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Phylodynamics is a set of population genetics tools that aim at reconstructing demographic history of a population based on molecular sequences of individuals sampled from the population of interest. One important task in phylodynamics is to estimate changes in (effective) population size. When applied to infectious disease sequences such estimation of population size trajectories can provide information about changes in the number of infections. To model changes in the number of infected individuals, current phylodynamic methods use non-parametric approaches, parametric approaches, and stochastic modeling in conjunction with likelihood-free Bayesian methods. The first class of methods yields results that are hard-to-interpret epidemiologically. The second class of methods provides estimates of important epidemiological parameters, such as infection and removal/recovery rates, but ignores variation in the dynamics of infectious disease spread. The third class of methods is the most advantageous statistically, but relies on computationally intensive particle filtering techniques that limits its applications. We propose a Bayesian model that combines phylodynamic inference and stochastic epidemic models, and achieves computational tractability by using a linear noise approximation (LNA) --- a technique that allows us to approximate probability densities of stochastic epidemic model trajectories. LNA opens the door for using modern Markov chain Monte Carlo tools to approximate the joint posterior distribution of the disease transmission parameters and of high dimensional vectors describing unobserved changes in the stochastic epidemic model compartment sizes (e.g., numbers of infectious and susceptible individuals). We apply our estimation technique to Ebola genealogies estimated using viral genetic data from the 2014 epidemic in Sierra Leone and Liberia., Comment: 43 pages, 6 figures in the main text

Metagenomic studies have uncovered an abundance of novel viruses by looking beyond hosts of obvious public health or economic interest. The discovery of conserved genes in viruses infecting geographically and phylogenetically diverse hosts has provided important evolutionary context for human and animal pathogens. However, the resulting viral genomes are often incomplete, and analyses largely characterize the distribution of viruses over their dynamics. Here, we show how the accumulated data of metagenomic studies can be integrated to reveal geographic and evolutionary dynamics in a case study ofOrthomyxoviridae, the family of RNA viruses containing influenza virus. First, we use sequences of the orthomyxovirid Wǔhàn mosquito virus 6 to track the global migrations of its host. We then look at overall orthomyxovirus genome evolution, finding significant gene gain and loss across members of the family, especially in the surface proteins responsible for cell and host tropism. We find that the surface protein of Wǔhàn mosquito virus 6 exhibits accelerated non-synonymous evolution suggestive of antigenic evolution, and an entire quaranjavirid group bearing highly diverged surface proteins. Finally we quantify the progress of orthomyxovirus discovery and forecast that many highly divergedOrthomyxoviridaemembers remain to be found. We argue that continued metagenomic studies will be fruitful for understanding the dynamics, evolution, ecology of viruses and their hosts, regardless of whether novel viruses are actually identified or not, as long as study designs allowing for the resolution of complete viral genomes are employed.

Significance Genetic recombination processes, such as reassortment, make it complex or impossible to use standard phylogenetic and phylodynamic methods. This is due to the fact that the shared evolutionary history of individuals has to be represented by a phylogenetic network instead of a tree. We therefore require novel approaches that allow us to coherently model these processes and that allow us to perform inference in the presence of such processes. Here, we introduce an approach to infer reassortment networks of segmented viruses using a Markov chain Monte Carlo approach. Our approach allows us to study different aspects of the reassortment process and allows us to show fitness benefits of reassortment events in seasonal human influenza viruses., Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment patterns of different human influenza datasets, we find large differences in reassortment rates across different human influenza viruses. Additionally, we find that reassortment events predominantly occur on selectively fitter parts of reassortment networks showing that on a population level, reassortment positively contributes to the fitness of human influenza viruses.

