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.

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.

Evolutionary Dynamics and Global Diversity of Influenza A Virus.

UNLABELLED: The increasing number of zoonotic infections caused by influenza A virus (IAV) subtypes of avian origin (e.g., H5N1 and H7N9) in recent years underscores the need to better understand the factors driving IAV evolution and diversity. To evaluate the current feasibility of global analyses to contribute to this aim, we evaluated information in the public domain to explore IAV evolutionary dynamics, including nucleotide substitution rates and selection pressures, using 14 IAV subtypes in 32 different countries over a 12-year period (2000 to 2011). Using geospatial information from 39,785 IAV strains, we examined associations between subtype diversity and socioeconomic, biodiversity, and agricultural indices. Our analyses showed that nucleotide substitution rates for 11 of the 14 evaluated subtypes tended to be higher in Asian countries, particularly in East Asia, than in Canada and the United States. Similarly, at a regional level, subtypes H5N1, H5N2, and H6N2 exhibited significantly higher substitution rates in East Asia than in North America. In contrast, the selection pressures (measured as ratios of nonsynonymous to synonymous evolutionary changes [dN/dS ratios]) acting on individual subtypes showed little geographic variation. We found that the strongest predictors for the detected subtype diversity at the country level were reporting effort (i.e., total number of strains reported) and health care spending (an indicator of economic development). Our analyses also identified major global gaps in IAV reporting (including a lack of sequences submitted from large portions of Africa and South America and a lack of geolocation information) and in broad subtype testing which, until addressed, will continue to hinder efforts to track the evolution and diversity of IAV around the world. IMPORTANCE: In recent years, an increasing number of influenza A virus (IAV) subtypes, including H5N1, H7N9, and H10N8, have been detected in humans. High fatality rates have led to an increased urgency to better understand where and how novel pathogenic influenza virus strains emerge. Our findings showed that mutational rates of 11 commonly encountered subtypes were higher in East Asian countries than in North America, suggesting that there may be a greater risk for the emergence of novel pathogenic strains in East Asia. In assessing the potential drivers of IAV subtype diversity, our analyses confirmed that reporting effort and health care spending were the best predictors of the observed subtype diversity at the country level. These findings underscore the need to increase sampling and reporting efforts for all subtypes in many undersampled countries throughout the world.

Bird Migration and Avian Influenza: A Comparison of Hydrogen Stable Isotopes and Satellite Tracking Methods.

Satellite-based tracking of migratory waterfowl is an important tool for understanding the potential role of wild birds in the long-distance transmission of highly pathogenic avian influenza. However, employing this technique on a continental scale is prohibitively expensive. This study explores the utility of stable isotope ratios in feathers in examining both the distances traveled by migratory birds and variation in migration behavior. We compared the satellite-derived movement data of 22 ducks from 8 species captured at wintering areas in Bangladesh, Turkey, and Hong Kong with deuterium ratios (δD) of these and other individuals captured at the same locations. We derived likely molting locations from the satellite tracking data and generated expected isotope ratios based on an interpolated map of δD in rainwater. Although δD was correlated with the distance between wintering and molting locations, surprisingly, measured δD values were not correlated with either expected values or latitudes of molting sites. However, population-level parameters derived from the satellite-tracking data, such as mean distance between wintering and molting locations and variation in migration distance, were reflected by means and variation of the stable isotope values. Our findings call into question the relevance of the rainfall isotope map for Asia for linking feather isotopes to molting locations, and underscore the need for extensive ground truthing in the form of feather-based isoscapes. Nevertheless, stable isotopes from feathers could inform disease models by characterizing the degree to which regional breeding populations interact at common wintering locations. Feather isotopes also could aid in surveying wintering locations to determine where high-resolution tracking techniques (e.g. satellite tracking) could most effectively be employed. Moreover, intrinsic markers such as stable isotopes offer the only means of inferring movement information from birds that have died as a result of infection. In the absence of feather based-isoscapes, we recommend a combination of isotope analysis and satellite-tracking as the best means of generating aggregate movement data for informing disease models.

Predicting hotspots for influenza virus reassortment.

