How accurately can we assess zoonotic risk?

Modeling the velocity of evolving lineages and predicting dispersal patterns

Accurate estimation of the dispersal velocity or speed of evolving organisms is no mean feat. In fact, existing probabilistic models in phylogeography or spatial population genetics generally do not provide an adequate framework to define velocity in a relevant manner. For instance, the very concept of instantaneous speed simply does not exist under one of the most popular approaches that models the evolution of spatial coordinates as Brownian trajectories running along a phylogeny [30]. Here, we introduce a new family of models - the so-called "Phylogenetic Integrated Velocity" (PIV) models - that use Gaussian processes to explicitly model the velocity of evolving lineages instead of focusing on the fluctuation of spatial coordinates over time. We describe the properties of these models and show an increased accuracy of velocity estimates compared to previous approaches. Analyses of West Nile virus data in the U.S.A. indicate that PIV models provide sensible predictions of the dispersal of evolving pathogens at a one-year time horizon. These results demonstrate the feasibility and relevance of predictive phylogeography in monitoring epidemics in time and space.

Pandemic preparedness: On the efficacy of non-pharmaceutical interventions in COVID-19 and about approaches to predict future pandemic viruses

With three major viral pandemics over the last 100 years, namely the Spanish flu, AIDS and COVID-19 each claiming many millions of lives, pandemic preparedness has become an important issue for public health. The economic, social and political consequences of the upheaval caused by such pandemics also represent a major challenge for governments with respect to sustainable development goals. The field of pandemic preparedness is vast and the current article can only address selected aspects. The article looks first backwards and addresses the question of the efficacy of non-pharmaceutical interventions (NPI) on the trajectory of the COVID-19 pandemic. The article looks then forward by asking to what extent viral candidates for future pandemics can be predicted by virome analyses from metagenome and transcriptome sequencing, by focusing on the virome from specific animal species and using ecological and epidemiological data about spillover viral infections in veterinary and human medicine. As a comprehensive overview on pandemic preparedness is beyond the capacity of a single reviewer, only selected topics will be discussed using recent key scientific publications. Since COVID-19 has not run its course, a computational program able to predict the future evolution of SARS-CoV-2 is mentioned that could assist proactive mRNA vaccine developments against possible future variants of concern. Ending the COVID-19 epidemic necessitates mucosal vaccines that can suppress the transmission of SARS-CoV-2 and therefore this article closes by discussing a promising and versatile protein nanoparticle experimental vaccine approach for inhalation that does not depend on needles nor a cold chain for distribution.

Temporal Dynamics, Discovery, and Emergence of Human-Transmissible RNA Viruses

Transmissibility, the ability to spread within host populations, is a prerequisite for a pathogen to have epidemic or pandemic potential. Here, we estimate the phylogenies of human infectivity and transmissibility using 1,408 genome sequences from 743 distinct RNA virus species/types in 59 genera. By repeating this analysis using data sets censored by virus discovery date, we explore how temporal changes in the known diversity of RNA viruses-especially recent increases in recognized nonhuman viruses-have altered these phylogenies. Over time, we find significant increases in the proportion of RNA virus genera estimated to have a nonhuman-infective ancestral state, in the fraction of distinct human virus lineages that are purely human-transmissible or strictly zoonotic (compared to mixed lineages), and in the number of human viruses with nearest relatives known not to infect humans. Our results are consistent with viruses that are capable of spreading in human populations commonly emerging from a nonhuman reservoir. This is more likely in lineages that already contain human-transmissible viruses but is rare in lineages that contain only strictly zoonotic viruses.

High risk of bat bites in an indigenous village in Brazil: Warning of the re-emergence of rabies among the Maxakali People

Bat-mediated human rabies is a viral zoonotic disease that poses a serious threat to the public health of traditional peoples, especially indigenous populations that maintain primitive cultural and social habits, such as the Maxakali ethnic group, located in the southeastern region of Brazil. The sociocultural habit of this population led to the emergence between April and May 2022 of the viral spillover of rabies transmitted by bats, which decimated the lives of four children from this population who maintained contact with this animal as a recreational practice. Because the vampire bats Desmodus rotundus have exceptional ecology and social characteristics that can have important effects on the dynamics of viral dispersion in this indigenous population, I present the dynamics of contact between native children and the bat and the meaning of this relationship, which involves ritualistic and recreational significance. As important as knowing the reasons for this practice is discussing some intrinsic and extrinsic factors that imply risks that intensify the vulnerability of this population to the transmission of the rabies virus at any time. In view of this, I warn of the need to adopt efficient strategies to mitigate the risks of a new emergency in this region. Although emergency containment measures were carried out during the critical period of the outbreak, such animal and environmental control actions must become routine programmatic and structuring interventions. Essential for rabies surveillance in this population is to develop culturally adapted interethnic health education campaigns to guarantee the accessibility of the Maxakali indigenous people to the content taught, so that any attempt at domestication, captivity and recreational practices with bats of any species is discouraged, thus avoiding a possible re-emergence of this anthropozoonosis that has impacted not only the epidemiological scenario in this region, but throughout Brazil, and also throughout Latin America.