In spring 2021, an increasing number of infections was observed caused by the hitherto rarely described SARS-CoV-2 variant A.27 in south-west Germany. From December 2020 to June 2021 this lineage has been detected in 31 countries. Phylogeographic analyses of A.27 sequences obtained from national and international databases reveal a global spread of this lineage through multiple introductions from its inferred origin in Western Africa. Variant A.27 is characterized by a mutational pattern in the spike gene that includes the L18F, L452R and N501Y spike amino acid substitutions found in various variants of concern but lacks the globally dominant D614G. Neutralization assays demonstrate an escape of A.27 from convalescent and vaccine-elicited antibody-mediated immunity. Moreover, the therapeutic monoclonal antibody Bamlanivimab and partially the REGN-COV2 cocktail fail to block infection by A.27. Our data emphasize the need for continued global monitoring of novel lineages because of the independent evolution of new escape mutations. ispartof: NATURE COMMUNICATIONS vol:13 issue:1 ispartof: location:England status: published

The global increase in species richness toward the tropics across continents and taxonomic groups, referred to as the latitudinal diversity gradient, stimulated the formulation of many hypotheses to explain the underlying mechanisms of this pattern. We evaluate several of these hypotheses to explain spatial diversity patterns in a butterfly family, the Nymphalidae, by assessing the contributions of speciation, extinction, and dispersal, and also the extent to which these processes differ among regions at the same latitude. We generate a time-calibrated phylogeny containing 2,866 nymphalid species (~45% of extant diversity). Neither speciation nor extinction rate variations consistently explain the latitudinal diversity gradient among regions because temporal diversification dynamics differ greatly across longitude. The Neotropical diversity results from low extinction rates, not high speciation rates, and biotic interchanges with other regions are rare. Southeast Asia is also characterized by a low speciation rate but, unlike the Neotropics, is the main source of dispersal events through time. Our results suggest that global climate change throughout the Cenozoic, combined with tropical niche conservatism, played a major role in generating the modern latitudinal diversity gradient of nymphalid butterflies., F.L.C is supported by an “Investissements d’Avenir” grant managed by the Agence Nationale de la Recherche (CEBA, ref. ANR-10-LABX-25-01). D.J.L. was supported by grants DEB-1541557 from NSF and WW-227R-17 from the National Geographic Society. R.I.V.W. was supported by Leverhulme Trust emeritus programme. M.E. was supported by an ATIP grant, a grant from the Human Frontier Science Program (RGP0014/2016) and a grant from the French National Research Agency (ANR CLEARWING ANR-16-CE02-0012). E.O.A. was supported by Sigma-Xi (G20100315153261), Center for Systematic Entomology and the Council of the Linnean Society and the Systematics Association for the Systematics Research Fund. S.N. was supported by the Swedish Research Council (2015-04218 and 2019-03441). P.M.M. was supported by a Czech Science Foundation grant (Junior GAČR, 20-18566Y). R.V. was supported by projects PID2019-107078GB-I00 / AEI / 10.13039/501100011033 (Agencia Estatal de Investigación) and 2017-SGR-991 (Generalitat de Catalunya). N.W. acknowledges support by the Swedish Research Council (2015-04441) and a start-up grant from the Department of Biology, Lund University.

More than a year after the first identification of severe acute respiratory syndrome coron-avirus 2 (SARS-CoV-2) as the causative agent of the 2019 coronavirus disease (COVID-19) in China, the emergence and spread of genomic variants of this virus through travel raise concerns regarding the introduction of lineages in previously unaffected regions, requiring adequate containment strate-gies. Concomitantly, such introductions fuel worries about a possible increase in transmissibility and disease severity, as well as a possible decrease in vaccine efficacy. Military personnel are frequently deployed on missions around the world. As part of a COVID-19 risk mitigation strategy, Belgian Armed Forces that engaged in missions and operations abroad were screened (7683 RT-qPCR tests), pre-and post-mission, for the presence of SARS-CoV-2, including the identification of viral lineages. Nine distinct viral genotypes were identified in soldiers returning from operations in Niger, the Democratic Republic of the Congo, Afghanistan, and Mali. The SARS-CoV-2 variants belonged to major clades 19B, 20A, and 20B (Nextstrain nomenclature), and included “variant of interest” B.1.525, “variant under monitoring” A.27, as well as lineages B.1.214, B.1, B.1.1.254, and A (pangolin nomenclature), some of which are internationally monitored due to the specific mutations they har-bor. Through contact tracing and phylogenetic analysis, we show that isolation and testing policies implemented by the Belgian military command appear to have been successful in containing the influx and transmission of these distinct SARS-CoV-2 variants into military and civilian populations., SCOPUS: ar.j, info:eu-repo/semantics/published