The 1957 and 1968 influenza pandemics, each of which killed ≈1 million persons, arose through reassortment events. Influenza virus in humans and domestic animals could reassort and cause another pandemic. To identify geographic areas where agricultural production systems are conducive to reassortment, we fitted multivariate regression models to surveillance data on influenza A virus subtype H5N1 among poultry in China and Egypt and subtype H3N2 among humans. We then applied the models across Asia and Egypt to predict where subtype H3N2 from humans and subtype H5N1 from birds overlap; this overlap serves as a proxy for co-infection and in vivo reassortment. For Asia, we refined the prioritization by identifying areas that also have high swine density. Potential geographic foci of reassortment include the northern plains of India, coastal and central provinces of China, the western Korean Peninsula and southwestern Japan in Asia, and the Nile Delta in Egypt.

Modeling DREAMS impact: trends in new HIV diagnoses among women attending antenatal care clinics in DREAMS countries.

OBJECTIVES: To understand the impact of United States President's Emergency Plan for AIDS Relief (PEPFAR's) DREAMS (Determined, Resilient, Empowered, AIDS-Free, Mentored, and Safe) Partnership on new HIV diagnoses among women in antenatal care (ANC) settings in 10 African countries from 2015 to 2020. DESIGN: We modeled spatiotemporal changes in new HIV diagnoses among women in ANC settings using PEPFAR data. Statistical tests were performed in R to compare differences in new diagnoses rates between DREAMS and non-DREAMS subnational units (SNUs) and to explore predictors of new diagnoses declines within DREAMS SNUs. METHODS: We used a predictive geospatial model to forecast the rate of new diagnoses for each time period in a 5 km grid cell (n = 861 SNUs). Linear model analyses were conducted using predictor variables: urbanicity, DREAMS geographic footprint, 'layering' proxy, and community-level male viral load suppression. RESULTS: New HIV diagnoses in ANC from 2015 to 2020 declined in nearly all SNUs. 'Always' DREAMS SNUs reported declines of 45% while 'Never' DREAMS SNUs reported a decline of only 37% (F = 8.1, 1 and 829 DF, P < 0.01). Within Always DREAMS SNUs, greater declines were seen in areas with a higher number of minimum services in their DREAMS primary package (t = 2.77, P < 0.01). CONCLUSION: New HIV diagnoses among women are declining in both DREAMS and non-DREAMS SNUs; mirroring HIV incidence decreases and reflecting increasing community viral load suppression and voluntary male medical circumcision rates. DREAMS programming may have contributed to accelerated declines of new HIV diagnoses in DREAMS SNUs compared with non-DREAMS SNUs. Increased progress is needed to further reduce the disparities between adolescent girls and young women (AGYW) and young men to achieve epidemic control.

Diversity and composition of viral communities: coinfection of barley and cereal yellow dwarf viruses in California grasslands.

Most species host multiple pathogens, yet field studies rarely examine the processes determining pathogen diversity within a single host or the effects of coinfection on pathogen dynamics in natural systems. Coinfection can affect pathogen transmission and virulence. In turn, coinfection can be regulated within hosts by interactions such as cross-protective immunity or at broader spatial scales via vector distributions. Using a general model, we demonstrate that coinfection by a group of vectored pathogens is highest with abundant generalist vectors and weak cross-protection and coinfection-induced mortality. Using these predictions, we investigate the distribution of five coexisting aphid-vectored, viral pathogens (barley and cereal yellow dwarf luteoviruses and poleroviruses) in a native perennial grass (Elymus glaucus) in both space (700 km) and time (4 years). Observed coinfection rates were much higher than expected at random, suggesting that within-host processes exerted weak effects on within-host pathogen diversity. Covariance among viruses in space and time was highest for viral species sharing a vector. Temporal correlation arose from the synchronous invasion of two viruses transmitted by a shared aphid species. On the basis of our modeling and empirical results, we expect that factors external to individual hosts may affect the coinfection dynamics in other communities hosting vectored pathogens.

Phylogeny and provenance affect plant-soil feedbacks in invaded California grasslands.

