Phylodynamic applications in 21st century global infectious disease research

Evaluating the performance of Plasmodium falciparum genetic metrics for inferring National Malaria Control Programme reported incidence in Senegal

BACKGROUND

Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programmes (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence.

METHODS

This study examined parasites from 3147 clinical infections sampled between the years 2012-2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, a series of Poisson generalized linear mixed-effects models were constructed to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates.

RESULTS

Model-predicted incidence was compared with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (< 10/1000/annual [‰]).

CONCLUSIONS

When transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence > 10‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was < 10‰, many of the correlations between parasite genetics and incidence were reversed, which may reflect the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.

Genomic surveillance for antimicrobial resistance - a One Health perspective

Antimicrobial resistance (AMR) - the ability of microorganisms to adapt and survive under diverse chemical selection pressures - is influenced by complex interactions between humans, companion and food-producing animals, wildlife, insects and the environment. To understand and manage the threat posed to health (human, animal, plant and environmental) and security (food and water security and biosecurity), a multifaceted 'One Health' approach to AMR surveillance is required. Genomic technologies have enabled monitoring of the mobilization, persistence and abundance of AMR genes and mutations within and between microbial populations. Their adoption has also allowed source-tracing of AMR pathogens and modelling of AMR evolution and transmission. Here, we highlight recent advances in genomic AMR surveillance and the relative strengths of different technologies for AMR surveillance and research. We showcase recent insights derived from One Health genomic surveillance and consider the challenges to broader adoption both in developed and in lower- and middle-income countries.

Genomic epidemiology of the main SARS-CoV-2 variants in Italy between summer 2020 and winter 2021

Since the beginning of the pandemic, SARS-CoV-2 has shown a great genomic variability, resulting in the continuous emergence of new variants that has made their global monitoring and study a priority. This work aimed to study the genomic heterogeneity, the temporal origin, the rate of viral evolution and the population dynamics of the main circulating variants (20E.EU1, Alpha and Delta) in Italy, in August 2020-January 2022 period. For phylogenetic analyses, three datasets were set up, each for a different main lineage/variant circulating in Italy in that time including other Italian and International sequences of the same lineage/variant, available in GISAID sampled in the same times. The international dataset showed 26 (23% Italians, 23% singleton, 54% mixed), 40 (60% mixed, 37.5% Italians, 1 singleton) and 42 (85.7% mixed, 9.5% singleton, 4.8% Italians) clusters with at least one Italian sequence, in 20E.EU1  clade, Alpha and Delta variants, respectively. The estimation of tMRCAs in the Italian clusters (including >70% of genomes from Italy) showed that in all the lineage/variant, the earliest clusters were the largest in size and the most persistent in time and frequently mixed. Isolates from the major Italian Islands tended to segregate in clusters more frequently than those from other part of Italy. The study of infection dynamics showed a positive correlation between the trend in the effective number of infections estimated by BSP model and the Re curves estimated by birth-death skyline plot. The present work highlighted different evolutionary dynamics of studied lineages with high concordance between epidemiological parameters estimation and phylodynamic trends suggesting that the mechanism of replacement of the SARS-CoV-2 variants must be related to a complex of factors involving the transmissibility, as well as the implementation of control measures, and the level of cross-immunization within the population.

Phylodynamic approaches to studying avian influenza virus

Avian influenza viruses can cause severe disease in domestic and wild birds and are a pandemic threat. Phylodynamics is the study of how epidemiological, evolutionary, and immunological processes can interact to shape viral phylogenies. This review summarizes how phylodynamic methods have and could contribute to the study of avian influenza viruses. Specifically, we assess how phylodynamics can be used to examine viral spread within and between wild or domestic bird populations at various geographical scales, identify factors associated with virus dispersal, and determine the order and timing of virus lineage movement between geographic regions or poultry production systems. We discuss factors that can complicate the interpretation of phylodynamic results and identify how future methodological developments could contribute to improved control of the virus.

