Toward a quantitative understanding of viral phylogeography

Comparing Phylogeographies to Reveal Incompatible Geographical Histories within Genomes

Modern phylogeography aims at reconstructing the geographic movement of organisms based on their genomic sequences and spatial information. Phylogeographic approaches are often applied to pathogen sequences and therefore tend to neglect the possibility of recombination, which decouples the evolutionary and geographic histories of different parts of the genome. Genomic regions of recombining or reassorting pathogens often originate and evolve at different times and locations, which characterize their unique spatial histories. Measuring the extent of these differences requires new methods to compare geographic information on phylogenetic trees reconstructed from different parts of the genome. Here we develop for the first time a set of measures of phylogeographic incompatibility, aimed at detecting differences between geographical histories in terms of distances between phylogeographies. We study the effect of varying demography and recombination on phylogeographic incompatibilities using coalescent simulations. We further apply these measures to the evolutionary history of human and livestock pathogens, either reassorting or recombining, such as the Victoria and Yamagata lineages of influenza B and the O/Ind-2001 foot-and-mouth disease virus strain. Our results reveal diverse geographical paths of migration that characterize the origins and evolutionary histories of different viral genes and genomic segments. These incompatibility measures can be applied to any phylogeography, and more generally to any phylogeny where each tip has been assigned either a continuous or discrete "trait" independent of the sequence. We illustrate this flexibility with an analysis of the interplay between the phylogeography and phylolinguistics of Uralic-speaking human populations, hinting at patrilinear language transmission.

Phylodynamic evolution of HIV-1 A6 sub-subtype epidemics in Poland

The human immunodeficiency virus type 1 (HIV-1) A6 sub-subtype is highly prevalent in Eastern Europe. Over the past decade, the dissemination of the A6 lineage has been expanding in Poland. The recent Russian invasion of Ukraine may further escalate the spread of this sub-subtype. While evolutionary studies using viral sequences have been instrumental in identifying the HIV epidemic patterns, the origins, and dynamics of the A6 sub-subtype in Poland remain to be explored. We analyzed 1185 HIV-1 A6 pol sequences from Poland, along with 8318 publicly available sequences from other countries. For analyses, phylogenetic tree construction, population dynamics inference, Bayesian analysis, and discrete phylogeographic modeling were employed. Of the introduction events to Poland, 69.94% originated from Ukraine, followed by 29.17% from Russia. Most A6 sequences in Poland (53.16%) formed four large clades, with their introductions spanning 1993-2008. Central and Southern Polish regions significantly influenced migration events. Transmissions among men who have sex with men (MSM) emerged as the dominant risk group for virus circulation, representing 72.92% of migration events. Sequences from migrants were found primarily outside the large clades. Past migration from Ukraine has fueled the spread of the A6 sub-subtype and the current influx of war-displaced people maintains the growing national epidemic.

Approaches and challenges to inferring the geographical source of infectious disease outbreaks using genomic data

Genomic data hold increasing potential in the elucidation of transmission dynamics and geographical sources of infectious disease outbreaks. Phylogeographic methods that use epidemiological and genomic data obtained from surveillance enable us to infer the history of spatial transmission that is naturally embedded in the topology of phylogenetic trees as a record of the dispersal of infectious agents between geographical locations. In this Review, we provide an overview of phylogeographic approaches widely used for reconstructing the geographical sources of outbreaks of interest. These approaches can be classified into ancestral trait or state reconstruction and structured population models, with structured population models including popular structured coalescent and birth-death models. We also describe the major challenges associated with sequencing technologies, surveillance strategies, data sharing, and analysis frameworks that became apparent during the generation of large-scale genomic data in recent years, extending beyond inference approaches. Finally, we highlight the role of genomic data in geographical source inference and clarify how this enhances understanding and molecular investigations of outbreak sources.

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.

Chikungunya virus infection in the southernmost state of Brazil was characterised by self-limited transmission (2017-2019) and a larger 2021 outbreak

BACKGROUND

Chikungunya is a mosquito-borne virus that has been causing large outbreaks in the Americas since 2014. In Brazil, Asian-Caribbean (AC) and East-Central-South-African (ECSA) genotypes have been detected and lead to large outbreaks in several Brazilian states. In Rio Grande do Sul (RS), the southernmost state of Brazil, the first cases were reported in 2016.

OBJECTIVES AND METHODS

We employed genome sequencing and epidemiological investigation to characterise the Chikungunya fever (CHIKF) burden in RS between 2017-2021.

FINDINGS

We detected an increasing CHIKF burden linked to travel associated introductions and communitary transmission of distinct lineages of the ECSA genotype during this period.

MAIN CONCLUSIONS

Until 2020, CHIKV introductions were most travel associated and transmission was limited. Then, in 2021, the largest outbreak occurred in the state associated with the introduction of a new ECSA lineage. CHIKV outbreaks are likely to occur in the near future due to abundant competent vectors and a susceptible population, exposing more than 11 million inhabitants to an increasing infection risk.

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.

Traversing missing links in the spread of HIV

Combining clinical and genetic data can improve the effectiveness of virus tracking with the aim of reducing the number of HIV cases by 2030.

Evolutionary Dynamics of Foot and Mouth Disease Virus Serotype A and Its Endemic Sub-Lineage A/ASIA/Iran-05/SIS-13 in Pakistan

Foot and mouth disease (FMD) causes severe economic losses to the livestock industry of endemic countries, including Pakistan. Pakistan is part of the endemic pool 3 for foot and mouth disease viruses (FMDV), characterized by co-circulating O, A, and Asia 1 serotypes, as designated by the world reference laboratory for FMD (WRL-FMD). FMDV serotype A lineage ASIA/Iran-05 is widespread in buffalos and cattle populations and was first reported in Pakistan in 2006. This lineage has a high turnover, with as many as 10 sub-lineages reported from Pakistan over the years. In this study, we reconstructed the evolutionary, demographic, and spatial history of serotype A and one of its sub-lineages, A/ASIA/Iran-05/SIS-13, prevalent in Pakistan. We sequenced nearly complete genomes of three isolates belonging to sub-lineage A/ASIA/Iran-05/SIS-13. We estimated recombination patterns and natural selection acting on the serotype A genomes. Source and transmission routes in Pakistan were inferred, and the clustering pattern of isolates of the SIS-13 sub-lineage were mapped on a tree. We hereby report nearly complete genome sequences of isolates belonging to sub-lineage A/ASIA/Iran-05/SIS-13, along with purported recombinant genomes, and highlight that complete coding sequences can better elucidate the endemic history and evolutionary pressures acting on long-term co-circulating FMDV strains.

Phylodynamics and Coat Protein Analysis of Babaco Mosaic Virus in Ecuador

Babaco is a fast-growing herbaceous shrub with great commercial potential because of the organoleptic properties of its fruit. Babaco mosaic virus (BabMV) is a potexvirus in the family Alphaflexiviridae affecting babaco in all the provinces that produce this crop in Ecuador. BabMV was recently described but it has been affecting babaco for decades and, since many potexviruses are serologically indistinguishable, it may have been previously misidentified as papaya mosaic virus. Based on the coat protein (CP) gene, we aimed to study the distribution and epidemiological patterns of BabMV in babaco and chamburo over the years and to model its three-dimensional structure. Sequences of the CP were obtained from thirty-six isolates from plants collected in the main babaco-producing provinces of Ecuador between 2016 and 2021. The evolution rate of BabMV was estimated at 1.21 × 10−3 nucleotide substitutions site−1 year−1 and a time of origin of the most recent common ancestor around 1958.80. From molecular dynamics simulations, compared to other proteins of BabMV—RDRP, TGB1, and Alkb domain—the CP exhibited a higher flexibility with the C and N terminals as the most flexible regions. The reconstructed viral distribution provides dispersion patterns which have implications for control approaches of BabMV.