Host phylogeny shapes viral transmission networks in an island ecosystem

Virus transmission between host species underpins disease emergence. Both host phylogenetic relatedness and aspects of their ecology, such as species interactions and predator-prey relationships, may govern rates and patterns of cross-species virus transmission and hence zoonotic risk. To address the impact of host phylogeny and ecology on virus diversity and evolution, we characterized the virome structure of a relatively isolated island ecological community in Fiordland, New Zealand, that are linked through a food web. We show that phylogenetic barriers that inhibited cross-species virus transmission occurred at the level of host phyla (between the Chordata, Arthropoda and Streptophyta) as well as at lower taxonomic levels. By contrast, host ecology, manifest as predator-prey interactions and diet, had a smaller influence on virome composition, especially at higher taxonomic levels. The virus-host community comprised a 'small world' network, in which hosts with a high diversity of viruses were more likely to acquire new viruses, and generalist viruses that infect multiple hosts were more likely to infect additional species compared to host specialist viruses. Such a highly connected ecological community increases the likelihood of cross-species virus transmission, particularly among closely related species, and suggests that host generalist viruses present the greatest risk of disease emergence.

Host traits shape virome composition and virus transmission in wild small mammals

Bats, rodents, and shrews are the most important animal sources of human infectious diseases. However, the evolution and transmission of viruses among them remain largely unexplored. Through the meta-transcriptomic sequencing of internal organ and fecal samples from 2,443 wild bats, rodents, and shrews sampled from four Chinese habitats, we identified 669 viruses, including 534 novel viruses, thereby greatly expanding the mammalian virome. Our analysis revealed high levels of phylogenetic diversity, identified cross-species virus transmission events, elucidated virus origins, and identified cases of invertebrate viruses in mammalian hosts. Host order and sample size were the most important factors impacting virome composition and patterns of virus spillover. Shrews harbored a high richness of viruses, including many invertebrate-associated viruses with multi-organ distributions, whereas rodents carried viruses with a greater capacity for host jumping. These data highlight the remarkable diversity of mammalian viruses in local habitats and their ability to emerge in new hosts.

Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long-term rodent datasets

The increasing frequency and cost of zoonotic disease emergence due to global change have led to calls for the primary surveillance of wildlife. This should be facilitated by the ready availability of remotely sensed environmental data, given the importance of the environment in determining infectious disease dynamics. However, there has been little evaluation of the temporal predictiveness of remotely sensed environmental data for infection reservoirs in vertebrate hosts due to a deficit of corresponding high-quality long-term infection datasets. Here we employ two unique decade-spanning datasets for assemblages of infectious agents, including zoonotic agents, in rodents in stable habitats. Such stable habitats are important, as they provide the baseline sets of pathogens for the interactions within degrading habitats that have been identified as hotspots for zoonotic emergence. We focus on the enhanced vegetation index (EVI), a measure of vegetation greening that equates to primary productivity, reasoning that this would modulate infectious agent populations via trophic cascades determining host population density or immunocompetence. We found that EVI, in analyses with data standardised by site, inversely predicted more than one-third of the variation in an index of infectious agent total abundance. Moreover, in bipartite host occupancy networks, weighted network statistics (connectance and modularity) were linked to total abundance and were also predicted by EVI. Infectious agent abundance and, perhaps, community structure are likely to influence infection risk and, in turn, the probability of transboundary emergence. Thus, the present results, which were consistent in disparate forest and desert systems, provide proof-of-principle that within-site fluctuations in satellite-derived greenness indices can furnish useful forecasting that could focus primary surveillance. In relation to the well-documented global greening trend of recent decades, the present results predict declining infection burden in wild vertebrates in stable habitats; but if greening trends were to be reversed, this might magnify the already upwards trend in zoonotic emergence.

Host specificity shapes fish viromes across lakes on an isolated remote island

Fish viromes often provide insights into the origin and evolution of viruses affecting tetrapods, including those associated with imporant human diseases. However, despite fish being the most diverse vertebrate group, their viruses are still understudied. We investigated the viromes of fish on Chatham Island (Rēkohu), a geographically isolated island housing 9% of New Zealand's threatened endemic fish species. Using metatranscriptomics, we analyzed samples from seven host species across 16 waterbodies. We identified 19 fish viruses, including 16 potentially novel species, expanding families such as the Coronaviridae, Hantaviridae, Poxviridae, and the recently proposed Tosoviridae. Surprisingly, virome composition was not influenced by the ecological factors measured and smelt (Retropinna retropinna) viromes were consistent across lakes despite differences in host life history, seawater influence, and community richness. Overall, fish viromes across Rēkohu were highly diverse and revealed a long history of co-divergence between host and virus despite their unique and geographically isolated ecosystem.

Praemonitus praemunitus: can we forecast and prepare for future viral disease outbreaks?

