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.

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.

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.

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 Mòjiāng 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.

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.

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 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.

Centering microbes in the emerging role of integrative biology in understanding environmental change

We argue that 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.

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.

Extracting novel antimicrobial emergence events from scientific literature and medical reports

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 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 1,773 novel AMR emergence events from 294 articles. Events were reported in 66 countries, with most events in the United States (152), India (129), and China (128). The most common bacteria demonstrating new resistance were Klebsiella pneumoniae (352) and Escherichia coli (218). Resistance was most common against antibiotic drugs imipenem (89 events), ciprofloxacin (85) and ceftazidime (82). We provide an open-access database of emergence events with standardized fields for bacterial species, drugs, location, and date, and we discuss guidelines and caveats 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.

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.

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.

Origin and cross-species transmission of bat coronaviruses in China

Bats are presumed reservoirs of diverse coronaviruses (CoVs) including progenitors of Severe Acute Respiratory Syndrome (SARS)-CoV and SARS-CoV-2, the causative agent of COVID-19. However, the evolution and diversification of these coronaviruses remains poorly understood. Here we use a Bayesian statistical framework and a large sequence data set from bat-CoVs (including 630 novel CoV sequences) in China to study their macroevolution, cross-species transmission and dispersal. We find that host-switching occurs more frequently and across more distantly related host taxa in alpha- than beta-CoVs, and is more highly constrained by phylogenetic distance for beta-CoVs. We show that inter-family and -genus switching is most common in Rhinolophidae and the genus Rhinolophus. Our analyses identify the host taxa and geographic regions that define hotspots of CoV evolutionary diversity in China that could help target bat-CoV discovery for proactive zoonotic disease surveillance. Finally, we present a phylogenetic analysis suggesting a likely origin for SARS-CoV-2 in Rhinolophus spp. bats.

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for the Global Burden of Disease Study 2017

BACKGROUND

Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea.

METHODS

We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates.

FINDINGS

The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage.

INTERPRETATION

By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health.

FUNDING

Bill & Melinda Gates Foundation.

Origin and cross-species transmission of bat coronaviruses in China

Bats are presumed reservoirs of diverse coronaviruses (CoVs) including progenitors of Severe Acute Respiratory Syndrome (SARS)-CoV and SARS-CoV-2, the causative agent of COVID-19. However, the evolution and diversification of these coronaviruses remains poorly understood. We used a Bayesian statistical framework and sequence data from all known bat-CoVs (including 630 novel CoV sequences) to study their macroevolution, cross-species transmission, and dispersal in China. We find that host-switching was more frequent and across more distantly related host taxa in alpha-than beta-CoVs, and more highly constrained by phylogenetic distance for beta-CoVs. We show that inter-family and -genus switching is most common in Rhinolophidae and the genus Rhinolophus . Our analyses identify the host taxa and geographic regions that define hotspots of CoV evolutionary diversity in China that could help target bat-CoV discovery for proactive zoonotic disease surveillance. Finally, we present a phylogenetic analysis suggesting a likely origin for SARS-CoV-2 in Rhinolophus spp. bats.

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.

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.

Measurement(s)	Import • wildlife • wildlife product
Technology Type(s)	digital curation
Sample Characteristic - Environment	wildlife trade network
Sample Characteristic - Location	United States of America

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11439471

Incorporating Health Outcomes into Land-Use Planning

The global trend toward increased agricultural production puts pressure on undeveloped areas, raising the question of how to optimally allocate land. Land-use change has recently been linked to a number of human health outcomes, but these are not routinely considered in land-use decision making. We review examples of planners' currently used strategies to evaluate land use and present a conceptual model of optimal land use that incorporates health outcomes. We then present a framework for evaluating the health outcomes of land-use scenarios that can be used by decision makers in an integrated approach to land-use planning.

An Ecological Framework for Modeling the Geography of Disease Transmission

Ecological niche modeling (ENM) is widely employed in ecology to predict species’ potential geographic distributions in relation to their environmental constraints and is rapidly becoming the gold-standard method for disease risk mapping. However, given the biological complexity of disease systems, the traditional ENM framework requires reevaluation. We provide an overview of the application of ENM to disease systems and propose a theoretical framework based on the biological properties of both hosts and parasites to produce reliable outputs resembling disease system distributions. Additionally, we discuss the differences between biological considerations when implementing ENM for distributional ecology and epidemiology. This new framework will help the field of disease ecology and applications of biogeography in the epidemiology of infectious diseases.

