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The chronic infection hypothesis for novel SARS-CoV-2 variant emergence is increasingly gaining credence following the appearance of Omicron. Here we investigate intrahost evolution and genetic diversity of lineage B.1.517 during a SARS-CoV-2 chronic infection lasting for 471 days (and still ongoing) with consistently recovered infectious virus and high viral loads. During the infection, we found an accelerated virus evolutionary rate translating to 35 nucleotide substitutions per year, approximately two-fold higher than the global SARS-CoV-2 evolutionary rate. This intrahost evolution led to the emergence and persistence of at least three genetically distinct genotypes suggesting the establishment of spatially structured viral populations continually reseeding different genotypes into the nasopharynx. Finally, using unique molecular indexes for accurate intrahost viral sequencing, we tracked the temporal dynamics of genetic diversity to identify advantageous mutations and highlight hallmark changes for chronic infection. Our findings demonstrate that untreated chronic infections accelerate SARS-CoV-2 evolution, ultimately providing opportunity for the emergence of genetically divergent and potentially highly transmissible variants as seen with Delta and Omicron.
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The emergence of the SARS-CoV-2 Delta variant of concern (lineage B.1.617.2) in late 2020 resulted in a new wave of infections in many countries across the world, where it often became the dominant lineage in a relatively short amount of time. We here report on a novel genomic surveillance effort in Rwanda in the time period from June to September 2021, leading to 201 SARS-CoV-2 genomes being generated, the majority of which were identified as the Delta variant of concern. We show that in Rwanda, the Delta variant almost completely replaced the previously dominant A.23.1 and B.1.351 (Beta) lineages in a matter of weeks, and led to a tripling of the total number of COVID-19 infections and COVID-19-related fatalities over the course of only three months. We estimate that Delta in Rwanda had an average growth rate advantage of 0.034 (95% CI 0.025-0.045) per day over A.23.1, and of 0.022 (95% CI 0.012-0.032) over B.1.351. Phylogenetic analysis reveals the presence of at least seven local Delta transmission clusters, with two of these clusters occurring close to the border with the Democratic Republic of the Congo, and another cluster close to the border with Tanzania. A smaller Delta cluster of infections also appeared close to the border with Uganda, illustrating the importance of monitoring cross-border traffic to limit the spread between Rwanda and its neighboring countries. We discuss our findings against a background of increased vaccination efforts in Rwanda, and also discuss a number of breakthrough infections identified during our study. Concluding, our study has added an important collection of data to the available genomes for the Eastern Africa region, with the number of Delta infections close to the border with neighboring countries highlighting the need to further strengthen genomic surveillance in the region to obtain a better understanding of the impact of border crossings on lowering the epidemic curve in Rwanda.
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The first SARS-CoV-2 variant of concern (VOC) to be designated was lineage B.1.1.7, later labelled by the World Health Organisation (WHO) as Alpha. Originating in early Autumn but discovered in December 2020, it spread rapidly and caused large waves of infections worldwide. The Alpha variant is notable for being defined by a long ancestral phylogenetic branch with an increased evolutionary rate, along which only two sequences have been sampled. Alpha genomes comprise a well-supported monophyletic clade within which the evolutionary rate is more typical of SARS-CoV-2. The Alpha epidemic continued to grow despite the continued restrictions on social mixing across the UK, and the imposition of new restrictions, in particular the English national lockdown in November 2020. While these interventions succeeded in reducing the absolute number of cases, the impact of these non-pharmaceutical interventions was predominantly to drive the decline of the SARS-CoV-2 lineages which preceded Alpha. We investigate the only two sampled sequences that fall on the branch ancestral to Alpha. We find that one is likely to be a true intermediate sequence, providing information about the order of mutational events that led to Alpha. We explore alternate hypotheses that can explain how Alpha acquired a large number of mutations yet remained largely unobserved in a region of high genomic surveillance: an under-sampled geographical location, a non-human animal population, or a chronically-infected individual. We conclude that the last hypothesis provides the best explanation of the observed behaviour and dynamics of the variant, although we find that the individual need not be immunocompromised, as persistently-infected immunocompetent hosts also display a higher within-host rate of evolution. Finally, we compare the ancestral branches and mutation profiles of other VOCs to each other, and identify that Delta appears to be an outlier both in terms of the genomic locations of its defining mutations, and its lack of rapid evolutionary rate on the ancestral branch. As new variants, such as Omicron, continue to evolve (potentially through similar mechanisms) it remains important to investigate the origins of other variants to identify ways to potentially disrupt their evolution and emergence.