Understanding the origins of past and present viral epidemics is critical in preparing for future outbreaks. Many viruses, including SARS-CoV-2, have led to significant consequences not only due to their virulence, but also because we were unprepared for their emergence. We need to learn from large amounts of data accumulated from well-studied, past pandemics and employ modern informatics and therapeutic development technologies to forecast future pandemics and help minimize their potential impacts. While acknowledging the complexity and difficulties associated with establishing reliable outbreak predictions, herein we provide a perspective on the regions of the world that are most likely to be impacted by future outbreaks. We specifically focus on viruses with epidemic potential, namely SARS-CoV-2, MERS-CoV, DENV, ZIKV, MAYV, LASV, noroviruses, influenza, Nipah virus, hantaviruses, Oropouche virus, MARV, and Ebola virus, which all require attention from both the public and scientific community to avoid societal catastrophes like COVID-19. Based on our literature review, data analysis, and outbreak simulations, we posit that these future viral epidemics are unavoidable, but that their societal impacts can be minimized by strategic investment into basic virology research, epidemiological studies of neglected viral diseases, and antiviral drug discovery.

Genome mining shows that retroviruses are pervasively invading vertebrate genomes

Endogenous retroviruses (ERVs) record past retroviral infections, providing molecular archives for interrogating the evolution of retroviruses and retrovirus-host interaction. However, the vast majority of ERVs are not active anymore due to various disruptive mutations, and ongoing retroviral invasion of vertebrate genomes has been rarely documented. Here we analyze genomics data from 2004 vertebrates for mining invading ERVs (ERVi). We find that at least 412 ERVi elements representing 217 viral operational taxonomic units are invading the genomes of 123 vertebrates, 18 of which have been assessed to be threatened species. Our results reveal an unexpected prevalence of ongoing retroviral invasion in vertebrates and expand the diversity of retroviruses recently circulating in the wild. We characterize the pattern and nature of ERVi in the historical and biogeographical context of their hosts, for instance, the generation of model organisms, sympatric speciation, and domestication. We suspect that these ERVi are relevant to conservation of threatened species, zoonoses in the wild, and emerging infectious diseases in humans.

Emerging zoonotic diseases and COVID-19 pandemic: global Perspective and Indian Scenario

The current coronavirus disease 2019 (COVID-19) pandemic is one example of the scores of zoonotic diseases responsible for various outbreaks resulting in the deaths of millions of people for centuries. The COVID-19 pandemic has broken the age-old healthcare infrastructure and led to utter chaos. In the shadow of this pandemic, other zoonotic infections like the nipah virus, monkeypox, and langya virus, to name a few, have been neglected. Hence, outbreaks caused by such zoonotic viruses are rising in their endemic areas, like the Indian subcontinent. The mortality and morbidity due to such zoonoses are greater than usual due to the shortage of healthcare professionals caused by the COVID-19 crisis. Due to the lack of vaccines and therapeutics directed against this viral infection, treatment of patients is limited to supportive management and prevention, making preparedness for these potential zoonotic viral outbreaks essential. This paper highlights some of these zoonotic infections, which perpetuated and wreaked havoc while the world was occupied with containing the COVID-19 pandemic.

Investigating and combatting the key drivers of viral zoonoses in Africa: an analysis of eight epidemics

Investigating the interplay of factors that result in a viral zoonotic outbreak is difficult, though it is increasingly important. As anthropogenic influences shift the delicate balance of ecosystems, new zoonoses emerge in humans. Sub-Saharan Africa is a notable hotspot for zoonotic disease due to abundant competent mammalian reservoir hosts. Furthermore, poverty, corruption, and an overreliance on natural resources play considerable roles in depleting biological resources, exacerbating the population's susceptibility. Unsurprisingly, viral zoonoses have emerged in Africa, including HIV/AIDS, Ebola, Avian influenza, Lassa fever, Zika, and Monkeypox. These diseases are among the principal causes of death in endemic areas. Though typically distinct in their manifestations, viral zoonoses are connected by underlying, definitive factors. This review summarises vital findings on viral zoonoses in Africa using nine notable case studies as a benchmark for future studies. We discuss the importance of ecological recuperation and protection as a central strategy to control zoonotic diseases. Emphasis was made on moderating key drivers of zoonotic diseases to forestall future pandemics. This is in conjunction with attempts to redirect efforts from reactive to pre-emptive through a multidisciplinary "one health" approach.

Predicting zoonotic potential of viruses: where are we?

The prospect of identifying high-risk viruses and designing interventions to pre-empt their emergence into human populations is enticing, but controversial, particularly when used to justify large-scale virus discovery initiatives. We review the current state of these efforts, identifying three broad classes of predictive models that have differences in data inputs that define their potential utility for triaging newly discovered viruses for further investigation. Prospects for model predictions of public health risk to guide preparedness depend not only on computational improvements to algorithms, but also on more efficient data generation in laboratory, field and clinical settings. Beyond public health applications, efforts to predict zoonoses provide unique research value by creating generalisable understanding of the ecological and evolutionary factors that promote viral emergence.

Network embedding unveils the hidden interactions in the mammalian virome

Predicting host-virus interactions is fundamentally a network science problem. We develop a method for bipartite network prediction that combines a recommender system (linear filtering) with an imputation algorithm based on low-rank graph embedding. We test this method by applying it to a global database of mammal-virus interactions and thus show that it makes biologically plausible predictions that are robust to data biases. We find that the mammalian virome is under-characterized anywhere in the world. We suggest that future virus discovery efforts could prioritize the Amazon Basin (for its unique coevolutionary assemblages) and sub-Saharan Africa (for its poorly characterized zoonotic reservoirs). Graph embedding of the imputed network improves predictions of human infection from viral genome features, providing a shortlist of priorities for laboratory studies and surveillance. Overall, our study indicates that the global structure of the mammal-virus network contains a large amount of information that is recoverable, and this provides new insights into fundamental biology and disease emergence.