Many high-income countries have met the SARS-CoV-2 pandemic with overwhelming sequencing resources and have identified numerous distinct lineages, including some with notably altered biology. Over a year into the pandemic following unprecedented reductions in worldwide human mobility, distinct introduced lineages of SARS-CoV-2 without sequenced antecedents are increasingly discovered in high-income countries as a result of ongoing SARS-CoV-2 genomic surveillance initiatives. We here describe one such SARS-CoV-2 lineage, carrying many mutations and deletions in the spike protein shared with widespread variants of concern (VOCs), including E484K, S477N and deletions HV69Δ, Y144Δ, and LLA241/243Δ. This lineage – designated B.1.620 – is known to circulate in Lithuania and has now been found in several European states, but also in increasing numbers in central Africa owing to important recent increases in genome sequencing efforts on the continent. We provide evidence of likely ongoing local transmission of B.1.620 in Lithuania, France, Germany, Spain, Belgium and the Central African Republic. We describe the suite of mutations this lineage carries, its potential to be resistant to neutralising antibodies, travel histories for a subset of the European cases, and evidence of local B.1.620 transmission in Europe. We make a case for the likely Central African origin of this lineage by providing travel records as well as the outcomes of carefully crafted phylogenetic and phylogeographic inference methodologies, the latter of which is able to exploit individual travel histories recorded for infected travellers having entered different European countries.

Mosquitoes are major infectious disease-carrying vectors. Assessment of current and future risks associated with the mosquito population requires knowledge of the full repertoire of pathogens they carry, including novel viruses, as well as their blood meal sources. Unbiased metatranscriptomic sequencing of individual mosquitoes offers a straightforward, rapid and quantitative means to acquire this information. Here, we profile 148 diverse wild-caught mosquitoes collected in California and detect sequences from eukaryotes, prokaryotes, 24 known and 46 novel viral species. Importantly, sequencing individuals greatly enhanced the value of the biological information obtained. It allowed us to a) speciate host mosquito, b) compute the prevalence of each microbe and recognize a high frequency of viral co-infections, c) associate animal pathogens with specific blood meal sources, and d) apply simple co-occurrence methods to recover previously undetected components of highly prevalent segmented viruses. In the context of emerging diseases, where knowledge about vectors, pathogens, and reservoirs is lacking, the approaches described here can provide actionable information for public health surveillance and intervention decisions.

BackgroundLower respiratory tract infections (LRTI) are a leading cause of critical illness and mortality in mechanically ventilated children; however, the pathogenic microbes frequently remain unknown. We combined traditional diagnostics with metagenomic next generation sequencing (mNGS) to evaluate the cause of LRTI in critically ill children.MethodsWe conducted a prospective, multicentre cohort study of critically ill children aged 31 days to 17 years with respiratory failure requiring mechanical ventilation (>72 h) in the USA. By combining bacterial culture and upper respiratory viral PCR testing with mNGS of tracheal aspirate collected from all patients within 24 h of intubation, we determined the prevalence, age distribution, and seasonal variation of viral and bacterial respiratory pathogens detected by either method in children with or without LRTI.FindingsBetween Feb 26, 2015, and Dec 31, 2017, of the 514 enrolled patients, 397 were eligible and included in the study (276 children with LRTI and 121 with no evidence of LRTI). A presumptive microbiological cause was identified in 255 (92%) children with LRTI, with respiratory syncytial virus (127 [46%]), Haemophilus influenzae (70 [25%]), and Moraxella catarrhalis (65 [24%]) being most prevalent. mNGS identified uncommon pathogens including Ureaplasma parvum and Bocavirus. Co-detection of viral and bacterial pathogens occurred in 144 (52%) patients. Incidental carriage of potentially pathogenic microbes occurred in 82 (68%) children without LRTI, with rhinovirus (30 [25%]) being most prevalent. Respiratory syncytial virus (p