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The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases1-3. The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions4,5. Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations; however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter-regional travel drove Deltas nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Deltas invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.
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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants respectively1-3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng Province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, predicted to influence antibody neutralization and spike function4. Here, we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity.
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The scale of data produced during the SARS-CoV-2 pandemic has been unprecedented, with more than 5 million sequences shared publicly at the time of writing. This wealth of sequence data provides important context for interpreting local outbreaks. However, placing sequences of interest into national and international context is difficult given the size of the global dataset. Often outbreak investigations and genomic surveillance efforts require running similar analyses again and again on the latest dataset and producing reports. We developed civet (cluster investigation and virus epidemiology tool) to aid these routine analyses and facilitate virus outbreak investigation and surveillance. Civet can place sequences of interest in the local context of background diversity, resolving the query into different catchments and presenting the phylogenetic results alongside metadata in an interactive, distributable report. Civet can be used on a fine scale for clinical outbreak investigation, for local surveillance and cluster discovery, and to routinely summarise the virus diversity circulating on a national level. Civet reports have helped researchers and public health bodies feedback genomic information in the appropriate context within a timeframe that is useful for public health.
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We present evidence for multiple independent origins of recombinant SARS-CoV-2 viruses sampled from late 2020 and early 2021 in the United Kingdom. Their genomes carry single nucleotide polymorphisms and deletions that are characteristic of the B.1.1.7 variant of concern, but lack the full complement of lineage-defining mutations. Instead, the remainder of their genomes share contiguous genetic variation with non-B.1.1.7 viruses circulating in the same geographic area at the same time as the recombinants. In four instances there was evidence for onward transmission of a recombinant-origin virus, including one transmission cluster of 45 sequenced cases over the course of two months. The inferred genomic locations of recombination breakpoints suggest that every community-transmitted recombinant virus inherited its spike region from a B.1.1.7 parental virus, consistent with a transmission advantage for B.1.1.7s set of mutations.
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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for coronavirus disease 19 (COVID-19), is a single-stranded positive-sense ribonucleic acid (RNA) virus that typically undergoes one to two single nucleotide mutations per month. COVID-19 continues to spread globally, with case fatality and test positivity rates often linked to locally circulating strains of SARS-CoV-2. Furthermore, mutations in this virus, in particular those occurring in the spike protein (involved in the virus binding to the host epithelial cells) have potential implications in current vaccination efforts. In Rwanda, more than twenty thousand cases have been confirmed as of March 14th 2021, with a case fatality rate of 1.4% and test positivity rate of 2.3% while the recovery rate is at 91.9%. Rwanda started its genomic surveillance efforts, taking advantage of pre-existing research projects and partnerships, to ensure early detection of SARS-CoV-2 variants and to potentially contain the spread of variants of concern (VOC). As a result of this initiative, we here present 203 SARS-CoV-2 whole genome sequences analyzed from strains circulating in the country from May 2020 to February 2021. In particular, we report a shift in variant distribution towards the newly emerging sub-lineage A.23.1 that is currently dominating. Furthermore, we report the detection of the first Rwandan cases of the VOCs, B.1.1.7 and B.1.351, among incoming travelers tested at Kigali International Airport. We also discuss the potential impact of COVID-19 control measures established in the country to control the spread of the virus. To assess the importance of viral introductions from neighboring countries and local transmission, we exploit available individual travel history metadata to inform spatio-temporal phylogeographic inference, enabling us to take into account infections from unsampled locations during the time frame of interest. We uncover an important role of neighboring countries in seeding introductions into Rwanda, including those from which no genomic sequences are currently available or that no longer report positive cases. Our results point to the importance of systematically screening all incoming travelers, regardless of the origin of their travels, as well as regional collaborations for durable response to COVID-19.