Accommodating sampling location uncertainty in continuous phylogeography

Phylogeographic inference of the dispersal history of viral lineages offers key opportunities to tackle epidemiological questions about the spread of fast-evolving pathogens across human, animal and plant populations. In continuous space, i.e. when locations are specified by longitude and latitude, these reconstructions are however often limited by the availability or accessibility of precise sampling locations required for such spatially explicit analyses. We here review the different approaches that can be considered when genomic sequences are associated with a geographic area of sampling instead of precise coordinates. In particular, we describe and compare the approaches to define homogeneous and heterogeneous prior ranges of sampling coordinates.

Phylodynamic Dispersal of SARS-CoV-2 Lineages Circulating across Polish-German Border Provinces

Introduction: The emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has evolved into a worldwide outbreak, with significant molecular evolution over time. Large-scale phylodynamic studies allow to map the virus spread and inform preventive strategies. Aim: This study investigates the extent of binational dispersal and dynamics of SARS-CoV-2 lineages between seven border provinces of the adjacent countries of Poland and Germany to reconstruct SARS-CoV-2 transmission networks. Methods: Following three pandemic waves from March 2020 to the end of May 2021, we analysed a dataset of 19,994 sequences divided into B.1.1.7|Alpha and non-Alpha lineage groups. We performed phylogeographic analyses using the discrete diffusion models to identify the pathways of virus spread. Results: Based on population dynamics inferences, in total, 673 lineage introductions (95% HPD interval 641−712) for non-Alpha and 618 (95% HPD interval 599−639) for B.1.1.7|Alpha were identified in the area. For non-Alpha lineages, 5.05% binational, 86.63% exclusively German, and 8.32% Polish clusters were found, with a higher frequency of international clustering observed for B.1.1.7|Alpha (13.11% for binational, 68.44% German and 18.45% Polish, p < 0.001). We identified key transmission hubs for the analysed lineages, namely Saxony, West Pomerania and Lower Silesia. Conclusions: Clustering patterns between Poland and Germany reflect the viral variant transmission dynamics at the international level in the borderline area. Tracing the spread of the virus between two adjacent large European countries may provide a basis for future intervention policies in cross-border cooperation efforts against the spread of the pandemics.

The rates of global bacterial and archaeal dispersal

The phylogenetic resolution at which microorganisms display geographic endemism, the rates at which they disperse at global scales, and the role of humans on global microbial dispersal are largely unknown. Answering these questions is necessary for interpreting microbial biogeography, ecology, and macroevolution and for predicting the spread of emerging pathogenic strains. To resolve these questions, I analyzed the geographic and evolutionary relationships between 36,795 bacterial and archaeal ("prokaryotic") genomes from ∼7000 locations around the world. I find clear signs of continental-scale endemism, including strong correlations between phylogenetic divergence and geographic distance. However, the phylogenetic scale at which endemism generally occurs is extremely small, and most "species" (defined by an average nucleotide identity ≥ 95%) and even closely related strains (average nucleotide identity ≥ 99.9%) are globally distributed. Human-associated lineages display faster dispersal rates than other terrestrial lineages; the average net distance between any two human-associated cell lineages diverging 50 years ago is roughly 580 km. These results suggest that many previously reported global-scale microbial biogeographical patterns are likely the result of recent or current environmental filtering rather than geographic endemism. For human-associated lineages, estimated transition rates between Europe and North America are particularly high, and much higher than for non-human associated terrestrial lineages, highlighting the role that human movement plays in global microbial dispersal. Dispersal was slowest for hot spring- and terrestrial subsurface-associated lineages, indicating that these environments may act as "isolated islands" of microbial evolution.

OUP accepted manuscript

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution plays a significant role in shaping the dynamics of the coronavirus disease 2019 pandemic. To monitor the evolution of SARS-CoV-2 variants, through international collaborations, we performed genomic epidemiology analyses on a weekly basis with SARS-CoV-2 samples collected from a border region between Germany, Poland, and the Czech Republic in a global background. For identified virus mutant variants, active viruses were isolated and functional evaluations were performed to test their replication fitness and neutralization sensitivity against vaccine-elicited serum neutralizing antibodies. Thereby we identified a new B.1.1.7 sub-lineage carrying additional mutations of nucleoprotein G204P and open-reading-frame-8 K68stop. Of note, this B.1.1.7 sub-lineage is the predominant B.1.1.7 variant in several European countries such as Czech Republic, Austria, and Slovakia. The earliest samples belonging to this sub-lineage were detected in November 2020 in a few countries in the European continent, but not in the UK. We have also detected its further evolution with extra spike mutations D138Y and A701V, which are signature mutations shared with the Gamma and Beta variants, respectively. Antibody neutralization assay of virus variant isolations has revealed that the variant with extra spike mutations is 3.2-fold less sensitive to vaccine-elicited antibodies as compared to the other B.1.1.7 variants tested, indicating potential for immune evasion, but it also exhibited reduced replication fitness, suggesting lower transmissibility. The wide spread of this B.1.1.7 sub-lineage was related to the pandemic waves in early 2021 in various European countries. These findings about the emergence, spread, evolution, infection, and transmission abilities of this B.1.1.7 sub-lineage add to our understanding about the pandemic development in Europe and highlight the importance of international collaboration on virus mutant surveillance.

The impact of sampling bias on viral phylogeographic reconstruction

Genomic epidemiology plays an ever-increasing role in our understanding of and response to the spread of infectious pathogens. Phylogeography, the reconstruction of the historical location and movement of pathogens from the evolutionary relationships among sampled pathogen sequences, can inform policy decisions related to viral movement among jurisdictions. However, phylogeographic reconstruction is impacted by the fact that the sampling and virus sequencing policies differ among jurisdictions, and these differences can cause bias in phylogeographic reconstructions. Here we assess the potential impacts of geographic-based sampling bias on estimated viral locations in the past, and on whether key viral movements can be detected. We quantify the effect of bias using simulated phylogenies with known geographic histories, and determine the impact of the biased sampling and of the underlying migration rate on the accuracy of estimated past viral locations. We find that overall, the accuracy of phylogeographic reconstruction is high, particularly when the migration rate is low. However, results depend on sampling, and sampling bias can have a large impact on the numbers and nature of estimated migration events. We apply these insights to the geographic spread of Ebolavirus in the 2014-2016 West Africa epidemic. This work highlights how sampling policy can both impact geographic inference and be optimized to best ensure the accuracy of specific features of geographic spread.

Evaluating the Impact of Anthropogenic Factors on the Dissemination of Contemporary Cosmopolitan, Arctic, and Arctic-like Rabies Viruses

Rabies is a globally prevalent viral zoonosis that causes 59,000 deaths per year and has important economic consequences. Most virus spread is associated with the migration of its primary hosts. Anthropogenic dissemination, mainly via the transportation of rabid dogs, shaped virus ecology a few hundred years ago and is responsible for several current outbreaks. A systematic analysis of aberrant long-distance events in the steppe and Arctic-like groups of rabies virus was performed using statistical (Bayesian) phylogeography and plots of genetic vs. geographic distances. The two approaches produced similar results but had some significant differences and complemented each other. No phylogeographic analysis could be performed for the Arctic group because polar foxes transfer the virus across the whole circumpolar region at high velocity, and there was no correlation between genetic and geographic distances in this virus group. In the Arctic-like group and the steppe subgroup of the cosmopolitan group, a significant number of known sequences (15-20%) was associated with rapid long-distance transfers, which mainly occurred within Eurasia. Some of these events have been described previously, while others have not been documented. Most of the recent long-distance transfers apparently did not result in establishing the introduced virus, but a few had important implications for the phylogeographic history of rabies. Thus, human-mediated long-distance transmission of the rabies virus remains a significant threat that needs to be addressed.