Epidemiology, genetic diversity, and evolutionary dynamics of Tembusu virus

Tembusu virus (TMUV) is an emerging pathogenic flavivirus associated with acute egg-drop and fatal encephalitis in domestic waterfowl. Since its initial identification in mosquitoes in 1955, TMUV has been confirmed to infect ducks, pigeons, sparrows, geese, and chickens, posing a significant threat to the poultry industry. Here, we sequenced two DTMUV strains isolated in 2019 and systematically investigated the possible origin, genetic relationships, evolutionary dynamics, and transmission patterns of TMUV based on complete virus genome sequences in the public database. We found that TMUV can be divided into four major clusters: TMUV, cluster 1, cluster 2, and cluster 3. Interestingly, we found that cluster 2.2 (within cluster 2) is the most commonly involved in interspecies transmission events, and subcluster 2.1.2 (within cluster 2.1) is currently the most prevalent cluster circulating in Asia. Notably, we also identified three positively selected sites in the E and NS1 proteins, which may be involved in virus replication, immune evasion, and host adaptation. Finally, phylogeographic analysis revealed that cluster dispersal originated in Southeast Asia and that short-distance transmission events have occurred frequently. Altogether, these data provide novel insights into the evolution and dispersal of TMUV, facilitating the development of rapid diagnostics, vaccines, and therapeutics against TMUV infection.

Population genomics of diarrheagenic Escherichia coli uncovers high connectivity between urban and rural communities in Ecuador

Human movement may be an important driver of transmission dynamics for enteric pathogens but has largely been underappreciated except for international 'travelers' diarrhea or cholera. Phylodynamic methods, which combine genomic and epidemiological data, are used to examine rates and dynamics of disease matching underlying evolutionary history and biogeographic distributions, but these methods often are not applied to enteric bacterial pathogens. We used phylodynamics to explore the phylogeographic and evolutionary patterns of diarrheagenic E. coli in northern Ecuador to investigate the role of human travel in the geographic distribution of strains across the country. Using whole genome sequences of diarrheagenic E. coli isolates, we built a core genome phylogeny, reconstructed discrete ancestral states across urban and rural sites, and estimated migration rates between E. coli populations. We found minimal structuring based on site locations, urban vs. rural locality, pathotype, or clinical status. Ancestral states of phylogenomic nodes and tips were inferred to have 51% urban ancestry and 49% rural ancestry. Lack of structuring by location or pathotype E. coli isolates imply highly connected communities and extensive sharing of genomic characteristics across isolates. Using an approximate structured coalescent model, we estimated rates of migration among circulating isolates were 6.7 times larger for urban towards rural populations compared to rural towards urban populations. This suggests increased inferred migration rates of diarrheagenic E. coli from urban populations towards rural populations. Our results indicate that investments in water and sanitation prevention in urban areas could limit the spread of enteric bacterial pathogens among rural populations.

Genomic epidemiology offers high resolution estimates of serial intervals for COVID-19

Serial intervals - the time between symptom onset in infector and infectee - are a fundamental quantity in infectious disease control. However, their estimation requires knowledge of individuals' exposures, typically obtained through resource-intensive contact tracing efforts. We introduce an alternate framework using virus sequences to inform who infected whom and thereby estimate serial intervals. We apply our technique to SARS-CoV-2 sequences from case clusters in the first two COVID-19 waves in Victoria, Australia. We find that our approach offers high resolution, cluster-specific serial interval estimates that are comparable with those obtained from contact data, despite requiring no knowledge of who infected whom and relying on incompletely-sampled data. Compared to a published serial interval, cluster-specific serial intervals can vary estimates of the effective reproduction number by a factor of 2-3. We find that serial interval estimates in settings such as schools and meat processing/packing plants are shorter than those in healthcare facilities.