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The SARS-CoV-2 lineage B.1.1.7, now designated Variant of Concern 202012/01 (VOC) by Public Health England, originated in the UK in late Summer to early Autumn 2020. We examine epidemiological evidence for this VOC having a transmission advantage from several perspectives. First, whole genome sequence data collected from community-based diagnostic testing provides an indication of changing prevalence of different genetic variants through time. Phylodynamic modelling additionally indicates that genetic diversity of this lineage has changed in a manner consistent with exponential growth. Second, we find that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S-gene target failures (SGTF) in community-based diagnostic PCR testing. Third, we examine growth trends in SGTF and non-SGTF case numbers at local area level across England, and show that the VOC has higher transmissibility than non-VOC lineages, even if the VOC has a different latent period or generation time. Available SGTF data indicate a shift in the age composition of reported cases, with a larger share of under 20 year olds among reported VOC than non-VOC cases. Fourth, we assess the association of VOC frequency with independent estimates of the overall SARS-CoV-2 reproduction number through time. Finally, we fit a semi-mechanistic model directly to local VOC and non-VOC case incidence to estimate the reproduction numbers over time for each. There is a consensus among all analyses that the VOC has a substantial transmission advantage, with the estimated difference in reproduction numbers between VOC and non-VOC ranging between 0.4 and 0.7, and the ratio of reproduction numbers varying between 1.4 and 1.8. We note that these estimates of transmission advantage apply to a period where high levels of social distancing were in place in England; extrapolation to other transmission contexts therefore requires caution.
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The second SARS virus, SARS-CoV-2, emerged in December 2019, and within a month was globally distributed. It was first introduced into Scotland in February 2020 associated with returning travellers and visitors. By March it was circulating in communities across the UK, and to control COVID-19 cases, and prevent overwhelming of the National Health Service (NHS), a lockdown was introduced on 23rd March 2020 with a restriction of peoples movements. To augment the public health efforts a large-scale genome epidemiology effort (as part of the COVID-19 Genomics UK (COG-UK) consortium) resulted in the sequencing of over 5000 SARS-CoV-2 genomes by 18th August 2020 from Scottish cases, about a quarter of the estimated number of cases at that time. Here we quantify the geographical origins of the first wave introductions into Scotland from abroad and other UK regions, the spread of these SARS-CoV-2 lineages to different regions within Scotland (defined at the level of NHS Health Board) and the effect of lockdown on virus success. We estimate that approximately 300 introductions seeded lineages in Scotland, with around 25% of these lineages composed of more than five viruses, but by June circulating lineages were reduced to low levels, in line with low numbers of recorded positive cases. Lockdown was, thus, associated with a dramatic reduction in infection numbers and the extinguishing of most virus lineages. Unfortunately since the summer cases have been rising in Scotland in a second wave, with >1000 people testing positive on a daily basis, and hospitalisation of COVID-19 cases on the rise again. Examining the available Scottish genome data from the second wave, and comparing it to the first wave, we find that while some UK lineages have persisted through the summer, the majority of lineages responsible for the second wave are new introductions from outside of Scotland and many from outside of the UK. This indicates that, while lockdown in Scotland is directly linked with the first wave case numbers being brought under control, travel-associated imports (mostly from Europe or other parts of the UK) following the easing of lockdown are responsible for seeding the current epidemic population. This demonstrates that the impact of stringent public health measures can be compromised if following this, movements from regions of high to low prevalence are not minimised.
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The UKs COVID-19 epidemic during early 2020 was one of worlds largest and unusually well represented by virus genomic sampling. Here we reveal the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 SARS-CoV-2 genomes, including 26,181 from the UK sampled throughout the countrys first wave of infection. Using large-scale phylogenetic analyses, combined with epidemiological and travel data, we quantify the size, spatio-temporal origins and persistence of genetically-distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown were larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whilst lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.