Double synonyms in the genetic code can be used as a tool to test competing hypotheses regarding ambigrammatic narnavirus genomes. Applying the analysis to recent observations of Culex narnavirus 1 and Zhejiang mosquito virus 3 ambigrammatic viruses indicates that the open reading frame on the complementary strand of the segment coding for RNA-dependent RNA polymerase does not code for a functional protein. Culex narnavirus 1 has been shown to possess a second segment, also ambigrammatic, termed ‘Robin’. We find a comparable segment for Zhejiang mosquito virus 3, a moderately diverged relative of Culex narnavirus 1. Our analysis of Robin polymorphisms suggests that its reverse open reading frame also does not code for a functional protein. We make a hypothesis about its role.

The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states, and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics., Genomic and epidemiological analyses provide a clearer picture of one of the earliest SARS-CoV-2 superspreader events in the United States in accelerating transmission, with a single introduction of the virus being responsible for most cases during this period.

The latitudinal diversity gradient (LDG) is arguably one of the most striking patterns in nature. The global increase in species richness toward the tropics across continents and taxonomic groups stimulated the formulation of many hypotheses to explain the underlying mechanisms of this pattern. We evaluated several of these hypotheses to explain spatial diversity patterns in the butterfly family, Nymphalidae, by assessing the contributions of speciation, extinction, and dispersal to the LDG, and also the extent to which these processes differ among regions at the same latitude. We generated a new, time-calibrated phylogeny of Nymphalidae based on 10 gene fragments and containing ca. 2,800 species (∼45% of extant diversity). Neither speciation nor extinction rate variations consistently explain the LDG among regions because temporal diversification dynamics differ greatly across longitude. For example, we found that Neotropical nymphalid diversity results from low extinction rates, not high speciation rates, and that biotic interchanges with other regions were rare. Southeast Asia was also characterized by a low speciation rate but, unlike the Neotropics, was the main source of dispersal events through time. Our results suggest that global climate change throughout the Cenozoic, particularly during the Eocene-Oligocene transition, combined with the conserved ancestral tropical niches, played a major role in generating the modern LDG of butterflies.

Population dynamics can be inferred from genetic sequence data by using phylodynamic methods. These methods typically quantify the dynamics in unstructured populations or assume migration rates and effective population sizes to be constant through time in structured populations. When considering rates to vary through time in structured populations, the number of parameters to infer increases rapidly and the available data might not be sufficient to inform these. Additionally, it is often of interest to know what predicts these parameters rather than knowing the parameters themselves. Here, we introduce a method to infer the predictors for time-varying migration rates and effective population sizes by using a generalized linear model (GLM) approach under the marginal approximation of the structured coalescent. Using simulations, we show that our approach is able to reliably infer the model parameters and its predictors from phylogenetic trees. Furthermore, when simulating trees under the structured coalescent, we show that our new approach outperforms the discrete trait GLM model. We then apply our framework to a previously described Ebola virus dataset, where we infer the parameters and its predictors from genome sequences while accounting for phylogenetic uncertainty. We infer weekly cases to be the strongest predictor for effective population size and geographic distance the strongest predictor for migration. This approach is implemented as part of the BEAST2 package MASCOT, which allows us to jointly infer population dynamics, i.e. the parameters and predictors, within structured populations, the phylogenetic tree, and evolutionary parameters., Virus Evolution, 5 (2), ISSN:2057-1577

Anelloviruses are a ubiquitous component of healthy human viromes and remain highly prevalent after being acquired early in life. The full extent of "anellome" diversity and its evolutionary dynamics remain unexplored. We employed in-depth sequencing of blood-transfusion donor(s)-recipient pairs coupled with public genomic resources for a large-scale assembly of anellovirus genomes and used the data to characterize global and personal anellovirus diversity through time. The breadth of the anellome is much greater than previously appreciated, and individuals harbor unique anellomes and transmit lineages that can persist for several months within a diverse milieu of endemic host lineages. Anellovirus sequence diversity is shaped by extensive recombination at all levels of divergence, hindering traditional phylogenetic analyses. Our findings illuminate the transmission dynamics and vast diversity of anelloviruses and set the foundation for future studies to characterize their biology.

