoms in the past year, which were associated with poultry, carnivore, rodent/shrew, or bat contact, with variability by family income and district of residence. This study provides serological evidence of bat coronavirus spillover in rural communities in Southern China. The low seroprevalence observed in this study suggests that bat coronavirus spillover is a rare event. Nonetheless, this study highlights associations between human-animal interaction and zoonotic spillover risk. These findings can be used to support targeted biological behavioral surveillance in high-risk geographic areas in order to reduce the risk of zoonotic disease emergence.

The global distribution of Bacillus anthracis and associated anthrax risk to humans, livestock and wildlife.

Bacillus anthracis is a spore-forming, Gram-positive bacterium responsible for anthrax, an acute infection that most significantly affects grazing livestock and wild ungulates, but also poses a threat to human health. The geographic extent of B. anthracis is poorly understood, despite multi-decade research on anthrax epizootic and epidemic dynamics; many countries have limited or inadequate surveillance systems, even within known endemic regions. Here, we compile a global occurrence dataset of human, livestock and wildlife anthrax outbreaks. With these records, we use boosted regression trees to produce a map of the global distribution of B. anthracis as a proxy for anthrax risk. We estimate that 1.83 billion people (95% credible interval (CI): 0.59-4.16 billion) live within regions of anthrax risk, but most of that population faces little occupational exposure. More informatively, a global total of 63.8 million poor livestock keepers (95% CI: 17.5-168.6 million) and 1.1 billion livestock (95% CI: 0.4-2.3 billion) live within vulnerable regions. Human and livestock vulnerability are both concentrated in rural rainfed systems throughout arid and temperate land across Eurasia, Africa and North America. We conclude by mapping where anthrax risk could disrupt sensitive conservation efforts for wild ungulates that coincide with anthrax-prone landscapes.

Benefits of a one health approach: An example using Rift Valley fever.

One Health has been promoted by international institutions as a framework to improve public health outcomes. Despite strong overall interest in One Health, country-, local- and project-level implementation remains limited, likely due to the lack of pragmatic and tested operational methods for implementation and metrics for evaluation. Here we use Rift Valley fever virus as an example to demonstrate the value of using a One Health approach for both scientific and resources advantages. We demonstrate that coordinated, a priori investigations between One Health sectors can yield higher statistical power to elucidate important public health relationships as compared to siloed investigations and post-hoc analyses. Likewise, we demonstrate that across a project or multi-ministry health study a One Health approach can result in improved resource efficiency, with resultant cost-savings (35% in the presented case). The results of these analyses demonstrate that One Health approaches can be directly and tangibly applied to health investigations.

Human-Wildlife Interactions Predict Febrile Illness in Park Landscapes of Western Uganda.

Fevers of unknown origin complicate treatment and prevention of infectious diseases and are a global health burden. We examined risk factors of self-reported fever-categorized as "malarial" and "nonmalarial"-in households adjacent to national parks across the Ugandan Albertine Rift, a biodiversity and emerging infectious disease hotspot. Statistical models fitted to these data suggest that perceived nonmalarial fevers of unknown origin were associated with more frequent direct contact with wildlife and with increased distance from parks where wildlife habitat is limited to small forest fragments. Perceived malarial fevers were associated with close proximity to parks but were not associated with direct wildlife contact. Self-reported fevers of any kind were not associated with livestock ownership. These results suggest a hypothesis that nonmalarial fevers in this area are associated with wildlife contact, and further investigation of zoonoses from wildlife is warranted. More generally, our findings of land use-disease relationships aid in hypothesis development for future research in this social-ecological system where emerging infectious diseases specifically, and rural public health provisioning generally, are important issues.

One Health Economics to confront disease threats.

Global economic impacts of epidemics suggest high return on investment in prevention and One Health capacity. However, such investments remain limited, contributing to persistent endemic diseases and vulnerability to emerging ones. An interdisciplinary workshop explored methods for country-level analysis of added value of One Health approaches to disease control. Key recommendations include: 1. systems thinking to identify risks and mitigation options for decision-making under uncertainty; 2. multisectoral economic impact assessment to identify wider relevance and possible resource-sharing, and 3. consistent integration of environmental considerations. Economic analysis offers a congruent measure of value complementing diverse impact metrics among sectors and contexts.