Current research and future directions for realizing the ideal One-Health approach: A summary of key-informant interviews in Japan and a literature review

The COVID-19 pandemic has highlighted the importance of the One Health (OH) approach, which considers the health of humans, animals, and the environment in preventing future pandemics. A wide range of sustainable interdisciplinary collaborations are required to truly fulfill the purpose of the OH approach. It is well-recognized, however, that such collaborations are challenging. In this study, we undertook key-informant interviews with a panel of stakeholders from Japan to identify their perceived needs and challenges related to OH research. This panel included scientists, government officials, journalists, and industry stakeholders. By combining a thematic analysis of these interviews and a literature review, we summarized two key themes pertinent to the effective implementation of OH research: types of required research and systems to support that research. As a technological issue, interviewees suggested the importance of research and development of methodologies that can promote the integration and collaboration of research fields that are currently fragmented. An example of such a methodology would allow researchers to obtain high-resolution metadata (e.g. ecological and wildlife data) with high throughput and then maximize the use of the obtained metadata in research, such as in environmental DNA analysis, database construction, or the use of computational algorithms to find novel viral genomes. In terms of systems surrounding OH research, some interviewees stressed the importance of creating a sustainable research system, such as one that has continuous budget support and allows researchers to pursue their academic careers and interests. These perceptions and challenges held by Japanese stakeholders may be common to others around the world. We hope this review will encourage more researchers and others to work together to create a resilient society against future pandemics.

Large-scale investigation of zoonotic viruses in the era of high-throughput sequencing

Zoonotic diseases considerably impact public health and socioeconomics. RNA viruses reportedly caused approximately 94% of zoonotic diseases documented from 1990 to 2010, emphasizing the importance of investigating RNA viruses in animals. Furthermore, it has been estimated that hundreds of thousands of animal viruses capable of infecting humans are yet to be discovered, warning against the inadequacy of our understanding of viral diversity. High-throughput sequencing (HTS) has enabled the identification of viral infections with relatively little bias. Viral searches using both symptomatic and asymptomatic animal samples by HTS have revealed hidden viral infections. This review introduces the history of viral searches using HTS, current analytical limitations, and future potentials. We primarily summarize recent research on large-scale investigations on viral infections reusing HTS data from public databases. Furthermore, considering the accumulation of uncultivated viruses, we discuss current studies and challenges for connecting viral sequences to their phenotypes using various approaches: performing data analysis, developing predictive modeling, or implementing high-throughput platforms of virological experiments. We believe that this article provides a future direction in large-scale investigations of potential zoonotic viruses using the HTS technology.

Rodent trapping studies as an overlooked information source for understanding endemic and novel zoonotic spillover

Rodents, a diverse, globally distributed and ecologically important order of mammals are nevertheless important reservoirs of known and novel zoonotic pathogens. Ongoing anthropogenic land use change is altering these species' abundance and distribution, which among zoonotic host species may increase the risk of zoonoses spillover events. A better understanding of the current distribution of rodent species is required to guide attempts to mitigate against potentially increased zoonotic disease hazard and risk. However, available species distribution and host-pathogen association datasets (e.g. IUCN, GBIF, CLOVER) are often taxonomically and spatially biased. Here, we synthesise data from West Africa from 127 rodent trapping studies, published between 1964-2022, as an additional source of information to characterise the range and presence of rodent species and identify the subgroup of species that are potential or known pathogen hosts. We identify that these rodent trapping studies, although biased towards human dominated landscapes across West Africa, can usefully complement current rodent species distribution datasets and we calculate the discrepancies between these datasets. For five regionally important zoonotic pathogens (Arenaviridae spp., Borrelia spp., Lassa mammarenavirus, Leptospira spp. and Toxoplasma gondii), we identify host-pathogen associations that have not been previously reported in host-association datasets. Finally, for these five pathogen groups, we find that the proportion of a rodent hosts range that have been sampled remains small with geographic clustering. A priority should be to sample rodent hosts across a greater geographic range to better characterise current and future risk of zoonotic spillover events. In the interim, studies of spatial pathogen risk informed by rodent distributions must incorporate a measure of the current sampling biases. The current synthesis of contextually rich rodent trapping data enriches available information from IUCN, GBIF and CLOVER which can support a more complete understanding of the hazard of zoonotic spillover events.

Bioinformatics approaches for unveiling virus-host interactions

The coronavirus disease-2019 (COVID-19) pandemic has elucidated major limitations in the capacity of medical and research institutions to appropriately manage emerging infectious diseases. We can improve our understanding of infectious diseases by unveiling virus-host interactions through host range prediction and protein-protein interaction prediction. Although many algorithms have been developed to predict virus-host interactions, numerous issues remain to be solved, and the entire network remains veiled. In this review, we comprehensively surveyed algorithms used to predict virus-host interactions. We also discuss the current challenges, such as dataset biases toward highly pathogenic viruses, and the potential solutions. The complete prediction of virus-host interactions remains difficult; however, bioinformatics can contribute to progress in research on infectious diseases and human health.