When Everything Becomes Bigger: Big Data for Big Poultry Production

In future decades, the demand for poultry meat and eggs is predicted to considerably increase in pace with human population growth. Although this expansion clearly represents a remarkable opportunity for the sector, it conceals a multitude of challenges. Pollution and land erosion, competition for limited resources between animal and human nutrition, animal welfare concerns, limitations on the use of growth promoters and antimicrobial agents, and increasing risks and effects of animal infectious diseases and zoonoses are several topics that have received attention from authorities and the public. The increase in poultry production must be achieved mainly through optimization and increased efficiency. The increasing ability to generate large amounts of data ("big data") is pervasive in both modern society and the farming industry. Information accessibility-coupled with the availability of tools and computational power to store, share, integrate, and analyze data with automatic and flexible algorithms-offers an unprecedented opportunity to develop tools to maximize farm profitability, reduce socio-environmental impacts, and increase animal and human health and welfare. A detailed description of all topics and applications of big data analysis in poultry farming would be infeasible. Therefore, the present work briefly reviews the application of sensor technologies, such as optical, acoustic, and wearable sensors, as well as infrared thermal imaging and optical flow, to poultry farming. The principles and benefits of advanced statistical techniques, such as machine learning and deep learning, and their use in developing effective and reliable classification and prediction models to benefit the farming system, are also discussed. Finally, recent progress in pathogen genome sequencing and analysis is discussed, highlighting practical applications in epidemiological tracking, and reconstruction of microorganisms' population dynamics, evolution, and spread. The benefits of the objective evaluation of the effectiveness of applied control strategies are also considered. Although human-artificial intelligence collaborations in the livestock sector can be frightening because they require farmers and employees in the sector to adapt to new roles, challenges, and competencies-and because several unknowns, limitations, and open-ended questions are inevitable-their overall benefits appear to be far greater than their drawbacks. As more farms and companies connect to technology, artificial intelligence (AI) and sensing technologies will begin to play a greater role in identifying patterns and solutions to pressing problems in modern animal farming, thus providing remarkable production-based and commercial advantages. Moreover, the combination of diverse sources and types of data will also become fundamental for the development of predictive models able to anticipate, rather than merely detect, disease occurrence. The increasing availability of sensors, infrastructures, and tools for big data collection, storage, sharing, and analysis-together with the use of open standards and integration with pathogen molecular epidemiology-have the potential to address the major challenge of producing higher-quality, more healthful food on a larger scale in a more sustainable manner, thereby protecting ecosystems, preserving natural resources, and improving animal and human welfare and health.

Viral informatics: bioinformatics-based solution for managing viral infections

Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.

Epidemiological Inference From Pathogen Genomes: A Review of Phylodynamic Models and Applications

Phylodynamics requires an interdisciplinary understanding of phylogenetics, epidemiology, and statistical inference. It has also experienced more intense application than ever before amid the SARS-CoV-2 pandemic. In light of this, we present a review of phylodynamic models beginning with foundational models and assumptions. Our target audience is public health researchers, epidemiologists, and biologists seeking a working knowledge of the links between epidemiology, evolutionary models, and resulting epidemiological inference. We discuss the assumptions linking evolutionary models of pathogen population size to epidemiological models of the infected population size. We then describe statistical inference for phylodynamic models and list how output parameters can be rearranged for epidemiological interpretation. We go on to cover more sophisticated models and finish by highlighting future directions.

Viruses Previously Identified in Brazil as Belonging to HIV-1 CRF72_BF1 Represent Two Closely Related Circulating Recombinant Forms, One of Which, Designated CRF122_BF1, Is Also Circulating in Spain

Circulating recombinant forms (CRFs) are important components of the HIV-1 pandemic. Those derived from recombination between subtype B and subsubtype F1, with 18 reported, most of them of South American origin, are among the most diverse. In this study, we identified a HIV-1 BF1 recombinant cluster that is expanding in Spain, transmitted mainly via heterosexual contact, which, analyzed in near full-length genomes in four viruses, exhibited a coincident BF1 mosaic structure, with 12 breakpoints, that fully coincided with that of two viruses (10BR_MG003 and 10BR_MG005) from Brazil, previously classified as CRF72_BF1. The three remaining Brazilian viruses (10BR_MG002, 10BR_MG004, and 10BR_MG008) previously identified as CRF72_BF1 exhibited mosaic structures highly similar, but not identical, to that of the Spanish viruses and to 10BR_MG003 and 10BR_MG005, with discrepant subtypes in two short genome segments, located in pol and gp120^env. Based on these results, we propose that the five viruses from Brazil previously identified as CRF72_BF1 actually belong to two closely related CRFs, one comprising 10BR_MG002, 10BR_MG004, and 10BR_MG008, which keep their CRF72_BF1 designation, and the other, designated CRF122_BF1, comprising 10BR_MG003, 10BR_MG005, and the viruses of the identified Spanish cluster. Three other BF1 recombinant genomes, two from Brazil and one from Italy, previously identified as unique recombinant forms, were classified as CRF72_BF1. CRF122_BF1, but not CRF72_BF1, was associated with protease L89M substitution, which was reported to contribute to antiretroviral drug resistance. Phylodynamic analyses estimate the emergence of CRF122_BF1 in Brazil around 1987. Given their close phylogenetic relationship and similar structures, the grouping of CRF72_BF1 and CRF122_BF1 in a CRF family is proposed.