Relax, Keep Walking - A Practical Guide to Continuous Phylogeographic Inference with BEAST

Spatially explicit phylogeographic analyses can be performed with an inference framework that employs relaxed random walks to reconstruct phylogenetic dispersal histories in continuous space. This core model was first implemented 10 years ago and has opened up new opportunities in the field of phylodynamics, allowing researchers to map and analyze the spatial dissemination of rapidly evolving pathogens. We here provide a detailed and step-by-step guide on how to set up, run, and interpret continuous phylogeographic analyses using the programs BEAUti, BEAST, Tracer, and TreeAnnotator.

Towards a more healthy conservation paradigm: integrating disease and molecular ecology to aid biological conservation†

Parasites, and the diseases they cause, are important from an ecological and evolutionary perspective because they can negatively affect host fitness and can regulate host populations. Consequently, conservation biology has long recognized the vital role that parasites can play in the process of species endangerment and recovery. However, we are only beginning to understand how deeply parasites are embedded in ecological systems, and there is a growing recognition of the important ways in which parasites affect ecosystem structure and function. Thus, there is an urgent need to revisit how parasites are viewed from a conservation perspective and broaden the role that disease ecology plays in conservation-related research and outcomes. This review broadly focusses on the role that disease ecology can play in biological conservation. Our review specifically emphasizes on how the integration of tools and analytical approaches associated with both disease and molecular ecology can be leveraged to aid conservation biology. Our review first concentrates on disease-mediated extinctions and wildlife epidemics. We then focus on elucidating how host–parasite interactions has improved our understanding of the eco-evolutionary dynamics affecting hosts at the individual, population, community and ecosystem scales. We believe that the role of parasites as drivers and indicators of ecosystem health is especially an exciting area of research that has the potential to fundamentally alter our view of parasites and their role in biological conservation. The review concludes with a broad overview of the current and potential applications of modern genomic tools in disease ecology to aid biological conservation.

Development of a Dissemination Platform for Spatiotemporal and Phylogenetic Analysis of Avian Infectious Bronchitis Virus

Infecting large portions of the global poultry populations, the avian infectious bronchitis virus (IBV) remains a major economic burden in North America. With more than 30 serotypes globally distributed, Arkansas, Connecticut, Delaware, Georgia, and Massachusetts are among the most predominant serotypes in the United States. Even though vaccination is widely used, the high mutation rate exhibited by IBV is continuously triggering the emergence of new viral strains and hindering control and prevention measures. For that reason, targeted strategies based on constantly updated information on the IBV circulation are necessary. Here, we sampled IBV-infected farms from one US state and collected and analyzed 65 genetic sequences coming from three different lineages along with the immunization information of each sampled farm. Phylodynamic analyses showed that IBV dispersal velocity was 12.3 km/year. The majority of IBV infections appeared to have derived from the introduction of the Arkansas DPI serotype, and the Arkansas DPI and Georgia 13 were the predominant serotypes. When analyzed against IBV sequences collected across the United States and deposited in the GenBank database, the most likely viral origin of our sequences was from the states of Alabama, Georgia, and Delaware. Information about vaccination showed that the MILDVAC-MASS+ARK vaccine was applied on 26% of the farms. Using a publicly accessible open-source tool for real-time interactive tracking of pathogen spread and evolution, we analyzed the spatiotemporal spread of IBV and developed an online reporting dashboard. Overall, our work demonstrates how the combination of genetic and spatial information could be used to track the spread and evolution of poultry diseases, providing timely information to the industry. Our results could allow producers and veterinarians to monitor in near-real time the current IBV strain circulating, making it more informative, for example, in vaccination-related decisions.

Dispersal dynamics of SARS-CoV-2 lineages during the first epidemic wave in New York City

During the first phase of the COVID-19 epidemic, New York City rapidly became the epicenter of the pandemic in the United States. While molecular phylogenetic analyses have previously highlighted multiple introductions and a period of cryptic community transmission within New York City, little is known about the circulation of SARS-CoV-2 within and among its boroughs. We here perform phylogeographic investigations to gain insights into the circulation of viral lineages during the first months of the New York City outbreak. Our analyses describe the dispersal dynamics of viral lineages at the state and city levels, illustrating that peripheral samples likely correspond to distinct dispersal events originating from the main metropolitan city areas. In line with the high prevalence recorded in this area, our results highlight the relatively important role of the borough of Queens as a transmission hub associated with higher local circulation and dispersal of viral lineages toward the surrounding boroughs.

Finding disease outbreak locations from human mobility data

Finding the origin location of an infectious disease outbreak quickly is crucial in mitigating its further dissemination. Current methods to identify outbreak locations early on rely on interviewing affected individuals and correlating their movements, which is a manual, time-consuming, and error-prone process. Other methods such as contact tracing, genomic sequencing or theoretical models of epidemic spread offer help, but they are not applicable at the onset of an outbreak as they require highly processed information or established transmission chains. Digital data sources such as mobile phones offer new ways to find outbreak sources in an automated way. Here, we propose a novel method to determine outbreak origins from geolocated movement data of individuals affected by the outbreak. Our algorithm scans movement trajectories for shared locations and identifies the outbreak origin as the most dominant among them. We test the method using various empirical and synthetic datasets, and demonstrate that it is able to single out the true outbreak location with high accuracy, requiring only data of N = 4 individuals. The method can be applied to scenarios with multiple outbreak locations, and is even able to estimate the number of outbreak sources if unknown, while being robust to noise. Our method is the first to offer a reliable, accurate out-of-the-box approach to identify outbreak locations in the initial phase of an outbreak. It can be easily and quickly applied in a crisis situation, improving on previous manual approaches. The method is not only applicable in the context of disease outbreaks, but can be used to find shared locations in movement data in other contexts as well.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1140/epjds/s13688-021-00306-6.

The Molecular Epidemiology and Transmission Dynamics of HIV Type 1 in a General Population Cohort in Uganda

The General Population Cohort (GPC) in south-western Uganda has a low HIV-1 incidence rate (<1%). However, new infections continue to emerge. In this research, 3796 HIV-1 pol sequences (GPC: n = 1418, non-GPC sites: n = 1223, Central Uganda: n = 1010 and Eastern Uganda: n = 145) generated between 2003–2015 were analysed using phylogenetic methods with demographic data to understand HIV-1 transmission in this cohort and inform the epidemic response. HIV-1 subtype A1 was the most prevalent strain in the GPC area (GPC and non-GPC sites) (39.8%), central (45.9%) and eastern (52.4%) Uganda. However, in the GPC alone, subtype D was the predominant subtype (39.1%). Of the 524 transmission clusters identified by Cluster Picker, all large clusters (≥5 individuals, n = 8) involved individuals from the GPC. In a multivariate analysis, clustering was strongly associated with being female (adjusted Odds Ratio, aOR = 1.28; 95% CI, 1.06–1.54), being >25 years (aOR = 1.52; 95% CI, 1.16–2.0) and being a resident in the GPC (aOR = 6.90; 95% CI, 5.22–9.21). Phylogeographic analysis showed significant viral dissemination (Bayes Factor test, BF > 3) from the GPC without significant viral introductions (BF < 3) into the GPC. The findings suggest localized HIV-1 transmission in the GPC. Intensifying geographically focused combination interventions in the GPC would contribute towards controlling HIV-1 infections.

