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.

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

This corrects the article DOI: 10.1038/nature22975.

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.

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.

Classification of new morbillivirus and jeilongvirus sequences from bats sampled in Brazil and Malaysia.

As part of a broad One Health surveillance effort to detect novel viruses in wildlife and people, we report several paramyxovirus sequences sampled primarily from bats during 2013 and 2014 in Brazil and Malaysia, including seven from which we recovered full-length genomes. Of these, six represent the first full-length paramyxovirid genomes sequenced from the Americas, including two that are the first full-length bat morbillivirus genome sequences published to date. Our findings add to the vast number of viral sequences in public repositories, which have been increasing considerably in recent years due to the rising accessibility of metagenomics. Taxonomic classification of these sequences in the absence of phenotypic data has been a significant challenge, particularly in the subfamily Orthoparamyxovirinae, where the rate of discovery of novel sequences has been substantial. Using pairwise amino acid sequence classification (PAASC), we propose that five of these sequences belong to members of the genus Jeilongvirus and two belong to members of the genus Morbillivirus. We also highlight inconsistencies in the classification of Tupaia virus and Mòjiang virus using the same demarcation criteria and suggest reclassification of these viruses into new genera. Importantly, this study underscores the critical importance of sequence length in PAASC analysis as well as the importance of biological characteristics such as genome organization in the taxonomic classification of viral sequences.

Was the COVID-19 pandemic avoidable? A call for a "solution-oriented" approach in pathogen evolutionary ecology to prevent future outbreaks.

Concerns about the prospect of a global pandemic have been triggered many times during the last two decades. These have been realised through the current COVID-19 pandemic, due to a new coronavirus SARS-CoV2, which has impacted almost every country on Earth. Here, we show how considering the pandemic through the lenses of the evolutionary ecology of pathogens can help better understand the root causes and devise solutions to prevent the emergence of future pandemics. We call for better integration of these approaches into transdisciplinary research and invite scientists working on the evolutionary ecology of pathogens to contribute to a more "solution-oriented" agenda with practical applications, emulating similar movements in the field of economics in recent decades.

Global biogeography of human infectious diseases.

The distributions of most infectious agents causing disease in humans are poorly resolved or unknown. However, poorly known and unknown agents contribute to the global burden of disease and will underlie many future disease risks. Existing patterns of infectious disease co-occurrence could thus play a critical role in resolving or anticipating current and future disease threats. We analyzed the global occurrence patterns of 187 human infectious diseases across 225 countries and seven epidemiological classes (human-specific, zoonotic, vector-borne, non-vector-borne, bacterial, viral, and parasitic) to show that human infectious diseases exhibit distinct spatial grouping patterns at a global scale. We demonstrate, using outbreaks of Ebola virus as a test case, that this spatial structuring provides an untapped source of prior information that could be used to tighten the focus of a range of health-related research and management activities at early stages or in data-poor settings, including disease surveillance, outbreak responses, or optimizing pathogen discovery. In examining the correlates of these spatial patterns, among a range of geographic, epidemiological, environmental, and social factors, mammalian biodiversity was the strongest predictor of infectious disease co-occurrence overall and for six of the seven disease classes examined, giving rise to a striking congruence between global pathogeographic and "Wallacean" zoogeographic patterns. This clear biogeographic signal suggests that infectious disease assemblages remain fundamentally constrained in their distributions by ecological barriers to dispersal or establishment, despite the homogenizing forces of globalization. Pathogeography thus provides an overarching context in which other factors promoting infectious disease emergence and spread are set.

Interdisciplinary approaches to understanding disease emergence: the past, present, and future drivers of Nipah virus emergence.

Emerging infectious diseases (EIDs) pose a significant threat to human health, economic stability, and biodiversity. Despite this, the mechanisms underlying disease emergence are still not fully understood, and control measures rely heavily on mitigating the impact of EIDs after they have emerged. Here, we highlight the emergence of a zoonotic Henipavirus, Nipah virus, to demonstrate the interdisciplinary and macroecological approaches necessary to understand EID emergence. Previous work suggests that Nipah virus emerged due to the interaction of the wildlife reservoir (Pteropus spp. fruit bats) with intensively managed livestock. The emergence of this and other henipaviruses involves interactions among a suite of anthropogenic environmental changes, socioeconomic factors, and changes in demography that overlay and interact with the distribution of these pathogens in their wildlife reservoirs. Here, we demonstrate how ecological niche modeling may be used to investigate the potential role of a changing climate on the future risk for Henipavirus emergence. We show that the distribution of Henipavirus reservoirs, and therefore henipaviruses, will likely change under climate change scenarios, a fundamental precondition for disease emergence in humans. We assess the variation among climate models to estimate where Henipavirus host distribution is most likely to expand, contract, or remain stable, presenting new risks for human health. We conclude that there is substantial potential to use this modeling framework to explore the distribution of wildlife hosts under a changing climate. These approaches may directly inform current and future management and surveillance strategies aiming to improve pathogen detection and, ultimately, reduce emergence risk.