Tracking, Synthesizing, and Sharing Global Batrachochytrium Data at AmphibianDisease.org

Emerging infectious diseases have been especially devastating to amphibians, the most endangered class of vertebrates. For amphibians, the greatest disease threat is chytridiomycosis, caused by one of two chytridiomycete fungal pathogens Batrachochytrium dendrobatidis (Bd) and Batrachochytrium salamandrivorans (Bsal). Research over the last two decades has shown that susceptibility to this disease varies greatly with respect to a suite of host and pathogen factors such as phylogeny, geography (including abiotic factors), host community composition, and historical exposure to pathogens; yet, despite a growing body of research, a comprehensive understanding of global chytridiomycosis incidence remains elusive. In a large collaborative effort, Bd-Maps was launched in 2007 to increase multidisciplinary investigations and understanding using compiled global Bd occurrence data (Bsal was not discovered until 2013). As its database functions aged and became unsustainable, we sought to address critical needs utilizing new technologies to meet the challenges of aggregating data to facilitate research on both Bd and Bsal. Here, we introduce an advanced central online repository to archive, aggregate, and share Bd and Bsal data collected from around the world. The Amphibian Disease Portal (https://amphibiandisease.org) addresses several critical community needs while also helping to build basic biological knowledge of chytridiomycosis. This portal could be useful for other amphibian diseases and could also be replicated for uses with other wildlife diseases. We show how the Amphibian Disease Portal provides: (1) a new repository for the legacy Bd-Maps data; (2) a repository for sample-level data to archive datasets and host published data with permanent DOIs; (3) a flexible framework to adapt to advances in field, laboratory, and informatics technologies; and (4) a global aggregation of Bd and Bsal infection data to enable and accelerate research and conservation. The new framework for this project is built using biodiversity informatics best practices and metadata standards to ensure scientific reproducibility and linkages across other biological and biodiversity repositories.

Optimizing viral genome subsampling by genetic diversity and temporal distribution (TARDiS) for phylogenetics

SUMMARY

TARDiS is a novel phylogenetic tool for optimal genetic subsampling. It optimizes both genetic diversity and temporal distribution through a genetic algorithm.

AVAILABILITY AND IMPLEMENTATION

TARDiS, along with example datasets and a user manual, is available at https://github.com/smarini/tardis-phylogenetics.

In silico analysis of RNA-dependent RNA polymerase of the SARS-CoV-2 and therapeutic potential of existing antiviral drugs

The continued sustained threat of the SARS-CoV-2 virus world-wide, urgently calls for far-reaching effective therapeutic strategies for treating this emerging infection. Accordingly, this study explores mode of action and therapeutic potential of existing antiviral drugs. Multiple sequence alignment and phylogenetic analyses indicate that the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 was mutable and similar to bat coronavirus RaTG13. Successive interactions between RdRp (nsp12 alone or in complex with cofactors nsp7-8) and viral RNA demonstrated that the binding affinity values remained the same, but the sites of interaction of RdRp (highly conserved for homologous sequences from different organisms) were altered in the presence of selected antiviral drugs such as Remdesivir, and Sofosbuvir. The antiviral drug Sofosbuvir reduced the number of hydrogen bonds formed between RdRp and RNA. Remdesivir bound more tightly to viral RNA than viral RdRp alone or the nsp12-7-8 hexadecameric complex, resulting in a significant number of hydrogen bonds being formed in the uracil-rich region. The interaction between nsp12-7-8 complex and RNA was mediated by specific interaction sites of nsp7-8. Therefore, the conserved nature of RdRp interaction sites, and alterations due to drug intervention indicate the therapeutic potential of the selected drugs. In this article, we provide additional focus on the interacting amino acids of the nsp7-8 complex and highlight crucial regions that could be targeted for precluding a correct recognition of subunits involved in the hexadecameric assembly, to rationally design molecules endowed with a significant antiviral profile.