Phylogeographic Estimation and Simulation of Global Diffusive Dispersal

The analysis of time-resolved phylogenies (timetrees) and geographic location data allows estimation of dispersal rates, for example, for invasive species and infectious diseases. Many estimation methods are based on the Brownian Motion model for diffusive dispersal on a 2D plane; however, the accuracy of these methods deteriorates substantially when dispersal occurs at global scales because spherical Brownian motion (SBM) differs from planar Brownian motion. No statistical method exists for estimating SBM diffusion coefficients from a given timetree and tip coordinates, and no method exists for simulating SBM along a given timetree. Here, I present new methods for simulating SBM along a given timetree, and for estimating SBM diffusivity from a given timetree and tip coordinates using a modification of Felsenstein's independent contrasts and maximum likelihood. My simulation and fitting methods can accommodate arbitrary time-dependent diffusivities and scale efficiently to trees with millions of tips, thus enabling new analyses even in cases where planar BM would be a sufficient approximation. I demonstrate these methods using a timetree of marine and terrestrial Cyanobacterial genomes, as well as timetrees of two globally circulating Influenza B clades. My methods are implemented in the R package "castor." [Independent contrasts; phylogenetic; random walk; simulation; spherical Brownian motion.].

Toxigenic Vibrio cholerae evolution and establishment of reservoirs in aquatic ecosystems

The spread of cholera in the midst of an epidemic is largely driven by direct transmission from person to person, although it is well-recognized that Vibrio cholerae is also capable of growth and long-term survival in aquatic ecosystems. While prior studies have shown that aquatic reservoirs are important in the persistence of the disease on the Indian subcontinent, an epidemiological view postulating that locally evolving environmental V. cholerae contributes to outbreaks outside Asia remains debated. The single-source introduction of toxigenic V. cholerae O1 in Haiti, one of the largest outbreaks occurring this century, with 812,586 suspected cases and 9,606 deaths reported through July 2018, provided a unique opportunity to evaluate the role of aquatic reservoirs and assess bacterial transmission dynamics across environmental boundaries. To this end, we investigated the phylogeography of both clinical and aquatic toxigenic V. cholerae O1 isolates and show robust evidence of the establishment of aquatic reservoirs as well as ongoing evolution of V. cholerae isolates from aquatic sites. Novel environmental lineages emerged from sequential population bottlenecks, carrying mutations potentially involved in adaptation to the aquatic ecosystem. Based on such empirical data, we developed a mixed-transmission dynamic model of V. cholerae, where aquatic reservoirs actively contribute to genetic diversification and epidemic emergence, which underscores the complexity of transmission pathways in epidemics and endemic settings and the need for long-term investments in cholera control at both human and environmental levels.

In Search of Covariates of HIV-1 Subtype B Spread in the United States-A Cautionary Tale of Large-Scale Bayesian Phylogeography

Infections with HIV-1 group M subtype B viruses account for the majority of the HIV epidemic in the Western world. Phylogeographic studies have placed the introduction of subtype B in the United States in New York around 1970, where it grew into a major source of spread. Currently, it is estimated that over one million people are living with HIV in the US and that most are infected with subtype B variants. Here, we aim to identify the drivers of HIV-1 subtype B dispersal in the United States by analyzing a collection of 23,588 pol sequences, collected for drug resistance testing from 45 states during 2004-2011. To this end, we introduce a workflow to reduce this large collection of data to more computationally-manageable sample sizes and apply the BEAST framework to test which covariates associate with the spread of HIV-1 across state borders. Our results show that we are able to consistently identify certain predictors of spread under reasonable run times across datasets of up to 10,000 sequences. However, the general lack of phylogenetic structure and the high uncertainty associated with HIV trees make it difficult to interpret the epidemiological relevance of the drivers of spread we are able to identify. While the workflow we present here could be applied to other virus datasets of a similar scale, the characteristic star-like shape of HIV-1 phylogenies poses a serious obstacle to reconstructing a detailed evolutionary and spatial history for HIV-1 subtype B in the US.

Impact of past climate warming on genomic diversity and demographic history of collared lemmings across the Eurasian Arctic

The Arctic climate was warmer than today at the last interglacial and the Holocene thermal optimum. To reveal the impact of past climate-warming events on the demographic history of an Arctic specialist, we examined both mitochondrial and nuclear genomic variation in the collared lemming (Dicrostonyx torquatus, Pallas), a keystone species in tundra communities, across its entire distribution in northern Eurasia. The ancestral phylogenetic position of the West Beringian group and divergence time estimates support the hypothesis of continental range contraction to a single refugial area located in West Beringia during high-magnitude warming of the last interglacial, followed by westward recolonization of northern Eurasia in the last glacial period. The West Beringian group harbors the highest mitogenome diversity and its inferred demography indicates a constantly large effective population size over the Late Pleistocene to Holocene. This suggests that northward forest expansion during recent warming of the Holocene thermal optimum did not affect the gene pool of the collared lemming in West Beringia but reduced genomic diversity and effective population size in all other regions of the Eurasian Arctic. Demographic inference from genomic diversity was corroborated by species distribution modeling showing reduction in species distribution during past climate warming. These conclusions are supported by recent paleoecological evidence suggesting smaller temperature increases and moderate northward forest advances in the extreme northeast of Eurasia during the Late Pleistocene-to-Holocene warming events. This study emphasizes the importance of West Beringia as a potential refugium for cold-adapted Arctic species under ongoing climate warming.

Distinct rates and patterns of spread of the major HIV-1 subtypes in Central and East Africa

Since the ignition of the HIV-1 group M pandemic in the beginning of the 20th century, group M lineages have spread heterogeneously throughout the world. Subtype C spread rapidly through sub-Saharan Africa and is currently the dominant HIV lineage worldwide. Yet the epidemiological and evolutionary circumstances that contributed to its epidemiological expansion remain poorly understood. Here, we analyse 346 novel pol sequences from the DRC to compare the evolutionary dynamics of the main HIV-1 lineages, subtypes A1, C and D. Our results place the origins of subtype C in the 1950s in Mbuji-Mayi, the mining city of southern DRC, while subtypes A1 and D emerged in the capital city of Kinshasa, and subtypes H and J in the less accessible port city of Matadi. Following a 15-year period of local transmission in southern DRC, we find that subtype C spread at least three-fold faster than other subtypes circulating in Central and East Africa. In conclusion, our results shed light on the origins of HIV-1 main lineages and suggest that socio-historical rather than evolutionary factors may have determined the epidemiological fate of subtype C in sub-Saharan Africa.

HIV Rebound Is Predominantly Fueled by Genetically Identical Viral Expansions from Diverse Reservoirs

Viral rebound upon stopping combined antiretroviral therapy poses a major barrier toward an HIV cure. Cellular and anatomical sources responsible for reinitiating viral replication remain a subject of ardent debate, despite extensive research efforts. To unravel the source of rebounding viruses, we conducted a large-scale HIV-STAR (HIV-1 sequencing before analytical treatment interruption to identify the anatomically relevant HIV reservoir) clinical trial. We collected samples from 11 participants and compared the genetic composition of (pro)viruses collected under treatment from different cellular and anatomical compartments with that of plasma viruses sampled during analytical treatment interruption. We found a remarkably heterogeneous source of viral rebound. In addition, irrespective of the compartment or cell subset, genetically identical viral expansions played a significant role in viral rebound. Our study suggests that although there does not seem to be a primary source for rebound HIV, cellular proliferation is an important driver of HIV persistence and should therefore be considered in future curative strategies.

Phylogeography of Puumala orthohantavirus in Europe

Puumala virus is an RNA virus hosted by the bank vole (Myodes glareolus) and is today present in most European countries. Whilst it is generally accepted that hantaviruses have been tightly co-evolving with their hosts, Puumala virus (PUUV) evolutionary history is still controversial and so far has not been studied at the whole European level. This study attempts to reconstruct the phylogeographical spread of modern PUUV throughout Europe during the last postglacial period in the light of an upgraded dataset of complete PUUV small (S) segment sequences and by using most recent computational approaches. Taking advantage of the knowledge on the past migrations of its host, we identified at least three potential independent dispersal routes of PUUV during postglacial recolonization of Europe by the bank vole. From the Alpe-Adrian region (Balkan, Austria, and Hungary) to Western European countries (Germany, France, Belgium, and Netherland), and South Scandinavia. From the vicinity of Carpathian Mountains to the Baltic countries and to Poland, Russia, and Finland. The dissemination towards Denmark and North Scandinavia is more hypothetical and probably involved several independent streams from south and north Fennoscandia.