Infectious diseases greatly impact human health, biodiversity, and global economies, highlighting the need to understand and predict their distributions.

Ecological niche modeling (ENM) was not originally designed to explicitly reconstruct complex biological phenomena such as diseases or parasitism, requiring a reevaluation of the traditional framework.

We provide an integrative ENM framework for disease systems that considers suitable host availability, parasite ecologies, and different scales of modeling.

Disease transmission is driven by factors related to parasite availability and host exposure and susceptibility, which can be incorporated in ENM frameworks.

Global hotspots and correlates of emerging zoonotic diseases

Zoonoses originating from wildlife represent a significant threat to global health, security and economic growth, and combatting their emergence is a public health priority. However, our understanding of the mechanisms underlying their emergence remains rudimentary. Here we update a global database of emerging infectious disease (EID) events, create a novel measure of reporting effort, and fit boosted regression tree models to analyze the demographic, environmental and biological correlates of their occurrence. After accounting for reporting effort, we show that zoonotic EID risk is elevated in forested tropical regions experiencing land-use changes and where wildlife biodiversity (mammal species richness) is high. We present a new global hotspot map of spatial variation in our zoonotic EID risk index, and partial dependence plots illustrating relationships between events and predictors. Our results may help to improve surveillance and long-term EID monitoring programs, and design field experiments to test underlying mechanisms of zoonotic disease emergence.

Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990-2015: a novel analysis from the Global Burden of Disease Study 2015

BACKGROUND

National levels of personal health-care access and quality can be approximated by measuring mortality rates from causes that should not be fatal in the presence of effective medical care (ie, amenable mortality). Previous analyses of mortality amenable to health care only focused on high-income countries and faced several methodological challenges. In the present analysis, we use the highly standardised cause of death and risk factor estimates generated through the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015.

METHODS

We mapped the most widely used list of causes amenable to personal health care developed by Nolte and McKee to 32 GBD causes. We accounted for variations in cause of death certification and misclassifications through the extensive data standardisation processes and redistribution algorithms developed for GBD. To isolate the effects of personal health-care access and quality, we risk-standardised cause-specific mortality rates for each geography-year by removing the joint effects of local environmental and behavioural risks, and adding back the global levels of risk exposure as estimated for GBD 2015. We employed principal component analysis to create a single, interpretable summary measure-the Healthcare Quality and Access (HAQ) Index-on a scale of 0 to 100. The HAQ Index showed strong convergence validity as compared with other health-system indicators, including health expenditure per capita (r=0·88), an index of 11 universal health coverage interventions (r=0·83), and human resources for health per 1000 (r=0·77). We used free disposal hull analysis with bootstrapping to produce a frontier based on the relationship between the HAQ Index and the Socio-demographic Index (SDI), a measure of overall development consisting of income per capita, average years of education, and total fertility rates. This frontier allowed us to better quantify the maximum levels of personal health-care access and quality achieved across the development spectrum, and pinpoint geographies where gaps between observed and potential levels have narrowed or widened over time.

FINDINGS

Between 1990 and 2015, nearly all countries and territories saw their HAQ Index values improve; nonetheless, the difference between the highest and lowest observed HAQ Index was larger in 2015 than in 1990, ranging from 28·6 to 94·6. Of 195 geographies, 167 had statistically significant increases in HAQ Index levels since 1990, with South Korea, Turkey, Peru, China, and the Maldives recording among the largest gains by 2015. Performance on the HAQ Index and individual causes showed distinct patterns by region and level of development, yet substantial heterogeneities emerged for several causes, including cancers in highest-SDI countries; chronic kidney disease, diabetes, diarrhoeal diseases, and lower respiratory infections among middle-SDI countries; and measles and tetanus among lowest-SDI countries. While the global HAQ Index average rose from 40·7 (95% uncertainty interval, 39·0-42·8) in 1990 to 53·7 (52·2-55·4) in 2015, far less progress occurred in narrowing the gap between observed HAQ Index values and maximum levels achieved; at the global level, the difference between the observed and frontier HAQ Index only decreased from 21·2 in 1990 to 20·1 in 2015. If every country and territory had achieved the highest observed HAQ Index by their corresponding level of SDI, the global average would have been 73·8 in 2015. Several countries, particularly in eastern and western sub-Saharan Africa, reached HAQ Index values similar to or beyond their development levels, whereas others, namely in southern sub-Saharan Africa, the Middle East, and south Asia, lagged behind what geographies of similar development attained between 1990 and 2015.