Phylodynamic analysis in the understanding of the current COVID-19 pandemic and its utility in vaccine and antiviral design and assessment

Over the last decades, the use of phylogenetic methods in the study of emerging infectious diseases has gained considerable traction in public health. Particularly, the integration of phylogenetic analyses with the understanding of the pathogen dynamics at the population level has provided powerful tools for epidemiological surveillance systems. In the same way, the development of statistical methods and theory, as well as improvement of computational efficiency for evolutionary analysis, has expanded the use of these tools for vaccine and antiviral development. Today with the Coronavirus Disease 2019 (COVID-19), this seems to be critical. In this article, we discuss how the application of phylodynamic analysis can improve the understanding of current pandemic dynamics as well as the design, selection, and evaluation of vaccine candidates and antivirals.

Molecular epidemiology in the HIV and SARS-CoV-2 pandemics

PURPOSE OF REVIEW

The aim of this review was to compare and contrast the application of molecular epidemiology approaches for the improved management and understanding of the HIV versus SARS-CoV-2 epidemics.

RECENT FINDINGS

Molecular biology approaches, including PCR and whole genome sequencing (WGS), have become powerful tools for epidemiological investigation. PCR approaches form the basis for many high-sensitivity diagnostic tests and can supplement traditional contact tracing and surveillance strategies to define risk networks and transmission patterns. WGS approaches can further define the causative agents of disease, trace the origins of the pathogen, and clarify routes of transmission. When coupled with clinical datasets, such as electronic medical record data, these approaches can investigate co-correlates of disease and pathogenesis. In the ongoing HIV epidemic, these approaches have been effectively deployed to identify treatment gaps, transmission clusters and risk factors, though significant barriers to rapid or real-time implementation remain critical to overcome. Likewise, these approaches have been successful in addressing some questions of SARS-CoV-2 transmission and pathogenesis, but the nature and rapid spread of the virus have posed additional challenges.

SUMMARY

Overall, molecular epidemiology approaches offer unique advantages and challenges that complement traditional epidemiological tools for the improved understanding and management of epidemics.

Differing impacts of global and regional responses on SARS-CoV-2 transmission cluster dynamics

Although the global response to COVID-19 has not been entirely unified, the opportunity arises to assess the impact of regional public health interventions and to classify strategies according to their outcome. Analysis of genetic sequence data gathered over the course of the pandemic allows us to link the dynamics associated with networks of connected individuals with specific interventions. In this study, clusters of transmission were inferred from a phylogenetic tree representing the relationships of patient sequences sampled from December 30, 2019 to April 17, 2020. Metadata comprising sampling time and location were used to define the global behavior of transmission over this earlier sampling period, but also the involvement of individual regions in transmission cluster dynamics. Results demonstrate a positive impact of international travel restrictions and nationwide lockdowns on global cluster dynamics. However, residual, localized clusters displayed a wide range of estimated initial secondary infection rates, for which uniform public health interventions are unlikely to have sustainable effects. Our findings highlight the presence of so-called "super-spreaders", with the propensity to infect a larger-than-average number of people, in countries, such as the USA, for which additional mitigation efforts targeting events surrounding this type of spread are urgently needed to curb further dissemination of SARS-CoV-2.

Animal Disease Surveillance in the 21st Century: Applications and Robustness of Phylodynamic Methods in Recent U.S. Human-Like H3 Swine Influenza Outbreaks