Evidence for both Intermittent and Persistent Compartmentalization of HIV-1 in the Female Genital Tract

HIV-1 has been shown to evolve independently in different anatomical compartments, but studies in the female genital tract have been inconclusive. Here, we examined evidence of compartmentalization using HIV-1 subtype C envelope (Env) glycoprotein genes (gp160) obtained from matched cervicovaginal lavage (CVL) and plasma samples over 2 to 3 years of infection. HIV-1 gp160 amplification from CVL was achieved for only 4 of 18 acutely infected women, and this was associated with the presence of proinflammatory cytokines and/or measurable viremia in the CVL. Maximum likelihood trees and divergence analyses showed that all four individuals had monophyletic compartment-specific clusters of CVL- and/or plasma-derived gp160 sequences at all or some time points. However, two participants (CAP177 and CAP217) had CVL gp160 diversity patterns that differed from those in plasma and showed restricted viral flow from the CVL. Statistical tests of compartmentalization revealed evidence of persistent compartment-specific gp160 evolution in CAP177, while in CAP217 this was intermittent. Lastly, we identified several Env sites that distinguished viruses in these two compartments; for CAP177, amino acid differences arose largely through positive selection, while insertions/deletions were more common in CAP217. In both cases these differences contributed to substantial charge changes spread across the Env. Our data indicate that, in some women, HIV-1 populations within the genital tract can have Env genetic features that differ from those of viruses in plasma, which could impact the sensitivity of viruses in the genital tract to vaginal microbicides and vaccine-elicited antibodies.IMPORTANCE Most HIV-1 infections in sub-Saharan Africa are acquired heterosexually through the genital mucosa. Understanding the properties of viruses replicating in the female genital tract, and whether these properties differ from those of more commonly studied viruses replicating in the blood, is therefore important. Using longitudinal CVL and plasma-derived sequences from four HIV-1 subtype C-infected women, we found fewer viral migrations from the genital tract to plasma than in the opposite direction, suggesting a mucosal sieve effect from the genital tract to the blood compartment. Evidence for both persistent and intermittent compartmentalization between the genital tract and plasma viruses during chronic infection was detected in two of four individuals, perhaps explaining previously conflicting findings. In cases where compartmentalization occurred, comparison of CVL- and plasma-derived HIV sequences indicated that distinct features of viral populations in the CVL may affect the efficacy of microbicides and vaccines designed to provide mucosal immunity.

Tracking virus outbreaks in the twenty-first century

Emerging viruses have the potential to impose substantial mortality, morbidity and economic burdens on human populations. Tracking the spread of infectious diseases to assist in their control has traditionally relied on the analysis of case data gathered as the outbreak proceeds. Here, we describe how many of the key questions in infectious disease epidemiology, from the initial detection and characterization of outbreak viruses, to transmission chain tracking and outbreak mapping, can now be much more accurately addressed using recent advances in virus sequencing and phylogenetics. We highlight the utility of this approach with the hypothetical outbreak of an unknown pathogen, ‘Disease X’, suggested by the World Health Organization to be a potential cause of a future major epidemic. We also outline the requirements and challenges, including the need for flexible platforms that generate sequence data in real-time, and for these data to be shared as widely and openly as possible.

This Review Article describes how recent advances in viral genome sequencing and phylogenetics have enabled key issues associated with outbreak epidemiology to be more accurately addressed, and highlights the requirements and challenges for generating, sharing and using such data when tackling a viral outbreak.

Characterising routes of H5N1 and H7N9 spread in China using Bayesian phylogeographical analysis

Avian influenza H5N1 subtype has caused a global public health concern due to its high pathogenicity in poultry and high case fatality rates in humans. The recently emerged H7N9 is a growing pandemic risk due to its sustained high rates of human infections, and recently acquired high pathogenicity in poultry. Here, we used Bayesian phylogeography on 265 H5N1 and 371 H7N9 haemagglutinin sequences isolated from humans, animals and the environment, to identify and compare migration patterns and factors predictive of H5N1 and H7N9 diffusion rates in China. H7N9 diffusion dynamics and predictor contributions differ from H5N1. Key determinants of spatial diffusion included: proximity between locations (for H5N1 and H7N9), and lower rural population densities (H5N1 only). For H7N9, additional predictors included low avian influenza vaccination rates, low percentage of nature reserves and high humidity levels. For both H5N1 and H7N9, we found viral migration rates from Guangdong to Guangxi and Guangdong to Hunan were highly supported transmission routes (Bayes Factor > 30). We show fundamental differences in wide-scale transmission dynamics between H5N1 and H7N9. Importantly, this indicates that avian influenza initiatives designed to control H5N1 may not be sufficient for controlling the H7N9 epidemic. We suggest control and prevention activities to specifically target poultry transportation networks between Central, Pan-Pearl River Delta and South-West regions.

On the importance of negative controls in viral landscape phylogeography

Phylogeographic reconstructions are becoming an established procedure to evaluate the factors that could impact virus spread. While a discrete phylogeographic approach can be used to test predictors of transition rates among discrete locations, alternative continuous phylogeographic reconstructions can also be exploited to investigate the impact of underlying environmental layers on the dispersal velocity of a virus. The two approaches are complementary tools for studying pathogens' spread, but in both cases, care must be taken to avoid misinterpretations. Here, we analyse rice yellow mottle virus (RYMV) sequence data from West and East Africa to illustrate how both approaches can be used to study the impact of environmental factors on the virus’ dispersal frequency and velocity. While it was previously reported that host connectivity was a major determinant of RYMV spread, we show that this was a false positive result due to the lack of appropriate negative controls. We also discuss and compare the phylodynamic tools currently available for investigating the impact of environmental factors on virus spread.

Tracking external introductions of HIV using phylodynamics reveals a major source of infections in rural KwaZulu-Natal, South Africa

Despite increasing access to antiretrovirals, HIV incidence in rural KwaZulu-Natal remains among the highest ever reported in Africa. While many epidemiological factors have been invoked to explain such high incidence, widespread human mobility and viral movement suggest that transmission between communities may be a major source of new infections. High cross-community transmission rates call into question how effective increasing the coverage of antiretroviral therapy locally will be at preventing new infections, especially if many new cases arise from external introductions. To help address this question, we use a phylodynamic model to reconstruct epidemic dynamics and estimate the relative contribution of local transmission versus external introductions to overall incidence in KwaZulu-Natal from HIV-1 phylogenies. By comparing our results with population-based surveillance data, we show that we can reliably estimate incidence from viral phylogenies once viral movement in and out of the local population is accounted for. Our analysis reveals that early epidemic dynamics were largely driven by external introductions. More recently, we estimate that 35 per cent (95% confidence interval: 20-60%) of new infections arise from external introductions. These results highlight the growing need to consider larger-scale regional transmission dynamics when designing and testing prevention strategies.

Phylodynamic assessment of intervention strategies for the West African Ebola virus outbreak

Genetic analyses have provided important insights into Ebola virus spread during the recent West African outbreak, but their implications for specific intervention scenarios remain unclear. Here, we address this issue using a collection of phylodynamic approaches. We show that long-distance dispersal events were not crucial for epidemic expansion and that preventing viral lineage movement to any given administrative area would, in most cases, have had little impact. However, major urban areas were critical in attracting and disseminating the virus: preventing viral lineage movement to all three capitals simultaneously would have contained epidemic size to one-third. We also show that announcements of border closures were followed by a significant but transient effect on international virus dispersal. By quantifying the hypothetical impact of different intervention strategies, as well as the impact of barriers on dispersal frequency, our study illustrates how phylodynamic analyses can help to address specific epidemiological and outbreak control questions.