The 2013–2016 epidemic of Ebola virus disease in West Africa was of unprecedented magnitude and changed our perspective on this lethal but sporadically emerging virus. This outbreak also marked the beginning of large-scale real-time molecular epidemiology. Herein, we show how evolutionary analyses of Ebola virus genome sequences provided key insights into virus origins, evolution, and spread during the epidemic. We provide basic scientists, epidemiologists, medical practitioners, and other outbreak responders with an enhanced understanding of the utility and limitations of pathogen genomic sequencing. This will be crucially important in our attempts to track and control future infectious disease outbreaks.

Significance Middle East respiratory syndrome (MERS) is a zoonotic disease of global health concern, and dromedary camels are the source of human infection. Although Africa has the largest number of dromedary camels, and MERS-coronavirus (MERS-CoV) is endemic in these camels, locally acquired zoonotic MERS is not reported from Africa. However, little is known of the genetic or phenotypic characterization of MERS-CoV from Africa. In this study we characterize MERS-CoV from Burkina Faso, Nigeria, Morocco, and Ethiopia. We demonstrate viral genetic and phenotypic differences in viruses from West Africa, which may be relevant to differences in zoonotic potential, highlighting the need for studies of MERS-CoV at the animal–human interface., Middle East respiratory syndrome coronavirus (MERS-CoV) causes a zoonotic respiratory disease of global public health concern, and dromedary camels are the only proven source of zoonotic infection. Although MERS-CoV infection is ubiquitous in dromedaries across Africa as well as in the Arabian Peninsula, zoonotic disease appears confined to the Arabian Peninsula. MERS-CoVs from Africa have hitherto been poorly studied. We genetically and phenotypically characterized MERS-CoV from dromedaries sampled in Morocco, Burkina Faso, Nigeria, and Ethiopia. Viruses from Africa (clade C) are phylogenetically distinct from contemporary viruses from the Arabian Peninsula (clades A and B) but remain antigenically similar in microneutralization tests. Viruses from West (Nigeria, Burkina Faso) and North (Morocco) Africa form a subclade, C1, that shares clade-defining genetic signatures including deletions in the accessory gene ORF4b. Compared with human and camel MERS-CoV from Saudi Arabia, virus isolates from Burkina Faso (BF785) and Nigeria (Nig1657) had lower virus replication competence in Calu-3 cells and in ex vivo cultures of human bronchus and lung. BF785 replicated to lower titer in lungs of human DPP4-transduced mice. A reverse genetics-derived recombinant MERS-CoV (EMC) lacking ORF4b elicited higher type I and III IFN responses than the isogenic EMC virus in Calu-3 cells. However, ORF4b deletions may not be the major determinant of the reduced replication competence of BF785 and Nig1657. Genetic and phenotypic differences in West African viruses may be relevant to zoonotic potential. There is an urgent need for studies of MERS-CoV at the animal–human interface.

Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic virus originating in camels that has been causing significant mortality and morbidity in humans in the Arabian Peninsula. The epidemiology of the virus remains poorly understood, with hospital outbreaks, isolated cases with known exposure to camels and apparent community transmission occurring simultaneously. While traditional and seroepidemiological studies have been employed extensively throughout the epidemic, viral sequence data have not been utilised to their full potential in understanding transmission patterns within the outbreak. Here we use existing MERS-CoV sequence data to explore the phylodynamics of the virus in two of its known major hosts, humans and camels. We employ structured coalescent models to show that long-term MERS-CoV evolution occurs exclusively in camels, whereas humans act as a transient, and ultimately terminal host. By analysing the distribution of human outbreak cluster sizes and zoonotic introduction times we show that human outbreaks in the Arabian peninsula are driven by seasonally varying zoonotic transfer of viruses from camels. Without heretofore unseen evolution of host tropism, MERS-CoV is unlikely to become endemic in humans.