Enveloped viruses show increased propensity to cross-species transmission and zoonosis

The transmission of viruses between different host species is a major source of emerging diseases and is of particular concern in the case of zoonotic transmission from mammals to humans. Several zoonosis risk factors have been identified, but it is currently unclear which viral traits primarily determine this process as previous work has focused on a few hundred viruses that are not representative of actual viral diversity. Here, we investigate fundamental virological traits that influence cross-species transmissibility and zoonotic propensity by interrogating a database of over 12,000 mammalian virus-host associations. Our analysis reveals that enveloped viruses tend to infect more host species and are more likely to be zoonotic than nonenveloped viruses, while other viral traits such as genome composition, structure, size, or the viral replication compartment play a less obvious role. This contrasts with the previous notion that viral envelopes did not significantly impact or even reduce zoonotic risk and should help better prioritize outbreak prevention efforts. We suggest several mechanisms by which viral envelopes could promote cross-species transmissibility, including structural flexibility of receptor-binding proteins and evasion of viral entry barriers.

The one health perspective to improve environmental surveillance of zoonotic viruses: lessons from COVID-19 and outlook beyond

The human population has doubled in the last 50 years from about 3.7 billion to approximately 7.8 billion. With this rapid expansion, more people live in close contact with wildlife, livestock, and pets, which in turn creates increasing opportunities for zoonotic diseases to pass between animals and people. At present an estimated 75% of all emerging virus-associated infectious diseases possess a zoonotic origin, and outbreaks of Zika, Ebola and COVID-19 in the past decade showed their huge disruptive potential on the global economy. Here, we describe how One Health inspired environmental surveillance campaigns have emerged as the preferred tools to monitor human-adjacent environments for known and yet to be discovered infectious diseases, and how they can complement classical clinical diagnostics. We highlight the importance of environmental factors concerning interactions between animals, pathogens and/or humans that drive the emergence of zoonoses, and the methodologies currently proposed to monitor them-the surveillance of wastewater, for example, was identified as one of the main tools to assess the spread of SARS-CoV-2 by public health professionals and policy makers during the COVID-19 pandemic. One-Health driven approaches that facilitate surveillance, thus harbour the potential of preparing humanity for future pandemics caused by aetiological agents with environmental reservoirs. Via the example of COVID-19 and other viral diseases, we propose that wastewater surveillance is a useful complement to clinical diagnosis as it is centralized, robust, cost-effective, and relatively easy to implement.

Implementing a school-based HIV prevention program during public health emergencies: lessons learned in The Bahamas

Background

Natural disasters and public health crises can disrupt communities’ capacities to implement important public health programs. A nationwide implementation of an evidence-based HIV prevention program, Focus on Youth in The Caribbean (FOYC) and Caribbean Informed Parents and Children Together (CImPACT), in The Bahamas was disrupted by Hurricane Dorian and the COVID-19 pandemic, especially in its more remote, Family Islands. We explored the teacher- and school-level factors that affected implementation of the program in these islands during those disruptions.

Methods

Data were collected from 47 Grade 6 teachers and 984 students in 34 government elementary schools during the 2020–2021 school year. Teachers completed a pre-implementation questionnaire to record their characteristics and perceptions that might affect their implementation fidelity and an annual program training workshop. School coordinators and high-performing teachers acting as mentors received additional training to provide teachers with monitoring, feedback, and additional support. Teachers submitted data on their completion of the 9 sessions and 35 core activities of FOYC + CImPACT. The fidelity outcomes were the number of sessions and core activities taught by teachers.

Results

On average, teachers taught 60% of sessions and 53% of core activities. Teachers with “very good” school coordinators (34% of teachers) taught more activities than those with “satisfactory” (43%) or no (34%) school coordinator (27.5 vs. 16.8 vs. 14.8, F = 12.86, P < 0.001). Teachers who had attended online training or both online and in-person training taught more sessions (6.1 vs. 6.2 vs. 3.6, F = 4.76, P < 0.01) and more core activities (21.1 vs. 20.8 vs. 12.6, F = 3.35, P < 0.05) than those who received no training. Teachers’ implementation was associated with improved student outcomes (preventive reproductive health skills, self-efficacy, and intention).

Conclusions

The Hurricane Dorian and the COVID-19 pandemic greatly disrupted education in The Bahamas Family Islands and affected implementation of FOYC + CImPACT. However, we identified several strategies that supported teachers’ implementation following these events. Teacher training and implementation monitoring increased implementation fidelity despite external challenges, and students achieved the desired learning outcomes. These strategies can better support teachers’ implementation of school-based interventions during future crises.

RNA Viruses, Pandemics and Anticipatory Preparedness

RNA viruses are likely to cause future pandemics and therefore we must create and organize a deep knowledge of these viruses to prevent and manage this risk. Assuming prevention will fail, at least once, we must be prepared to manage a future pandemic using all resources available. We emphasize the importance of having safe vaccine candidates and safe broad-spectrum antivirals ready for rapid clinical translation. Additionally, we must have similar tools to be ready for outbreaks of RNA viruses among animals and plants. Finally, similar coordination should be accomplished for other pathogens with pandemic potential.

Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors

Zoonotic diseases spread through pathogens-infected animal carriers. In the case of Ebola Virus Disease (EVD), evidence supports that the main carriers are fruit bats and non-human primates. Further, EVD spread is a multi-factorial problem that depends on sociodemographic and economic (SDE) factors. Here we inquire into this phenomenon and aim at determining, quantitatively, the Ebola spillover infection exposure map and try to link it to SDE factors. To that end, we designed and conducted a survey in Sierra Leone and implement a pipeline to analyze data using regression and machine learning techniques. Our methodology is able (1) to identify the features that are best predictors of an individual’s tendency to partake in behaviors that can expose them to Ebola infection, (2) to develop a predictive model about the spillover risk statistics that can be calibrated for different regions and future times, and (3) to compute a spillover exposure map for Sierra Leone. Our results and conclusions are relevant to identify the regions in Sierra Leone at risk of EVD spillover and, consequently, to design and implement policies for an effective deployment of resources (e.g., drug supplies) and other preventative measures (e.g., educational campaigns).

The Ecology of Viral Emergence

The coronavirus disease 2019 (COVID-19) pandemic has had a profound impact on human health, economic well-being, and societal function. It is essential that we use this generational experience to better understand the processes that underpin the emergence of COVID-19 and other zoonotic diseases. Herein, I review the mechanisms that determine why and how viruses emerge in new hosts, as well as the barriers to this process. I show that traditional studies of virus emergence have an inherent anthropocentric bias, with disease in humans considered the inevitable outcome of virus emergence, when in reality viruses are integral components of a global ecosystem characterized by continual host jumping with humans also transmitting their viruses to other animals. I illustrate these points using coronaviruses, including severe acute respiratory syndrome coronavirus 2, as a case study. I also outline the potential steps that can be followed to help mitigate and prevent future pandemics, with combating climate change a central component. Expected final online publication date for the Annual Review of Virology, Volume 9 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Bats host the most virulent-but not the most dangerous-zoonotic viruses

SignificanceThe clear need to mitigate zoonotic risk has fueled increased viral discovery in specific reservoir host taxa. We show that a combination of viral and reservoir traits can predict zoonotic virus virulence and transmissibility in humans, supporting the hypothesis that bats harbor exceptionally virulent zoonoses. However, pandemic prevention requires thinking beyond zoonotic capacity, virulence, and transmissibility to consider collective "burden" on human health. For this, viral discovery targeting specific reservoirs may be inefficient as death burden correlates with viral, not reservoir, traits, and depends on context-specific epidemiological dynamics across and beyond the human-animal interface. These findings suggest that longitudinal studies of viral dynamics in reservoir and spillover host populations may offer the most effective strategy for mitigating zoonotic risk.

Bats host the most virulent-but not the most dangerous-zoonotic viruses

SignificanceThe clear need to mitigate zoonotic risk has fueled increased viral discovery in specific reservoir host taxa. We show that a combination of viral and reservoir traits can predict zoonotic virus virulence and transmissibility in humans, supporting the hypothesis that bats harbor exceptionally virulent zoonoses. However, pandemic prevention requires thinking beyond zoonotic capacity, virulence, and transmissibility to consider collective "burden" on human health. For this, viral discovery targeting specific reservoirs may be inefficient as death burden correlates with viral, not reservoir, traits, and depends on context-specific epidemiological dynamics across and beyond the human-animal interface. These findings suggest that longitudinal studies of viral dynamics in reservoir and spillover host populations may offer the most effective strategy for mitigating zoonotic risk.

Biological invasions facilitate zoonotic disease emergences

Outbreaks of zoonotic diseases are accelerating at an unprecedented rate in the current era of globalization, with substantial impacts on the global economy, public health, and sustainability. Alien species invasions have been hypothesized to be important to zoonotic diseases by introducing both existing and novel pathogens to invaded ranges. However, few studies have evaluated the generality of alien species facilitating zoonoses across multiple host and parasite taxa worldwide. Here, we simultaneously quantify the role of 795 established alien hosts on the 10,473 zoonosis events across the globe since the 14^th century. We observe an average of ~5.9 zoonoses per alien zoonotic host. After accounting for species-, disease-, and geographic-level sampling biases, spatial autocorrelation, and the lack of independence of zoonosis events, we find that the number of zoonosis events increase with the richness of alien zoonotic hosts, both across space and through time. We also detect positive associations between the number of zoonosis events per unit space and climate change, land-use change, biodiversity loss, human population density, and PubMed citations. These findings suggest that alien host introductions have likely contributed to zoonosis emergences throughout recent history and that minimizing future zoonotic host species introductions could have global health benefits.

Alien species invasions are thought to be important to zoonotic diseases through the introduction of both existing and novel pathogens to invaded ranges. Using data from 795 established alien animals and 10,473 zoonosis events worldwide, this study examines the role of alien zoonotic hosts on zoonosis emergences after accounting for climate, propagule pressure, global change and sampling bias.

COVID-19-lessons for zoonotic disease

Disease emergence is driven by human-animal contact in a global viral ecosystem.