During the last Ebola virus outbreak in West Africa, a large amount of viral genomic data was obtained. Here, Dellicour et al. use phylodynamic approaches to assess effect of intervention strategies such as border closures.

Global phylogeography and genetic diversity of the zoonotic tapeworm Echinococcus granulosus sensu stricto genotype G1

Echinococcus granulosus sensu stricto (s.s.) is the major cause of human cystic echinococcosis worldwide and is listed among the most severe parasitic diseases of humans. To date, numerous studies have investigated the genetic diversity and population structure of E. granulosus s.s. in various geographic regions. However, there has been no global study. Recently, using mitochondrial DNA, it was shown that E. granulosus s.s. G1 and G3 are distinct genotypes, but a larger dataset is required to confirm the distinction of these genotypes. The objectives of this study were to: (i) investigate the distinction of genotypes G1 and G3 using a large global dataset; and (ii) analyse the genetic diversity and phylogeography of genotype G1 on a global scale using near-complete mitogenome sequences. For this study, 222 globally distributed E. granulosus s.s. samples were used, of which 212 belonged to genotype G1 and 10 to G3. Using a total sequence length of 11,682 bp, we inferred phylogenetic networks for three datasets: E. granulosus s.s. (n = 222), G1 (n = 212) and human G1 samples (n = 41). In addition, the Bayesian phylogenetic and phylogeographic analyses were performed. The latter yielded several strongly supported diffusion routes of genotype G1 originating from Turkey, Tunisia and Argentina. We conclude that: (i) using a considerably larger dataset than employed previously, E. granulosus s.s. G1 and G3 are indeed distinct mitochondrial genotypes; (ii) the genetic diversity of E. granulosus s.s. G1 is high globally, with lower values in South America; and (iii) the complex phylogeographic patterns emerging from the phylogenetic and geographic analyses suggest that the current distribution of genotype G1 has been shaped by intensive animal trade.

Using Viral Gene Sequences to Compare and Explain the Heterogeneous Spatial Dynamics of Virus Epidemics

Rabies is an important zoonotic disease distributed worldwide. A key question in rabies epidemiology is the identification of factors that impact virus dispersion. Here we apply new analytical methods, based on phylogeographic reconstructions of viral lineage movement, to undertake a comparative evolutionary-epidemiological study of the spatial dynamics of rabies virus (RABV) epidemics in different hosts and habitats. We compiled RABV data sets from skunk, raccoon, bat and domestic dog populations in order to investigate the viral diffusivity of different RABV epidemics, and to detect and compare the environmental factors that impact the velocity of viral spread in continuous spatial landscapes. We build on a recently developed statistical framework that uses spatially- and temporally-referenced phylogenies. We estimate several spatial statistics of virus spread, which reveal a higher diffusivity of RABV in domestic dogs compared with RABV in other mammals. This finding is explained by subsequent analyses of environmental heterogeneity, which indicate that factors relating to human geography play a significant role in RABV dispersion in domestic dogs. More generally, our results suggest that human-related factors are important worldwide in explaining RABV dispersion in terrestrial host species. Our study shows that phylogenetically informed viral movements can be used to elucidate the factors that impact virus dispersal, opening new opportunities for a better understanding of the impact of host species and environmental conditions on the spatial dynamics of rapidly evolving populations.

Host Genetic Variation Does Not Determine Spatio-Temporal Patterns of European Bat 1 Lyssavirus

The majority of bat rabies cases in Europe are attributed to European bat 1 lyssavirus (EBLV-1), circulating mainly in serotine bats (Eptesicus serotinus). Two subtypes have been defined (EBLV-1a and EBLV-1b), each associated with a different geographical distribution. In this study, we undertake a comprehensive sequence analysis based on 80 newly obtained EBLV-1 nearly complete genome sequences from nine European countries over a 45-year period to infer selection pressures, rates of nucleotide substitution, and evolutionary time scale of these two subtypes in Europe. Our results suggest that the current lineage of EBLV-1 arose in Europe ∼600 years ago and the virus has evolved at an estimated average substitution rate of ∼4.19×10-5 subs/site/year, which is among the lowest recorded for RNA viruses. In parallel, we investigate the genetic structure of French serotine bats at both the nuclear and mitochondrial level and find that they constitute a single genetic cluster. Furthermore, Mantel tests based on interindividual distances reveal the absence of correlation between genetic distances estimated between viruses and between host individuals. Taken together, this indicates that the genetic diversity observed in our E. serotinus samples does not account for EBLV-1a and -1b segregation and dispersal in Europe.

The epidemic dynamics of hepatitis C virus subtypes 4a and 4d in Saudi Arabia

The relatedness between viral variants sampled at different locations through time can provide information pertinent to public health that cannot readily be obtained through standard surveillance methods. Here, we use virus genetic data to identify the transmission dynamics that drive the hepatitis C virus subtypes 4a (HCV4a) and 4d (HCV4d) epidemics in Saudi Arabia. We use a comprehensive dataset of newly generated and publicly available sequence data to infer the HCV4a and HCV4d evolutionary histories in a Bayesian statistical framework. We also introduce a novel analytical method for an objective assessment of the migration intensity between locations. We find that international host mobility patterns dominate over within country spread in shaping the Saudi Arabia HCV4a epidemic, while this may be different for the HCV4d epidemic. This indicates that the subtypes 4a and 4d burden can be most effectively reduced by combining the prioritized screening and treatment of Egyptian immigrants with domestic prevention campaigns. Our results highlight that the joint investigation of evolutionary and epidemiological processes can provide valuable public health information, even in the absence of extensive metadata information.

Spatiotemporal dynamics of HIV-1 transmission in France (1999-2014) and impact of targeted prevention strategies

Background

Characterizing HIV-1 transmission networks can be important in understanding the evolutionary patterns and geospatial spread of the epidemic. We reconstructed the broad molecular epidemiology of HIV from individuals with primary HIV-1 infection (PHI) enrolled in France in the ANRS PRIMO C06 cohort over 15 years.

Results

Sociodemographic, geographic, clinical, biological and pol sequence data from 1356 patients were collected between 1999 and 2014. Network analysis was performed to infer genetic relationships, i.e. clusters of transmission, between HIV-1 sequences. Bayesian coalescent-based methods were used to examine the temporal and spatial dynamics of identified clusters from different regions in France. We also evaluated the use of network information to target prevention efforts. Participants were mostly Caucasian (85.9%) and men (86.7%) who reported sex with men (MSM, 71.4%). Overall, 387 individuals (28.5%) were involved in clusters: 156 patients (11.5%) in 78 dyads and 231 participants (17%) in 42 larger clusters (median size: 4, range 3–41). Compared to individuals with single PHI (n = 969), those in clusters were more frequently men (95.9 vs 83%, p < 0.01), MSM (85.8 vs 65.6%, p < 0.01) and infected with CRF02_AG (20.4 vs 13.4%, p < 0.01). Reconstruction of viral migrations across time suggests that Paris area was the major hub of dissemination of both subtype B and CRF02_AG epidemics. By targeting clustering individuals belonging to the identified active transmission network before 2010, 60 of the 143 onward transmissions could have been prevented.

Conclusion

These analyses support the hypothesis of a recent and rapid rise of CRF02_AG within the French HIV-1 epidemic among MSM. Combined with a short turnaround time for sample processing, targeting prevention efforts based on phylogenetic monitoring may be an efficient way to deliver prevention interventions but would require near real time targeted interventions on the identified index cases and their partners.

Electronic supplementary material

The online version of this article (doi:10.1186/s12977-017-0339-4) contains supplementary material, which is available to authorized users.

Effect of different vaccination strategies on IBV QX population dynamics and clinical outbreaks

•

Two large scale molecular epidemiology studies performed in Italy and Spain.

•

The population dynamics trends differed between the two countries.

•

Relevant association between changes in vaccination strategies and viral population.