Here we release draft genome sequences of Zika virus (ZIKV) that were sequenced from PCR-positive diagnostic specimens collected by the United States Virgin Islands Department of Health (USVI DoH) as part of their ongoing response to the ZIKV outbreak. We will use these sequences to conduct a genomic epidemiological study of ZIKV transmission in the USVI. We are releasing these genomes in the hope that they are useful for those individuals involved in the public health response to ZIKV and to other groups working to understand Zika virus transmission and evolution.

Evolution of Ebola virus over time The high rate of mortality in the current Ebola epidemic has made it difficult for researchers to collect samples of the virus and study its evolution. Gire et al. describe Ebola epidemiology on the basis of 99 whole-genome sequences, including samples from 78 affected individuals. The authors analyzed changes in the viral sequence and conclude that the current outbreak probably resulted from the spread of the virus from central Africa in the past decade. The outbreak started from a single transmission event from an unknown animal reservoir into the human population. Two viral lineages from Guinea then spread from person to person into Sierra Leone. Science , this issue p. 1369

Zika virus (ZIKV) is currently causing an unprecedented pandemic linked to severe congenital syndromes1,2. In July 2016, mosquito-borne ZIKV transmission was first reported in the continental United States and since then, hundreds of locally acquired infections have been described3. To gain insights into the timing, source, and likely route(s) of introduction into the United States, we tracked the virus from its first detection in Miami, Florida by direct sequencing of ZIKV genomes from infected patients and Aedes aegypti mosquitoes. We detected at least four distinct ZIKV introductions and estimate that 11-52 introductions contributed to the outbreak in Florida. Furthermore, our data suggests that ZIKV transmission likely started in the spring of 2016 - several months before initial detection. By analyzing epidemiological, surveillance, and genetic data, we discovered that several spatially distinct ZIKV transmission zones were likely portions of the same outbreak, rather than isolated events. Our analyses show that most introductions are linked to the Caribbean, which is supported by the high incidence rates and traffic, especially via cruises, from the region into Miami. By comparing mosquito abundance and travel capacity across the United States, we find that southern Florida is especially vulnerable to ZIKV introductions and at risk of repeat occurrences. By tracking the virus from its initial introduction into the United States, we provide a deeper understanding of how ZIKV initiates and sustains transmission in new regions.

SummaryThe 2013-2016 epidemic of Ebola virus disease in West Africa was of unprecedented magnitude, duration and impact. Extensive collaborative sequencing projects have produced a large collection of over 1600 Ebola virus genomes, representing over 5% of known cases, unmatched for any single human epidemic. In this comprehensive analysis of this entire dataset, we reconstruct in detail the history of migration, proliferation and decline of Ebola virus throughout the region. We test the association of geography, climate, administrative boundaries, demography and culture with viral movement among 56 administrative regions. Our results show that during the outbreak viral lineages moved according to a classic ‘gravity’ model, with more intense migration between larger and more proximate population centers. Notably, we find that despite a strong attenuation of international dispersal after border closures, localized cross-border transmission beforehand had already set the seeds for an international epidemic, rendering these measures relatively ineffective in curbing the epidemic. We use this empirical evidence to address why the epidemic did not spread into neighboring countries, showing that although these regions were susceptible to developing significant outbreaks, they were also at lower risk of viral introductions. Finally, viral genome sequence data uniquely reveals this large epidemic to be a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help inform approaches to intervention in such epidemics in the future.

BACKGROUND Several patients with Ebola virus disease (EVD) managed in the United States have received ZMapp monoclonal antibodies, TKM-Ebola small interfering RNA, brincidofovir, and/or convalescent plasma as investigational therapeutics. METHODS To investigate whether treatment selected for Ebola virus (EBOV) mutations conferring resistance, viral sequencing was performed on RNA extracted from clinical blood specimens from patients with EVD following treatment, and putative viral targets were analyzed. RESULTS We observed no major or minor EBOV mutations within regions targeted by therapeutics. CONCLUSIONS This small subset of patients and clinical specimens suggests that evolution of resistance is not a direct consequence of antiviral treatment. As EVD antiviral treatments are introduced into wider use, it is essential that continuous viral full-genome surveillance is performed, to monitor for the emergence of escape mutations.