Animal alphacoronaviruses found in human patients with acute respiratory illness in different countries

Here we review the existing evidence of animal alphacoronaviruses (Alphacoronavirus 1 species) circulating in human patients with acute respiratory illness. Thus far, the viruses similar to canine, feline and porcine alphacoronaviruses (including the most recent CCoV-HuPn-2018 and HuCCoV_Z19) have been detected in humans in Haiti, Malaysia, Thailand, and USA. The available data suggest that these viruses emerged in different geographic locations independently and have circulated in humans for at least 20 years. Additional studies are needed to investigate their prevalence and disease impact.

Selected Livestock-Associated Zoonoses as a Growing Challenge for Public Health

The aim of this paper is to review the most significant livestock-associated zoonoses. Human and animal health are intimately connected. This idea has been known for more than a century but now it has gained special importance because of the increasing threat from zoonoses. Zoonosis is defined as any infection naturally transmissible from vertebrate animals to humans. As the frequency and prevalence of zoonotic diseases increase worldwide, they become a real threat to public health. In addition, many of the newly discovered diseases have a zoonotic origin. Due to globalization and urbanization, some of these diseases have already spread all over the world, caused by the international flow of goods, people, and animals. However, special attention should be paid to farm animals since, apart from the direct contact, humans consume their products, such as meat, eggs, and milk. Therefore, zoonoses such as salmonellosis, campylobacteriosis, tuberculosis, swine and avian influenza, Q fever, brucellosis, STEC infections, and listeriosis are crucial for both veterinary and human medicine. Consequently, in the suspicion of any zoonoses outbreak, the medical and veterinary services should closely cooperate to protect the public health.

Eroding norms over release of self-spreading viruses

Risky research on lab-modified self-spreading viruses has yet to present credible paths to upsides.

Diversity and evolution of the animal virome

The COVID-19 pandemic has given the study of virus evolution and ecology new relevance. Although viruses were first identified more than a century ago, we likely know less about their diversity than that of any other biological entity. Most documented animal viruses have been sampled from just two phyla - the Chordata and the Arthropoda - with a strong bias towards viruses that infect humans or animals of economic and social importance, often in association with strong disease phenotypes. Fortunately, the recent development of unbiased metagenomic next-generation sequencing is providing a richer view of the animal virome and shedding new light on virus evolution. In this Review, we explore our changing understanding of the diversity, composition and evolution of the animal virome. We outline the factors that determine the phylogenetic diversity and genomic structure of animal viruses on evolutionary timescales and show how this impacts assessment of the risk of disease emergence in the short term. We also describe the ongoing challenges in metagenomic analysis and outline key themes for future research. A central question is how major events in the evolutionary history of animals, such as the origin of the vertebrates and periodic mass extinction events, have shaped the diversity and evolution of the viruses they carry.

Evolution of RNA sensing receptors in birds

Birds are important hosts for many RNA viruses, including influenza A virus, Newcastle disease virus, West Nile virus and coronaviruses. Innate defense against RNA viruses in birds involves detection of viral RNA by pattern recognition receptors. Several receptors of different classes are involved, such as endosomal toll-like receptors and cytoplasmic retinoic acid-inducible gene I-like receptors, and their downstream adaptor proteins. The function of these receptors and their antagonism by viruses is well established in mammals; however, this has received less attention in birds. These receptors have been characterized in a few bird species, and the completion of avian genomes will permit study of their evolution. For each receptor, functional work has established ligand specificity and activation by viral infection. Engagement of adaptors, regulation by modulators and the supramolecular organization of proteins required for activation are incompletely understood in both mammals and birds. These receptors bind conserved nucleic acid agonists such as single- or double-stranded RNA and generally show purifying selection, particularly the ligand binding regions. However, in birds, these receptors and adaptors differ between species, and between individuals, suggesting that they are under selection for diversification over time. Avian receptors and signalling pathways, like their mammalian counterparts, are targets for antagonism by a variety of viruses, intent on escape from innate immune responses.

Lessons from a pandemic

Several interventions have been used around the world trying to contain the SARS-CoV-2 pandemic, such as quarantine, prohibition of mass demonstrations, isolation of sick people, tracing of virus carriers, semi-containment, promotion of barrier gestures, development of rapid self-tests and vaccines among others. We propose a simple model to evaluate the potential impact of such interventions. A model for the reproduction number of an infectious disease including three main contexts of infection (indoor mass events, public indoor activities and household) and seven parameters is considered. We illustrate how these parameters could be obtained from the literature or from expert assumptions, and we apply the model to describe 20 scenarios that can typically occur during the different phases of a pandemic. This model provides a useful framework for better understanding and communicating the effects of different (combinations of) possible interventions, while encouraging constant updating of expert assumptions to better match reality. This simple approach will bring more transparency and public support to help governments to think, decide, evaluate and adjust what to do during a pandemic.

Mammal virus diversity estimates are unstable due to accelerating discovery effort

Host-virus association data underpin research into the distribution and eco-evolutionary correlates of viral diversity and zoonotic risk across host species. However, current knowledge of the wildlife virome is inherently constrained by historical discovery effort, and there are concerns that the reliability of ecological inference from host-virus data may be undermined by taxonomic and geographical sampling biases. Here, we evaluate whether current estimates of host-level viral diversity in wild mammals are stable enough to be considered biologically meaningful, by analysing a comprehensive dataset of discovery dates of 6571 unique mammal host-virus associations between 1930 and 2018. We show that virus discovery rates in mammal hosts are either constant or accelerating, with little evidence of declines towards viral richness asymptotes, even in highly sampled hosts. Consequently, inference of relative viral richness across host species has been unstable over time, particularly in bats, where intensified surveillance since the early 2000s caused a rapid rearrangement of species' ranked viral richness. Our results illustrate that comparative inference of host-level virus diversity across mammals is highly sensitive to even short-term changes in sampling effort. We advise caution to avoid overinterpreting patterns in current data, since it is feasible that an analysis conducted today could draw quite different conclusions than one conducted only a decade ago.