•

Strong association between viral population dynamics and outbreak frequency.

•

Hill’s criteria for causation were accomplished.

The extreme variability and rapid evolution of Infectious bronchitis virus (IBV) has always represented the key challenge for its control because of the limited cross-protection among different strains. Several experimental trials have proven a broadening of the protection spectrum when animals are vaccinated with multiple genotypes. Nevertheless, the conditions of vaccine administration in field are so different that the generalization of experimental results is, at least, questionable. In the present study a large scale epidemiological-phylodynamic approach was used to reconstruct the demographic history of the major field genotype (i.e. the QX one) circulating in Italy and Spain. These two countries were selected because, even if they share a comparable epidemiological scenario, the implemented vaccination protocols did not vary in Spain while changed dramatically in Italy over the time period considered. One hundred and ninety-five Italian and 98 Spanish non-recombinant sequences of the hyper-variable region of the S1 gene obtained between 2012 and 2016 were analyzed using a serial coalescent-based approach to reconstruct viral population history over time. While the IBV QX population dynamics remained constant in Spain, a much more complex pattern was evidenced in Italy; both in terms of viral population size and clinical outbreak frequency. Remarkably, a strong association with changes in vaccination strategies was recognized. This allowed demonstrating, by accomplishing all Hill’s criteria for causation, the cause-effect relationship between the vaccine administration/withdrawal and the variation in viral population dynamics and, above all, IBV related outbreaks. Thus, a robust confirmation about the efficacy of IBV vaccination in field conditions was provided. Additionally, the history herein reported testifies the primary importance of rigorously planning not only the intervention strategies but also their monitoring and evaluation.

Phylogeography of the current rabies viruses in Indonesia

Rabies is a major fatal zoonotic disease in Indonesia. This study was conducted to determine the recent dynamics of rabies virus (RABV) in various areas and animal species throughout Indonesia. A total of 27 brain samples collected from rabid animals of various species in Bali, Sumatra, Kalimantan, Sulawesi, Java, and Flores in 2008 to 2010 were investigated. The cDNA of the nucleoprotein gene from each sample was generated and amplified by one-step reverse transcription-PCR, after which the products were sequenced and analyzed. The symmetric substitution model of a Bayesian stochastic search variable selection extension of the discrete phylogeographic model of the social network was applied in BEAST ver. 1.7.5 software. The spatial dispersal was visualized in Cartographica using Spatial Phylogenetic Reconstruction of Evolutionary Dynamics. We demonstrated inter-island introduction and reintroduction, and dog was found to be the only source of infection of other animals. Ancestors of Indonesian RABVs originated in Java and its descendants were transmitted to Kalimantan, then further to Sumatra, Flores, and Bali. The Flores descendent was subsequently transmitted to Sulawesi and back to Kalimantan. The viruses found in various animal species were transmitted by the dog.

A high-precision rule-based extraction system for expanding geospatial metadata in GenBank records

OBJECTIVE

The metadata reflecting the location of the infected host (LOIH) of virus sequences in GenBank often lacks specificity. This work seeks to enhance this metadata by extracting more specific geographic information from related full-text articles and mapping them to their latitude/longitudes using knowledge derived from external geographical databases.

MATERIALS AND METHODS

We developed a rule-based information extraction framework for linking GenBank records to the latitude/longitudes of the LOIH. Our system first extracts existing geospatial metadata from GenBank records and attempts to improve it by seeking additional, relevant geographic information from text and tables in related full-text PubMed Central articles. The final extracted locations of the records, based on data assimilated from these sources, are then disambiguated and mapped to their respective geo-coordinates. We evaluated our approach on a manually annotated dataset comprising of 5728 GenBank records for the influenza A virus.

RESULTS

We found the precision, recall, and f-measure of our system for linking GenBank records to the latitude/longitudes of their LOIH to be 0.832, 0.967, and 0.894, respectively.

DISCUSSION

Our system had a high level of accuracy for linking GenBank records to the geo-coordinates of the LOIH. However, it can be further improved by expanding our database of geospatial data, incorporating spell correction, and enhancing the rules used for extraction.

CONCLUSION

Our system performs reasonably well for linking GenBank records for the influenza A virus to the geo-coordinates of their LOIH based on record metadata and information extracted from related full-text articles.

Detailed phylogenetic analysis of primate T-lymphotropic virus type 1 (PTLV-1) sequences from orangutans (Pongo pygmaeus) reveals new insights into the evolutionary history of PTLV-1 in Asia

While human T-lymphotropic virus type 1 (HTLV-1) originates from ancient cross-species transmission of simian T-lymphotropic virus type 1 (STLV-1) from infected nonhuman primates, much debate exists on whether the first HTLV-1 occurred in Africa, or in Asia during early human evolution and migration. This topic is complicated by a lack of representative Asian STLV-1 to infer PTLV-1 evolutionary histories. In this study we obtained new STLV-1 LTR and tax sequences from a wild-born Bornean orangutan (Pongo pygmaeus) and performed detailed phylogenetic analyses using both maximum likelihood and Bayesian inference of available Asian PTLV-1 and African STLV-1 sequences. Phylogenies, divergence dates and nucleotide substitution rates were co-inferred and compared using six different molecular clock calibrations in a Bayesian framework, including both archaeological and/or nucleotide substitution rate calibrations. We then combined our molecular results with paleobiogeographical and ecological data to infer the most likely evolutionary history of PTLV-1. Based on the preferred models our analyses robustly inferred an Asian source for PTLV-1 with cross-species transmission of STLV-1 likely from a macaque (Macaca sp.) to an orangutan about 37.9-48.9kya, and to humans between 20.3-25.5kya. An orangutan diversification of STLV-1 commenced approximately 6.4-7.3kya. Our analyses also inferred that HTLV-1 was first introduced into Australia ~3.1-3.7kya, corresponding to both genetic and archaeological changes occurring in Australia at that time. Finally, HTLV-1 appears in Melanesia at ~2.3-2.7kya corresponding to the migration of the Lapita peoples into the region. Our results also provide an important future reference for calibrating information essential for PTLV evolutionary timescale inference. Longer sequence data, or full genomes from a greater representation of Asian primates, including gibbons, leaf monkeys, and Sumatran orangutans are needed to fully elucidate these evolutionary dates and relationships using the model criteria suggested herein.

Explaining the geographic spread of emerging epidemics: a framework for comparing viral phylogenies and environmental landscape data

Background

Phylogenetic analysis is now an important tool in the study of viral outbreaks. It can reconstruct epidemic history when surveillance epidemiology data are sparse, and can indicate transmission linkages among infections that may not otherwise be evident. However, a remaining challenge is to develop an analytical framework that can test hypotheses about the effect of environmental variables on pathogen spatial spread. Recent phylogeographic approaches can reconstruct the history of virus dispersal from sampled viral genomes and infer the locations of ancestral infections. Such methods provide a unique source of spatio-temporal information, and are exploited here.

Results

We present and apply a new statistical framework that combines genomic and geographic data to test the impact of environmental variables on the mode and tempo of pathogen dispersal during emerging epidemics. First, the spatial history of an emerging pathogen is estimated using standard phylogeographic methods. The inferred dispersal path for each phylogenetic lineage is then assigned a “weight” using environmental data (e.g. altitude, land cover). Next, tests measure the association between each environmental variable and lineage movement. A randomisation procedure is used to assess statistical confidence and we validate this approach using simulated data. We apply our new framework to a set of gene sequences from an epidemic of rabies virus in North American raccoons. We test the impact of six different environmental variables on this epidemic and demonstrate that elevation is associated with a slower rabies spread in a natural population.

Conclusion

This study shows that it is possible to integrate genomic and environmental data in order to test hypotheses concerning the mode and tempo of virus dispersal during emerging epidemics.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0924-x) contains supplementary material, which is available to authorized users.