Bats are a major natural reservoir for hepaciviruses and pegiviruses.

Although there are over 1,150 bat species worldwide, the diversity of viruses harbored by bats has only recently come into focus as a result of expanded wildlife surveillance. Such surveys are of importance in determining the potential for novel viruses to emerge in humans, and for optimal management of bats and their habitats. To enhance our knowledge of the viral diversity present in bats, we initially surveyed 415 sera from African and Central American bats. Unbiased high-throughput sequencing revealed the presence of a highly diverse group of bat-derived viruses related to hepaciviruses and pegiviruses within the family Flaviridae. Subsequent PCR screening of 1,258 bat specimens collected worldwide indicated the presence of these viruses also in North America and Asia. A total of 83 bat-derived viruses were identified, representing an infection rate of nearly 5%. Evolutionary analyses revealed that all known hepaciviruses and pegiviruses, including those previously documented in humans and other primates, fall within the phylogenetic diversity of the bat-derived viruses described here. The prevalence, unprecedented viral biodiversity, phylogenetic divergence, and worldwide distribution of the bat-derived viruses suggest that bats are a major and ancient natural reservoir for both hepaciviruses and pegiviruses and provide insights into the evolutionary history of hepatitis C virus and the human GB viruses.

Prediction and prevention of the next pandemic zoonosis.

Most pandemics--eg, HIV/AIDS, severe acute respiratory syndrome, pandemic influenza--originate in animals, are caused by viruses, and are driven to emerge by ecological, behavioural, or socioeconomic changes. Despite their substantial effects on global public health and growing understanding of the process by which they emerge, no pandemic has been predicted before infecting human beings. We review what is known about the pathogens that emerge, the hosts that they originate in, and the factors that drive their emergence. We discuss challenges to their control and new efforts to predict pandemics, target surveillance to the most crucial interfaces, and identify prevention strategies. New mathematical modelling, diagnostic, communications, and informatics technologies can identify and report hitherto unknown microbes in other species, and thus new risk assessment approaches are needed to identify microbes most likely to cause human disease. We lay out a series of research and surveillance opportunities and goals that could help to overcome these challenges and move the global pandemic strategy from response to pre-emption.

Operationalizing One Health: Environmental Solutions for Pandemic Prevention.

Human pressure on the environment is increasing the frequency, diversity, and spatial extent of disease outbreaks. Despite international recognition, the interconnection between the health of the environment, animals, and humans has been historically overlooked. Past and current initiatives have often neglected prevention under the One Health preparedness cycle, largely focusing on post-spillover stages. We argue that pandemic prevention initiatives have yet to produce actionable targets and indicators, connected to overarching goals, like it has been done for biodiversity loss and climate change. We show how the Driver-Pressure-State-Impact-Response framework, already employed by the Convention on Biological Diversity, can be repurposed to operationalize pandemic prevention. Global responses for pandemic prevention should strive for complementarity and synergies among initiatives, better articulating prevention under One Health. Without agreed-upon goals underpinning specific targets and interventions, current global efforts are unlikely to function at the speed and scale necessary to decrease the risk of disease outbreaks that might lead to pandemics. Threats to the environment are not always abatable, but decreasing the likelihood that environmental pressure leads to pandemics, and developing strategies to mitigate these impacts, are both attainable goals.

Plant and animal endemism in the eastern Andean slope: challenges to conservation.