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Global dispersal and increasing frequency of the SARS-CoV-2 Spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of Spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large data set, well represented by both Spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the Spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant.
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Spatiotemporal bias in genome sequence sampling can severely confound phylogeographic inference based on discrete trait ancestral reconstruction. This has impeded our ability to accurately track the emergence and spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic. Despite the availability of unprecedented numbers of SARS-CoV-2 genomes on a global scale, evolutionary reconstructions are hindered by the slow accumulation of sequence divergence over its relatively short transmission history. When confronted with these issues, incorporating additional contextual data may critically inform phylodynamic reconstructions. Here, we present a new approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2, while also including global air transportation data. We demonstrate that including travel history data for each SARS-CoV-2 genome yields more realistic reconstructions of virus spread, particularly when travelers from undersampled locations are included to mitigate sampling bias. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations in the analyses. Our reconstructions reinforce specific transmission hypotheses suggested by the inclusion of travel history data, but also suggest alternative routes of virus migration that are plausible within the epidemiological context but are not apparent with current sampling efforts. Although further research is needed to fully examine the performance of our travel-aware phylogeographic analyses with unsampled diversity and to further improve them, they represent multiple new avenues for directly addressing the colossal issue of sample bias in phylogeographic inference.
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Accurate understanding of the global spread of emerging viruses is critically important for public health response and for anticipating and preventing future outbreaks. Here, we elucidate when, where and how the earliest sustained SARS-CoV-2 transmission networks became established in Europe and the United States (US). Our results refute prior findings erroneously linking cases in January 2020 with outbreaks that occurred weeks later. Instead, rapid interventions successfully prevented onward transmission of those early cases in Germany and Washington State. Other, later introductions of the virus from China to both Italy and Washington State founded the earliest sustained European and US transmission networks. Our analyses reveal an extended period of missed opportunity when intensive testing and contact tracing could have prevented SARS-CoV-2 from becoming established in the US and Europe.
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COVID-19 is caused by the SARS-CoV-2 coronavirus and was first reported in central China in December 2019. Extensive molecular surveillance in Guangdong, Chinas most populous province, during early 2020 resulted in 1,388 reported RNA positive cases from 1.6 million tests. In order to understand the molecular epidemiology and genetic diversity of SARS-CoV-2 in China we generated 53 genomes from infected individuals in Guangdong using a combination of metagenomic sequencing and tiling amplicon approaches. Combined epidemiological and phylogenetic analyses indicate multiple independent introductions to Guangdong, although phylogenetic clustering is uncertain due to low virus genetic variation early in the pandemic. Our results illustrate how the timing, size and duration of putative local transmission chains were constrained by national travel restrictions and by the provinces large-scale intensive surveillance and intervention measures. Despite these successes, COVID-19 surveillance in Guangdong is still required as the number of cases imported from other countries is increasing. HighlightsO_LI1.6 million molecular diagnostic tests identified 1,388 SARS-CoV-2 infections in Guangdong Province, China, by 19th March 2020 C_LIO_LIVirus genomes can be recovered using a variety of sequencing approaches from a range of patient samples. C_LIO_LIGenomic analyses reveal multiple virus importations into Guangdong Province, resulting in genetically distinct clusters that require careful interpretation. C_LIO_LILarge-scale epidemiological surveillance and intervention measures were effective in interrupting community transmission in Guangdong C_LI
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The ongoing pandemic spread of a novel human coronavirus, SARS-COV-2, associated with severe pneumonia disease (COVID-19), has resulted in the generation of thousands of virus genome sequences. The rate of genome generation is unprecedented, yet there is currently no coherent nor accepted scheme for naming the expanding phylogenetic diversity of SARS-CoV-2. We present a rational and dynamic virus nomenclature that uses a phylogenetic framework to identify those lineages that contribute most to active spread. Our system is made tractable by constraining the number and depth of hierarchical lineage labels and by flagging and declassifying virus lineages that become unobserved and hence are likely inactive. By focusing on active virus lineages and those spreading to new locations this nomenclature will assist in tracking and understanding the patterns and determinants of the global spread of SARS-CoV-2.