INTERPRETATION

This novel extension of the GBD Study shows the untapped potential for personal health-care access and quality improvement across the development spectrum. Amid substantive advances in personal health care at the national level, heterogeneous patterns for individual causes in given countries or territories suggest that few places have consistently achieved optimal health-care access and quality across health-system functions and therapeutic areas. This is especially evident in middle-SDI countries, many of which have recently undergone or are currently experiencing epidemiological transitions. The HAQ Index, if paired with other measures of health-system characteristics such as intervention coverage, could provide a robust avenue for tracking progress on universal health coverage and identifying local priorities for strengthening personal health-care quality and access throughout the world.

FUNDING

Bill & Melinda Gates Foundation.

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.

Host and viral traits predict zoonotic spillover from mammals

Analysis of a comprehensive database of mammalian host–virus relationships reveals that both the total number of viruses that infect a given species and the proportion likely to be zoonotic are predictable and that this enables identification of mammalian species and geographic locations where novel zoonoses are likely to be found.

Zoonotic viruses, many originating in wild mammals, pose a serious threat to global public health. Peter Daszak and colleagues create a comprehensive database of mammalian host–virus relationships, which they analyse to determine patterns of virus and zoonotic virus distribution in mammals. They identify various factors that influence the number and diversity of viruses that infect a given species as well as factors that predict the proportion of zoonotic viruses per species. In doing so, they identify mammalian species and geographic locations where novel zoonoses are likely to be found.

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)^1,2,3. Understanding patterns of viral diversity in wildlife and determinants of successful cross-species transmission, or spillover, are therefore key goals for pandemic surveillance programs⁴. 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^5,6,7. 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.

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.

Summarizing US Wildlife Trade with an Eye Toward Assessing the Risk of Infectious Disease Introduction

The aim of this study was to characterize the role of the USA in the global exchange of wildlife and describe high volume trade with an eye toward prioritizing health risk assessment questions for further analysis. Here we summarize nearly 14 years (2000-2013) of the most comprehensive data available (USFWS LEMIS system), involving 11 billion individual specimens and an additional 977 million kilograms of wildlife. The majority of shipments contained mammals (27%), while the majority of specimens imported were shells (57%) and tropical fish (25%). Most imports were facilitated by the aquatic and pet industry, resulting in one-third of all shipments containing live animals. The importer reported origin of wildlife was 77.7% wild-caught and 17.7% captive-reared. Indonesia was the leading exporter of legal shipments, while Mexico was the leading source reported for illegal shipments. At the specimen level, China was the leading exporter of legal and illegal wildlife imports. The number of annual declared shipments doubled during the period examined, illustrating continually increasing demand, which reinforces the need to scale up capacity for border inspections, risk management protocols and disease surveillance. Most regulatory oversight of wildlife trade is aimed at conservation, rather than prevention of disease introduction.

Measuring the health-related Sustainable Development Goals in 188 countries: a baseline analysis from the Global Burden of Disease Study 2015

BACKGROUND

In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015).

METHODS

We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices.

FINDINGS

In 2015, the median health-related SDG index was 59·3 (95% uncertainty interval 56·8-61·8) and varied widely by country, ranging from 85·5 (84·2-86·5) in Iceland to 20·4 (15·4-24·9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r2=0·88) and the MDG index (r2=0·92), whereas the non-MDG index had a weaker relation with SDI (r2=0·79). Between 2000 and 2015, the health-related SDG index improved by a median of 7·9 (IQR 5·0-10·4), and gains on the MDG index (a median change of 10·0 [6·7-13·1]) exceeded that of the non-MDG index (a median change of 5·5 [2·1-8·9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened.

INTERPRETATION

GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.

FUNDING

Bill & Melinda Gates Foundation.