BACKGROUND: The Andes-Amazon basin of Peru and Bolivia is one of the most data-poor, biologically rich, and rapidly changing areas of the world. Conservation scientists agree that this area hosts extremely high endemism, perhaps the highest in the world, yet we know little about the geographic distributions of these species and ecosystems within country boundaries. To address this need, we have developed conservation data on endemic biodiversity (~800 species of birds, mammals, amphibians, and plants) and terrestrial ecological systems (~90; groups of vegetation communities resulting from the action of ecological processes, substrates, and/or environmental gradients) with which we conduct a fine scale conservation prioritization across the Amazon watershed of Peru and Bolivia. We modelled the geographic distributions of 435 endemic plants and all 347 endemic vertebrate species, from existing museum and herbaria specimens at a regional conservation practitioner's scale (1:250,000-1:1,000,000), based on the best available tools and geographic data. We mapped ecological systems, endemic species concentrations, and irreplaceable areas with respect to national level protected areas. RESULTS: We found that sizes of endemic species distributions ranged widely (< 20 km2 to > 200,000 km2) across the study area. Bird and mammal endemic species richness was greatest within a narrow 2500-3000 m elevation band along the length of the Andes Mountains. Endemic amphibian richness was highest at 1000-1500 m elevation and concentrated in the southern half of the study area. Geographical distribution of plant endemism was highly taxon-dependent. Irreplaceable areas, defined as locations with the highest number of species with narrow ranges, overlapped slightly with areas of high endemism, yet generally exhibited unique patterns across the study area by species group. We found that many endemic species and ecological systems are lacking national-level protection; a third of endemic species have distributions completely outside of national protected areas. Protected areas cover only 20% of areas of high endemism and 20% of irreplaceable areas. Almost 40% of the 91 ecological systems are in serious need of protection (= < 2% of their ranges protected). CONCLUSIONS: We identify for the first time, areas of high endemic species concentrations and high irreplaceability that have only been roughly indicated in the past at the continental scale. We conclude that new complementary protected areas are needed to safeguard these endemics and ecosystems. An expansion in protected areas will be challenged by geographically isolated micro-endemics, varied endemic patterns among taxa, increasing deforestation, resource extraction, and changes in climate. Relying on pre-existing collections, publically accessible datasets and tools, this working framework is exportable to other regions plagued by incomplete conservation data.

Centering Microbes in the Emerging Role of Integrative Biology in Understanding Environmental Change.

The current environmental changes stressing the Earth's biological systems urgently require study from an integrated perspective to reveal unexpected, cross-scale interactions, particularly between microbes and macroscale phenomena. Such interactions are the basis of a mechanistic understanding of the important connections between deforestation and emerging infectious disease, feedback between ecosystem disturbance and the gut microbiome, and the cross-scale effects of environmental pollutants. These kinds of questions can be answered with existing techniques and data, but a concerted effort is necessary to better coordinate studies and data sets from different disciplines to fully leverage their potential.

A strategy to assess spillover risk of bat SARS-related coronaviruses in Southeast Asia.

Emerging diseases caused by coronaviruses of likely bat origin (e.g., SARS, MERS, SADS, COVID-19) have disrupted global health and economies for two decades. Evidence suggests that some bat SARS-related coronaviruses (SARSr-CoVs) could infect people directly, and that their spillover is more frequent than previously recognized. Each zoonotic spillover of a novel virus represents an opportunity for evolutionary adaptation and further spread; therefore, quantifying the extent of this spillover may help target prevention programs. We derive current range distributions for known bat SARSr-CoV hosts and quantify their overlap with human populations. We then use probabilistic risk assessment and data on human-bat contact, human viral seroprevalence, and antibody duration to estimate that a median of 66,280 people (95% CI: 65,351-67,131) are infected with SARSr-CoVs annually in Southeast Asia. These data on the geography and scale of spillover can be used to target surveillance and prevention programs for potential future bat-CoV emergence.

Prevalence of bat viruses associated with land-use change in the Atlantic Forest, Brazil.

Introduction: Bats are critical to maintaining healthy ecosystems and many species are threatened primarily due to global habitat loss. Bats are also important hosts of a range of viruses, several of which have had significant impacts on global public health. The emergence of these viruses has been associated with land-use change and decreased host species richness. Yet, few studies have assessed how bat communities and the viruses they host alter with land-use change, particularly in highly biodiverse sites. Methods: In this study, we investigate the effects of deforestation on bat host species richness and diversity, and viral prevalence and richness across five forested sites and three nearby deforested sites in the interior Atlantic Forest of southern Brazil. Nested-PCR and qPCR were used to amplify and detect viral genetic sequence from six viral families (corona-, adeno-, herpes-, hanta-, paramyxo-, and astro-viridae) in 944 blood, saliva and rectal samples collected from 335 bats. Results: We found that deforested sites had a less diverse bat community than forested sites, but higher viral prevalence and richness after controlling for confounding factors. Viral detection was more likely in juvenile males located in deforested sites. Interestingly, we also found a significant effect of host bat species on viral prevalence indicating that viral taxa were detected more frequently in some species than others. In particular, viruses from the Coronaviridae family were detected more frequently in generalist species compared to specialist species. Discussion: Our findings suggest that deforestation may drive changes in the ecosystem which reduce bat host diversity while increasing the abundance of generalist species which host a wider range of viruses.