Emerging and endemic animal viral diseases continue to impose substantial impacts on animal and human health. Most current and past molecular surveillance studies of animal diseases investigated spatio-temporal and evolutionary dynamics of the viruses in a disjointed analytical framework, ignoring many uncertainties and made joint conclusions from both analytical approaches. Phylodynamic methods offer a uniquely integrated platform capable of inferring complex epidemiological and evolutionary processes from the phylogeny of viruses in populations using a single Bayesian statistical framework. In this study, we reviewed and outlined basic concepts and aspects of phylodynamic methods and attempted to summarize essential components of the methodology in one analytical pipeline to facilitate the proper use of the methods by animal health researchers. Also, we challenged the robustness of the posterior evolutionary parameters, inferred by the commonly used phylodynamic models, using hemagglutinin (HA) and polymerase basic 2 (PB2) segments of the currently circulating human-like H3 swine influenza (SI) viruses isolated in the United States and multiple priors. Subsequently, we compared similarities and differences between the posterior parameters inferred from sequence data using multiple phylodynamic models. Our suggested phylodynamic approach attempts to reduce the impact of its inherent limitations to offer less biased and biologically plausible inferences about the pathogen evolutionary characteristics to properly guide intervention activities. We also pinpointed requirements and challenges for integrating phylodynamic methods in routine animal disease surveillance activities.

What is global health? Key concepts and clarification of misperceptions: Report of the 2019 GHRP editorial meeting

The call for "Working Together to Build a Community of Shared Future for Mankind" requires us to improve people's health across the globe, while global health development entails a satisfactory answer to a fundamental question: "What is global health?" To promote research, teaching, policymaking, and practice in global health, we summarize the main points on the definition of global health from the Editorial Board Meeting of Global Health Research and Policy, convened in July 2019 in Wuhan, China. The meeting functioned as a platform for free brainstorming, in-depth discussion, and post-meeting synthesizing. Through the meeting, we have reached a consensus that global health can be considered as a general guiding principle, an organizing framework for thinking and action, a new branch of sciences and specialized discipline in the large family of public health and medicine. The word "global" in global health can be subjective or objective, depending on the context and setting. In addition to dual-, multi-country and global, a project or a study conducted at a local area can be global if it (1) is framed with a global perspective, (2) intends to address an issue with global impact, and/or (3) seeks global solutions to an issue, such as frameworks, strategies, policies, laws, and regulations. In this regard, global health is eventually an extension of "international health" by borrowing related knowledge, theories, technologies and methodologies from public health and medicine. Although global health is a concept that will continue to evolve, our conceptualization through group effort provides, to date, a comprehensive understanding. This report helps to inform individuals in the global health community to advance global health science and practice, and recommend to take advantage of the Belt and Road Initiative proposed by China.

Advances in Visualization Tools for Phylogenomic and Phylodynamic Studies of Viral Diseases

Genomic and epidemiological monitoring have become an integral part of our response to emerging and ongoing epidemics of viral infectious diseases. Advances in high-throughput sequencing, including portable genomic sequencing at reduced costs and turnaround time, are paralleled by continuing developments in methodology to infer evolutionary histories (dynamics/patterns) and to identify factors driving viral spread in space and time. The traditionally static nature of visualizing phylogenetic trees that represent these evolutionary relationships/processes has also evolved, albeit perhaps at a slower rate. Advanced visualization tools with increased resolution assist in drawing conclusions from phylogenetic estimates and may even have potential to better inform public health and treatment decisions, but the design (and choice of what analyses are shown) is hindered by the complexity of information embedded within current phylogenetic models and the integration of available meta-data. In this review, we discuss visualization challenges for the interpretation and exploration of reconstructed histories of viral epidemics that arose from increasing volumes of sequence data and the wealth of additional data layers that can be integrated. We focus on solutions that address joint temporal and spatial visualization but also consider what the future may bring in terms of visualization and how this may become of value for the coming era of real-time digital pathogen surveillance, where actionable results and adequate intervention strategies need to be obtained within days.

Neutral Theory and Rapidly Evolving Viral Pathogens

The evolution of viral pathogens is shaped by strong selective forces that are exerted during jumps to new hosts, confrontations with host immune responses and antiviral drugs, and numerous other processes. However, while undeniably strong and frequent, adaptive evolution is largely confined to small parts of information-packed viral genomes, and the majority of observed variation is effectively neutral. The predictions and implications of the neutral theory have proven immensely useful in this context, with applications spanning understanding within-host population structure, tracing the origins and spread of viral pathogens, predicting evolutionary dynamics, and modeling the emergence of drug resistance. We highlight the multiple ways in which the neutral theory has had an impact, which has been accelerated in the age of high-throughput, high-resolution genomics.