Plant-soil feedbacks can affect plant community dynamics by influencing processes of coexistence or invasion, or by maintaining alternate stable states. Darwin's naturalization hypothesis suggests that phylogenetic relatedness should be a critical factor governing such feedbacks in invaded communities but is rarely considered in soil feedback studies. We investigated the effects of soil biota from experimentally established native and invaded California grassland communities on resource capture and allocation of three native and three exotic grass species, comprising three tribes, grown in the laboratory. Phylogeny was the single greatest determinant of grass biomass, root:shoot ratio, and growth rate, with presence of soil biota explaining the second greatest proportion of variance in total grass biomass. Similar trends were observed in soil collected from naturally occurring stands of native perennial and exotic annual grasses. Species of similar life history/provenance exhibited similar biomass responses to the same soil community, while more closely related species exhibited similar root:shoot ratio responses to the same soil community. Relationships between the plant community composition of a field plot and species responses to soil inoculum collected from that field plot were idiosyncratic, with many aspects of plant community structure potentially contributing to soil feedbacks. Thus, future studies should explicitly consider both phylogeny and provenance and evaluate soil feedbacks in a community setting.

Nutrient recycling affects autotroph and ecosystem stoichiometry.

Stoichiometric nutrient ratios are the consequence of myriad interacting processes, both biotic and abiotic. Theoretical explanations for autotroph stoichiometry have focused on species' nutrient requirements but have not addressed the role of nutrient availability in determining autotroph stoichiometry. Remineralization of organic N and P supplies a significant fraction of inorganic N and P to autotrophs, making nutrient recycling a potentially important process influencing autotroph stoichiometry. To quantitatively investigate the relationship between available N and P, autotroph N:P, and nutrient recycling, we analyze a stoichiometrically explicit model of autotroph growth, incorporating Michaelis-Menten-Monod nutrient uptake kinetics, Droop growth, and Liebig's law of the minimum. If autotroph growth is limited by a single nutrient, increased recycling of the limiting nutrient pushes autotrophs toward colimitation and alters both autotroph and environmental stoichiometry. We derive a steady state relationship between input stoichiometry, autotroph N:P, and the stoichiometry of organic losses that allows us to estimate the relative recycling of N to P within an ecosystem. We then estimate relative N and P recycling for a marine, an aquatic, and two terrestrial ecosystems. Preferential P recycling, in conjunction with greater relative P retention at the organismal and ecosystem levels, presents a strong case for the importance of P to biomass production across ecosystems.

Does the impact of biodiversity differ between emerging and endemic pathogens? The need to separate the concepts of hazard and risk.

Biodiversity is of critical value to human societies, but recent evidence that biodiversity may mitigate infectious-disease risk has sparked controversy among researchers. The majority of work on this topic has focused on direct assessments of the relationship between biodiversity and endemic-pathogen prevalence, without disentangling intervening mechanisms; thus study outcomes often differ, fuelling more debate. Here, we suggest two critical changes to the approach researchers take to understanding relationships between infectious disease, both endemic and emerging, and biodiversity that may help clarify sources of controversy. First, the distinct concepts of hazards versus risks need to be separated to determine how biodiversity and its drivers may act differently on each. This distinction is particularly important since it illustrates that disease emergence drivers in humans could be quite different to the general relationship between biodiversity and transmission of endemic pathogens. Second, the interactive relationship among biodiversity, anthropogenic change and zoonotic disease risk, including both direct and indirect effects, needs to be recognized and accounted for. By carefully disentangling these interactions between humans' activities and pathogen circulation in wildlife, we suggest that conservation efforts could mitigate disease risks and hazards in novel ways that complement more typical disease control efforts.This article is part of the themed issue 'Conservation, biodiversity and infectious disease: scientific evidence and policy implications'.

Seasonality and the dynamics of infectious diseases.

Seasonal variations in temperature, rainfall and resource availability are ubiquitous and can exert strong pressures on population dynamics. Infectious diseases provide some of the best-studied examples of the role of seasonality in shaping population fluctuations. In this paper, we review examples from human and wildlife disease systems to illustrate the challenges inherent in understanding the mechanisms and impacts of seasonal environmental drivers. Empirical evidence points to several biologically distinct mechanisms by which seasonality can impact host-pathogen interactions, including seasonal changes in host social behaviour and contact rates, variation in encounters with infective stages in the environment, annual pulses of host births and deaths and changes in host immune defences. Mathematical models and field observations show that the strength and mechanisms of seasonality can alter the spread and persistence of infectious diseases, and that population-level responses can range from simple annual cycles to more complex multiyear fluctuations. From an applied perspective, understanding the timing and causes of seasonality offers important insights into how parasite-host systems operate, how and when parasite control measures should be applied, and how disease risks will respond to anthropogenic climate change and altered patterns of seasonality. Finally, by focusing on well-studied examples of infectious diseases, we hope to highlight general insights that are relevant to other ecological interactions.