Non-random patterns in viral diversity

It is currently unclear whether changes in viral communities will ever be predictable. Here we investigate whether viral communities in wildlife are inherently structured (inferring predictability) by looking at whether communities are assembled through deterministic (often predictable) or stochastic (not predictable) processes. We sample macaque faeces across nine sites in Bangladesh and use consensus PCR and sequencing to discover 184 viruses from 14 viral families. We then use network modelling and statistical null-hypothesis testing to show the presence of non-random deterministic patterns at different scales, between sites and within individuals. We show that the effects of determinism are not absolute however, as stochastic patterns are also observed. In showing that determinism is an important process in viral community assembly we conclude that it should be possible to forecast changes to some portion of a viral community, however there will always be some portion for which prediction will be unlikely.

Targeting Transmission Pathways for Emerging Zoonotic Disease Surveillance and Control

We used literature searches and a database of all reported emerging infectious diseases (EIDs) to analyze the most important transmission pathways (e.g., vector-borne, aerosol droplet transmitted) for emerging zoonoses. Our results suggest that at the broad scale, the likelihood of transmission occurring through any one pathway is approximately equal. However, the major transmission pathways for zoonoses differ widely according to the specific underlying drivers of EID events (e.g., land-use change, agricultural intensification). These results can be used to develop better targeting of surveillance for, and more effective control of newly emerged zoonoses in regions under different underlying pressures that drive disease emergence.

Metacommunity and phylogenetic structure determine wildlife and zoonotic infectious disease patterns in time and space

The potential for disease transmission at the interface of wildlife, domestic animals and humans has become a major concern for public health and conservation biology. Research in this subject is commonly conducted at local scales while the regional context is neglected. We argue that prevalence of infection at local and regional levels is influenced by three mechanisms occurring at the landscape level in a metacommunity context. First, (1) dispersal, colonization, and extinction of pathogens, reservoir or vector hosts, and nonreservoir hosts, may be due to stochastic and niche-based processes, thus determining distribution of all species, and then their potential interactions, across local communities (metacommunity structure). Second, (2) anthropogenic processes may drive environmental filtering of hosts, nonhosts, and pathogens. Finally, (3) phylogenetic diversity relative to reservoir or vector host(s), within and between local communities may facilitate pathogen persistence and circulation. Using a metacommunity approach, public heath scientists may better evaluate the factors that predispose certain times and places for the origin and emergence of infectious diseases. The multidisciplinary approach we describe fits within a comprehensive One Health and Ecohealth framework addressing zoonotic infectious disease outbreaks and their relationship to their hosts, other animals, humans, and the environment.

Duration of Maternal Antibodies against Canine Distemper Virus and Hendra Virus in Pteropid Bats

Old World frugivorous bats have been identified as natural hosts for emerging zoonotic viruses of significant public health concern, including henipaviruses (Nipah and Hendra virus), Ebola virus, and Marburg virus. Epidemiological studies of these viruses in bats often utilize serology to describe viral dynamics, with particular attention paid to juveniles, whose birth increases the overall susceptibility of the population to a viral outbreak once maternal immunity wanes. However, little is understood about bat immunology, including the duration of maternal antibodies in neonates. Understanding duration of maternally derived immunity is critical for characterizing viral dynamics in bat populations, which may help assess the risk of spillover to humans. We conducted two separate studies of pregnant Pteropus bat species and their offspring to measure the half-life and duration of antibodies to 1) canine distemper virus antigen in vaccinated captive Pteropus hypomelanus; and 2) Hendra virus in wild-caught, naturally infected Pteropus alecto. Both of these pteropid bat species are known reservoirs for henipaviruses. We found that in both species, antibodies were transferred from dam to pup. In P. hypomelanus pups, titers against CDV waned over a mean period of 228.6 days (95% CI: 185.4-271.8) and had a mean terminal phase half-life of 96.0 days (CI 95%: 30.7-299.7). In P. alecto pups, antibodies waned over 255.13 days (95% CI: 221.0-289.3) and had a mean terminal phase half-life of 52.24 days (CI 95%: 33.76-80.83). Each species showed a duration of transferred maternal immunity of between 7.5 and 8.5 months, which was longer than has been previously estimated. These data will allow for more accurate interpretation of age-related Henipavirus serological data collected from wild pteropid bats.

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.