Challenges in modelling the dynamics of infectious diseases at the wildlife-human interface

The Covid-19 pandemic is of zoonotic origin, and many other emerging infections of humans have their origin in an animal host population. We review the challenges involved in modelling the dynamics of wildlife–human interfaces governing infectious disease emergence and spread. We argue that we need a better understanding of the dynamic nature of such interfaces, the underpinning diversity of pathogens and host–pathogen association networks, and the scales and frequencies at which environmental conditions enable spillover and host shifting from animals to humans to occur. The major drivers of the emergence of zoonoses are anthropogenic, including the global change in climate and land use. These, and other ecological processes pose challenges that must be overcome to counterbalance pandemic risk. The development of more detailed and nuanced models will provide better tools for analysing and understanding infectious disease emergence and spread.

The science of the host-virus network

Better methods to predict and prevent the emergence of zoonotic viruses could support future efforts to reduce the risk of epidemics. We propose a network science framework for understanding and predicting human and animal susceptibility to viral infections. Related approaches have so far helped to identify basic biological rules that govern cross-species transmission and structure the global virome. We highlight ways to make modelling both accurate and actionable, and discuss the barriers that prevent researchers from translating viral ecology into public health policies that could prevent future pandemics.

The future of zoonotic risk prediction

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

Microbial Ecology and Evolution Are Essential for Understanding Pandemics

Ecology and evolution, especially of microbes, have never been more relevant than in our global fight against SARS-CoV-2, the virus that causes COVID-19. Understanding how populations of SARS-CoV-2 grow, disperse, and evolve is of critical importance to managing the COVID-19 pandemic, and these questions are fundamentally ecological and evolutionary in nature. We compiled data from bioRxiv and medRxiv preprint abstracts and US National Institutes of Health Research Project grant abstracts to visualize the impact that the pivot to COVID-19 research has had on the study of microbes across biological disciplines. Finding that the pivot appears weaker in ecology and evolutionary biology than in other areas of biology, we discuss why the ecology and evolution of microbes, both pathogenic and otherwise, need renewed attention and investment going forward.

Genomic signatures for predicting the zoonotic potential of novel viruses

Powered by metagenomics, viral discovery is outpacing our capacity for the downstream characterization needed to fully assess zoonotic potential. A study published in PLOS Biology uses machine learning to prioritize novel viruses based only on genomic signatures.

Identifying and prioritizing potential human-infecting viruses from their genome sequences

Determining which animal viruses may be capable of infecting humans is currently intractable at the time of their discovery, precluding prioritization of high-risk viruses for early investigation and outbreak preparedness. Given the increasing use of genomics in virus discovery and the otherwise sparse knowledge of the biology of newly discovered viruses, we developed machine learning models that identify candidate zoonoses solely using signatures of host range encoded in viral genomes. Within a dataset of 861 viral species with known zoonotic status, our approach outperformed models based on the phylogenetic relatedness of viruses to known human-infecting viruses (area under the receiver operating characteristic curve [AUC] = 0.773), distinguishing high-risk viruses within families that contain a minority of human-infecting species and identifying putatively undetected or so far unrealized zoonoses. Analyses of the underpinnings of model predictions suggested the existence of generalizable features of viral genomes that are independent of virus taxonomic relationships and that may preadapt viruses to infect humans. Our model reduced a second set of 645 animal-associated viruses that were excluded from training to 272 high and 41 very high-risk candidate zoonoses and showed significantly elevated predicted zoonotic risk in viruses from nonhuman primates, but not other mammalian or avian host groups. A second application showed that our models could have identified Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) as a relatively high-risk coronavirus strain and that this prediction required no prior knowledge of zoonotic Severe Acute Respiratory Syndrome (SARS)-related coronaviruses. Genome-based zoonotic risk assessment provides a rapid, low-cost approach to enable evidence-driven virus surveillance and increases the feasibility of downstream biological and ecological characterization of viruses.

Data Proliferation, Reconciliation, and Synthesis in Viral Ecology

The fields of viral ecology and evolution are rapidly expanding, motivated in part by concerns around emerging zoonoses. One consequence is the proliferation of host–virus association data, which underpin viral macroecology and zoonotic risk prediction but remain fragmented across numerous data portals. In the present article, we propose that synthesis of host–virus data is a central challenge to characterize the global virome and develop foundational theory in viral ecology. To illustrate this, we build an open database of mammal host–virus associations that reconciles four published data sets. We show that this offers a substantially richer view of the known virome than any individual source data set but also that databases such as these risk becoming out of date as viral discovery accelerates. We argue for a shift in practice toward the development, incremental updating, and use of synthetic data sets in viral ecology, to improve replicability and facilitate work to predict the structure and dynamics of the global virome.