Spatial spread of an emerging infectious disease: conjunctivitis in House Finches.

In this paper we quantify the rate of spread of the newly emerged pathogen Mycoplasma gallisepticum of the House Finch, Carpodacus mexicanus, in its introduced range. We compare and contrast the rapid, yet decelerating, rate of spread of the pathogen with the slower, yet accelerating rate of spread of the introduced host. Comparing the rate of spread of this pathogen to pathogens in terrestrial mammalian hosts, we see that elevation and factors relating to host abundance restrict disease spread, rather than finding any major effects of discrete barriers or anthropogenic movement. We examine the role of seasonality in the rate of spread, finding that the rate and direction of disease spread relates more to seasonality in host movement than to seasonality in disease prevalence. We conclude that asymptomatic carriers are major transmitters of Mycoplasma gallisepticum into novel locations, a finding which may also be true for many other diseases, such as West Nile Virus and avian influenza.

Genetically Diverse Low Pathogenicity Avian Influenza A Virus Subtypes Co-Circulate among Poultry in Bangladesh.

Influenza virus surveillance, poultry outbreak investigations and genomic sequencing were assessed to understand the ecology and evolution of low pathogenicity avian influenza (LPAI) A viruses in Bangladesh from 2007 to 2013. We analyzed 506 avian specimens collected from poultry in live bird markets and backyard flocks to identify influenza A viruses. Virus isolation-positive specimens (n = 50) were subtyped and their coding-complete genomes were sequenced. The most frequently identified subtypes among LPAI isolates were H9N2, H11N3, H4N6, and H1N1. Less frequently detected subtypes included H1N3, H2N4, H3N2, H3N6, H3N8, H4N2, H5N2, H6N1, H6N7, and H7N9. Gene sequences were compared to publicly available sequences using phylogenetic inference approaches. Among the 14 subtypes identified, the majority of viral gene segments were most closely related to poultry or wild bird viruses commonly found in Southeast Asia, Europe, and/or northern Africa. LPAI subtypes were distributed over several geographic locations in Bangladesh, and surface and internal protein gene segments clustered phylogenetically with a diverse number of viral subtypes suggesting extensive reassortment among these LPAI viruses. H9N2 subtype viruses differed from other LPAI subtypes because genes from these viruses consistently clustered together, indicating this subtype is enzootic in Bangladesh. The H9N2 strains identified in Bangladesh were phylogenetically and antigenically related to previous human-derived H9N2 viruses detected in Bangladesh representing a potential source for human infection. In contrast, the circulating LPAI H5N2 and H7N9 viruses were both phylogenetically and antigenically unrelated to H5 viruses identified previously in humans in Bangladesh and H7N9 strains isolated from humans in China. In Bangladesh, domestic poultry sold in live bird markets carried a wide range of LPAI virus subtypes and a high diversity of genotypes. These findings, combined with the seven year timeframe of sampling, indicate a continuous circulation of these viruses in the country.

Dynamics of a novel pathogen in an avian host: Mycoplasmal conjunctivitis in house finches.