HIV-1 transmission between MSM and heterosexuals, and increasing proportions of circulating recombinant forms in the Nordic Countries

Increased knowledge about HIV-1 transmission dynamics in different transmission groups and geographical regions is fundamental for assessing and designing prevention efforts against HIV-1 spread. Since the first reported cases of HIV infection during the early 1980s, the HIV-1 epidemic in the Nordic countries has been dominated by HIV-1 subtype B and MSM transmission. HIV-1 pol sequences and clinical data of 51 per cent of all newly diagnosed HIV-1 infections in Sweden, Denmark, and Finland in the period 2000-2012 (N = 3,802) were analysed together with a large reference sequence dataset (N = 4,537) by trend analysis and phylogenetics. Analysis of the eight dominating subtypes and CRFs in the Nordic countries (A, B, C, D, G, CRF01_AE, CRF02_AG, and CRF06_cpx) showed that the subtype B proportion decreased while the CRF proportion increased over the study period. A majority (57 per cent) of the Nordic sequences formed transmission clusters, with evidence of mixing both geographically and between transmission groups. Detailed analyses showed multiple occasions of transmissions from MSM to heterosexuals and that active transmission clusters more often involved single than multiple Nordic countries. The strongest geographical link was between Denmark and Sweden. Finally, Denmark had a larger proportion of heterosexual domestic spread of HIV-1 subtype B (75 per cent) compared with Sweden (49 per cent) and Finland (57 per cent). We describe different HIV-1 transmission patterns between countries and transmission groups in a large geographical region. Our results may have implications for public health interventions in targeting HIV-1 transmission networks and identifying where to introduce such interventions.

Enterovirus Migration Patterns between France and Tunisia

The enterovirus (EV) types echovirus (E-) 5, E-9, and E-18, and coxsackievirus (CV-) A9 are infrequently reported in human diseases and their epidemiologic features are poorly defined. Virus transmission patterns between countries have been estimated with phylogenetic data derived from the 1D/VP1 and 3CD gene sequences of a sample of 74 strains obtained in France (2000–2012) and Tunisia (2011–2013) and from the publicly available sequences. The EV types (E-5, E-9, and E-18) exhibited a lower worldwide genetic diversity (respective number of genogroups: 4, 5, and 3) in comparison to CV-A9 (n = 10). The phylogenetic trees estimated with both 1D/VP1 and 3CD sequence data showed variations in the number of co-circulating lineages over the last 20 years among the four EV types. Despite the low number of genogroups in E-18, the virus exhibited the highest number of recombinant 3CD lineages (n = 10) versus 4 (E-5) to 8 (E-9). The phylogenies provided evidence of multiple transportation events between France and Tunisia involving E-5, E-9, E-18, and CV-A9 strains. Virus spread events between France and 17 other countries in five continents had high probabilities of occurrence as those between Tunisia and two European countries other than France. All transportation events were supported by BF values > 10. Inferring the source of virus transmission from phylogenetic data may provide insights into the patterns of sporadic and epidemic diseases caused by EVs.

Extracting transmission networks from phylogeographic data for epidemic and endemic diseases: Ebola virus in Sierra Leone, 2009 H1N1 pandemic influenza and polio in Nigeria

Background

Phylogeography improves our understanding of spatial epidemiology. However, application to practical problems requires choices among computational tools to balance statistical rigor, computational complexity, sensitivity to sampling strategy and interpretability.

Methods

We introduce a fast, heuristic algorithm to reconstruct partially-observed transmission networks (POTN) that combines features of phylogenetic and transmission tree approaches. We compare the transmission network generated by POTN with existing algorithms (BEAST and SeqTrack), and discuss the benefits and challenges of phylogeographic analysis on examples of epidemic and endemic diseases: Ebola virus, H1N1 pandemic influenza and polio.

Results

For the 2014 Sierra Leone Ebola virus outbreak and the 2009 H1N1 outbreak, all three methods provide similarly plausible transmission histories but differ in detail. For polio in northern Nigeria, we discuss performance trade-offs between the POTN and discrete phylogeography in BEAST and conclude that spatial history reconstruction is limited by under-sampling.

Conclusions

POTN is complementary to available tools on densely-sampled data, fails gracefully on under-sampled data and is scalable to accommodate larger datasets. We provide further evidence for the utility of phylogeography for understanding transmission networks of rapidly evolving epidemics. We propose simple heuristic criteria to identify how sampling rates and disease dynamics interact to determine fundamental limitations of phylogeographic inference.

Bayesian Inference Reveals Host-Specific Contributions to the Epidemic Expansion of Influenza A H5N1

Since its first isolation in 1996 in Guangdong, China, the highly pathogenic avian influenza virus (HPAIV) H5N1 has circulated in avian hosts for almost two decades and spread to more than 60 countries worldwide. The role of different avian hosts and the domestic-wild bird interface has been critical in shaping the complex HPAIV H5N1 disease ecology, but remains difficult to ascertain. To shed light on the large-scale H5N1 transmission patterns and disentangle the contributions of different avian hosts on the tempo and mode of HPAIV H5N1 dispersal, we apply Bayesian evolutionary inference techniques to comprehensive sets of hemagglutinin and neuraminidase gene sequences sampled between 1996 and 2011 throughout Asia and Russia. Our analyses demonstrate that the large-scale H5N1 transmission dynamics are structured according to different avian flyways, and that the incursion of the Central Asian flyway specifically was driven by Anatidae hosts coinciding with rapid rate of spread and an epidemic wavefront acceleration. This also resulted in long-distance dispersal that is likely to be explained by wild bird migration. We identify a significant degree of asymmetry in the large-scale transmission dynamics between Anatidae and Phasianidae, with the latter largely representing poultry as an evolutionary sink. A joint analysis of host dynamics and continuous spatial diffusion demonstrates that the rate of viral dispersal and host diffusivity is significantly higher for Anatidae compared with Phasianidae. These findings complement risk modeling studies and satellite tracking of wild birds in demonstrating a continental-scale structuring into areas of H5N1 persistence that are connected through migratory waterfowl.

Spatial and temporal epidemiological analysis in the Big Data era

Concurrent with global economic development in the last 50 years, the opportunities for the spread of existing diseases and emergence of new infectious pathogens, have increased substantially. The activities associated with the enormously intensified global connectivity have resulted in large amounts of data being generated, which in turn provides opportunities for generating knowledge that will allow more effective management of animal and human health risks. This so-called Big Data has, more recently, been accompanied by the Internet of Things which highlights the increasing presence of a wide range of sensors, interconnected via the Internet. Analysis of this data needs to exploit its complexity, accommodate variation in data quality and should take advantage of its spatial and temporal dimensions, where available. Apart from the development of hardware technologies and networking/communication infrastructure, it is necessary to develop appropriate data management tools that make this data accessible for analysis. This includes relational databases, geographical information systems and most recently, cloud-based data storage such as Hadoop distributed file systems. While the development in analytical methodologies has not quite caught up with the data deluge, important advances have been made in a number of areas, including spatial and temporal data analysis where the spectrum of analytical methods ranges from visualisation and exploratory analysis, to modelling. While there used to be a primary focus on statistical science in terms of methodological development for data analysis, the newly emerged discipline of data science is a reflection of the challenges presented by the need to integrate diverse data sources and exploit them using novel data- and knowledge-driven modelling methods while simultaneously recognising the value of quantitative as well as qualitative analytical approaches. Machine learning regression methods, which are more robust and can handle large datasets faster than classical regression approaches, are now also used to analyse spatial and spatio-temporal data. Multi-criteria decision analysis methods have gained greater acceptance, due in part, to the need to increasingly combine data from diverse sources including published scientific information and expert opinion in an attempt to fill important knowledge gaps. The opportunities for more effective prevention, detection and control of animal health threats arising from these developments are immense, but not without risks given the different types, and much higher frequency, of biases associated with these data.