The costs and benefits of primary prevention of zoonotic pandemics.

The lives lost and economic costs of viral zoonotic pandemics have steadily increased over the past century. Prominent policymakers have promoted plans that argue the best ways to address future pandemic catastrophes should entail, "detecting and containing emerging zoonotic threats." In other words, we should take actions only after humans get sick. We sharply disagree. Humans have extensive contact with wildlife known to harbor vast numbers of viruses, many of which have not yet spilled into humans. We compute the annualized damages from emerging viral zoonoses. We explore three practical actions to minimize the impact of future pandemics: better surveillance of pathogen spillover and development of global databases of virus genomics and serology, better management of wildlife trade, and substantial reduction of deforestation. We find that these primary pandemic prevention actions cost less than 1/20th the value of lives lost each year to emerging viral zoonoses and have substantial cobenefits.

A strategy to assess spillover risk of bat SARS-related coronaviruses in Southeast Asia.

Emerging diseases caused by coronaviruses of likely bat origin (e.g. SARS, MERS, SADS and COVID-19) have disrupted global health and economies for two decades. Evidence suggests that some bat SARS-related coronaviruses (SARSr-CoVs) could infect people directly, and that their spillover is more frequent than previously recognized. Each zoonotic spillover of a novel virus represents an opportunity for evolutionary adaptation and further spread; therefore, quantifying the extent of this "hidden" spillover may help target prevention programs. We derive biologically realistic range distributions for known bat SARSr-CoV hosts and quantify their overlap with human populations. We then use probabilistic risk assessment and data on human-bat contact, human SARSr-CoV seroprevalence, and antibody duration to estimate that ∼400,000 people (median: ∼50,000) are infected with SARSr-CoVs annually in South and Southeast Asia. These data on the geography and scale of spillover can be used to target surveillance and prevention programs for potential future bat-CoV emergence.

Land-use change and rodent-borne diseases: hazards on the shared socioeconomic pathways.

Land-use change has a direct impact on species survival and reproduction, altering their spatio-temporal distributions. It acts as a selective force that favours the abundance and diversity of reservoir hosts and affects host-pathogen dynamics and prevalence. This has led to land-use change being a significant driver of infectious diseases emergence. Here, we predict the presence of rodent taxa and map the zoonotic hazard (potential sources of harm) from rodent-borne diseases in the short and long term (2025 and 2050). The study considers three different land-use scenarios based on the shared socioeconomic pathways narratives (SSPs): sustainable (SSP1-Representative Concentration Pathway (RCP) 2.6), fossil-fuelled development (SSP5-RCP 8.5) and deepening inequality (SSP4-RCP 6.0). We found that cropland expansion into forest and pasture may increase zoonotic hazards in areas with high rodent-species diversity. Nevertheless, a future sustainable scenario may not always reduce hazards. All scenarios presented high heterogeneity in zoonotic hazard, with high-income countries having the lowest hazard range. The SSPs narratives suggest that opening borders and reducing cropland expansion are critical to mitigate current and future zoonotic hazards globally, particularly in middle- and low-income economies. Our study advances previous efforts to anticipate the emergence of zoonotic diseases by integrating past, present and future information to guide surveillance and mitigation of zoonotic hazards at the regional and local scale. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

A COVID-19 Risk Assessment for the US Labor Force.

The consequences of COVID-19 infection varies substantially based on individual social risk factors and predisposing health conditions. Understanding this variability may be critical for targeting COVID-19 control measures, resources and policies, including efforts to return people back to the workplace. We compiled individual level data from the National Health Information Survey and Quarterly Census of Earnings and Wages to estimate the number of at-risk workers for each US county and industry, accounting for both social and health risks. Nearly 80% of all workers have at least one health risk and 11% are over 60 with an additional health risk. We document important variation in the at-risk population across states, counties, and industries that could provide a strategic underpinning to a staged return to work.