In early 1994, a novel strain of Mycoplasma gallisepticum (MG)--a poultry pathogen with a world-wide distribution--emerged in wild house finches and within 3 years had reached epidemic proportions across their eastern North American range. The ensuing epizootic resulted in a rapid decline of the host population coupled with considerable seasonal fluctuations in prevalence. To understand the dynamics of this disease system, a multi-disciplinary team composed of biologists, veterinarians, microbiologists and mathematical modelers set forth to determine factors driving and influenced by this host-pathogen system. On a broad geographic scale, volunteer observers ("citizen scientists") collected and reported data used for calculating both host abundance and disease prevalence. The scale at which this monitoring initiative was conducted is unprecedented and it has been an invaluable source of data for researchers at the Cornell Laboratory of Ornithology to track the spread and magnitude of disease both spatially and temporally. At a finer scale, localized and intensive field studies provided data used to quantify the effects of disease on host demographic parameters via capture-mark-recapture modeling, effects of host behavior on disease and vice-versa, and the biological and genetic profiles of birds with known phenotypic characteristics. To balance the field-based component of the study, experiments were conducted with finches held in captivity to describe and quantify the effects of experimental infections on hosts in both individual and social settings. The confluence of these various elements of the investigation provided the foundation for construction of a general compartmentalized epidemiological model of the dynamics of the house finch-MG system. This paper serves several purposes including (i) a basic review of the pathogen, host, and epidemic cycle; (ii) an explanation of our research strategy; (iii) a basic review of results from the diverse multi-disciplinary approaches employed; and (iv) pertinent questions relevant to this and other wildlife disease studies that require further investigation.

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.

Seasonality and wildlife disease: how seasonal birth, aggregation and variation in immunity affect the dynamics of Mycoplasma gallisepticum in house finches.

We examine the role of host seasonal breeding, host seasonal social aggregation and partial immunity in affecting wildlife disease dynamics, focusing on the dynamics of house finch conjunctivitis (Mycoplasma gallisepticum (MG) in Carpodacus mexicanus). This case study of an unmanaged emerging infectious disease provides useful insight into the important role of seasonal factors in driving ongoing disease dynamics. Seasonal breeding can force recurrent epidemics through the input of fresh susceptibles, which will clearly affect a wide variety of wildlife disease dynamics. Seasonal patterns of social aggregation and foraging behaviour could change transmission dynamics. We use latitudinal variation in the timing of breeding, and social systems to model seasonal dynamics of house finch conjunctivitis across eastern North America. We quantify the patterns of seasonal breeding, and social aggregation across a latitudinal gradient in the eastern range of the house finch, supplemented with known field and laboratory information on immunity to MG in finches. We then examine the interactions of these factors in a theoretical model of disease dynamics. We find that both forms of seasonality could explain the dynamics of the house finch-MG system, and that these factors could have important effects on the dynamics of wildlife diseases generally. In particular, while either alone is sufficient to create recurrent cycles of prevalence in a population with an endemic disease, both are required to produce the specific semi-annual pattern of disease prevalence seen in the house finch conjunctivitis system.

Experimental infection of house finches with Mycoplasma gallisepticum.

Mycoplasma gallisepticum (MG) has caused an endemic upper respiratory and ocular infection in the eastern house finch (Carpodacus mexicanus) after the epidemic first described in 1994. The disease has been studied by a number of investigators at a population level and reports describe experimental infection in group-housed MG-free house finches. Because detailed observation and evaluation of individual birds in group-housed passerines is problematic, we studied individually housed house finches that were experimentally inoculated with the finch strain of MG in a controlled environment. To accomplish this, a study was conducted spanning the period of November 2001-April 2002 with 20 MG-free (confirmed by the rapid plate agglutination assay and polymerase chain reaction [PCR] assay) eastern house finches captured in the Cayuga Basin area of central New York (USA) in the summer of 2001. After a period of acclimatization and observation (12 wk), 20 finches were inoculated with a 0.05-ml aliquot of MG (3.24 x 10(5) colony-forming units/ml) via bilateral conjunctival sac instillations. Two additional finches acted as controls and were inoculated in the same manner with preservative-free sterile saline solution. After inoculation, all finches except the controls exhibited clinical signs of conjunctivitis within 2-6 days. The progression of the disease was evaluated by several methods, including PCR, behavioral observations, and physical examination including eye scoring, body weight, and body condition index. Over a period of 21 wk, MG-infected finches developed signs of disease and recovered (80%), developed signs of disease and progressed to become chronically infected (15%), or died (5%). We hypothesize that the high survival rate and recovery of these finches after infection was associated with the use of controlled environmental conditions, acclimatization, a high plane of nutrition, and low stocking (housing) density, all of which are factors documented to be important in the outcome of MG infections in domestic poultry and other species.