Search

Our understanding of the still unfolding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic would have been extremely limited without the study of the genetics and evolution of this new human coronavirus. Large-scale genome-sequencing efforts have provided close to real-time tracking of the global spread and diversification of SARS-CoV-2 since its entry into the human population in late 2019. These data have underpinned analysis of its origins, epidemiology, and adaptations to the human population: principally immune evasion and increasing transmissibility. SARS-CoV-2, despite being a new human pathogen, was highly capable of human-to-human transmission. During its rapid spread in humans, SARS-CoV-2 has evolved independent new forms, the so-called "variants of concern," that are better optimized for human-to-human transmission. The most important adaptation of the bat coronavirus progenitor of both SARS-CoV-1 and SARS-CoV-2 for human infection (and other mammals) is the use of the angiotensin-converting enzyme 2 (ACE2) receptor. Relaxed structural constraints provide plasticity to SARS-related coronavirus spike protein permitting it to accommodate significant amino acid replacements of antigenic consequence without compromising the ability to bind to ACE2. Although the bulk of research has justifiably concentrated on the viral spike protein as the main determinant of antigenic evolution and changes in transmissibility, there is accumulating evidence for the contribution of other regions of the viral proteome to virus-host interaction. Whereas levels of community transmission of recombinants compromising genetically distinct variants are at present low, when divergent variants cocirculate, recombination between SARS-CoV-2 clades is being detected, increasing the risk that viruses with new properties emerge. Applying computational and machine learning methods to genome sequence data sets to generate experimentally verifiable predictions will serve as an early warning system for novel variant surveillance and will be important in future vaccine planning. Omicron, the latest SARS-CoV-2 variant of concern, has focused attention on step change antigenic events, "shift," as opposed to incremental "drift" changes in antigenicity. Both an increase in transmissibility and antigenic shift in Omicron led to it readily causing infections in the fully vaccinated and/or previously infected. Omicron's virulence, while reduced relative to the variant of concern it replaced, Delta, is very much premised on the past immune exposure of individuals with a clear signal that boosted vaccination protects from severe disease. Currently, SARS-CoV-2 has proven itself to be a dangerous new human respiratory pathogen with an unpredictable evolutionary capacity, leading to a risk of future variants too great not to ensure all regions of the world are screened by viral genome sequencing, protected through available and affordable vaccines, and have non-punitive strategies in place for detecting and responding to novel variants of concern.

Pre-existing SARS-CoV-2-reactive T cells have been identified in SARS-CoV-2-unexposed individuals, potentially modulating COVID-19 and vaccination outcomes. Here, we provide evidence that functional cross-reactive memory CD4 + T cell immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is established in early childhood, mirroring early seroconversion with seasonal human coronavirus OC43. Humoral and cellular immune responses against OC43 and SARS-CoV-2 were assessed in SARS-CoV-2-unexposed children (paired samples at age two and six) and adults (age 26 to 83). Pre-existing SARS-CoV-2-reactive CD4 + T cell responses targeting spike, nucleocapsid, and membrane were closely linked to the frequency of OC43-specific memory CD4 + T cells in childhood. The functional quality of the cross-reactive memory CD4 + T cell responses targeting SARS-CoV-2 spike, but not nucleocapsid, paralleled OC43-specific T cell responses. OC43-specific antibodies were prevalent already at age two. However, they did not increase further with age, contrasting with the antibody magnitudes against HKU1 (β-coronavirus), 229E and NL63 (α-coronaviruses), rhinovirus, Epstein–Barr virus (EBV), and influenza virus, which increased after age two. The quality of the memory CD4 + T cell responses peaked at age six and subsequently declined with age, with diminished expression of interferon (IFN)-γ, interleukin (IL)-2, tumor necrosis factor (TNF), and CD38 in late adulthood. Age-dependent qualitative differences in the pre-existing SARS-CoV-2-reactive T cell responses may reflect the ability of the host to control coronavirus infections and respond to vaccination.

A group convened and led by the Virus Evolution Working Group of the World Health Organization reports on its deliberations and announces a naming scheme that will enable clear communication about SARS-CoV-2 variants of interest and concern.

BackgroundWorldwide outbreaks of enterovirus D68 (EV-D68) in 2014 and 2016 have caused serious respiratory and neurological disease.MethodsWe collected samples from several European countries during the 2018 out-break and determined 53 near full-length genome (‘whole genome’) sequences. These sequences were combined with 718 whole genome and 1,987 VP1-gene publicly available sequences.FindingsIn 2018, circulating strains clustered into multiple subgroups in the B3 and A2 subclades, with different phylogenetic origins. Clusters in subclade B3 emerged from strains circulating primarily in the US and Europe in 2016, though some had deeper roots linking to Asian strains, while clusters in A2 traced back to strains detected in East Asia in 2015-2016. In 2018, all sequences from the USA formed a distinct subgroup, containing only three non-US samples. Alongside the varied origins of seasonal strains, we found that diversification of these variants begins up to 18 months prior to the first diagnostic detection during a EV-D68 season. EV-D68 displays strong signs of continuous antigenic evolution and all 2018 A2 strains had novel patterns in the putative neutralizing epitopes in the BC- and DE-loops. The pattern in the BC-loop of the USA B3 subgroup had not been detected on that continent before. Patients with EV-D68 in subclade A2 were significantly older than patients with a B3 subclade virus. In contrast to other subclades, the age distribution of A2 is distinctly bimodal and was found primarily among children and in the elderly.InterpretationWe hypothesize that EV-D68’s rapid evolution of surface proteins, extensive diversity, and high rate of geographic mixing could be explained by substantial reinfection of adults.FundingUniversity of Basel and Swedish Foundation for Research and Development in Medical Microbiology

Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 SARS-CoV-2 genomes from Switzerland in 2020 - the 6th largest effort globally. Using a representative subset of these data, we estimated viral introductions to Switzerland and their persistence over the course of 2020. We contrast these estimates with simple null models representing the absence of certain public health measures. We show that Switzerland’s border closures de-coupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86 - 98% reduction in introductions during Switzerland’s strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Finally, we quantified local transmission dynamics once introductions into Switzerland occurred, using a novel phylodynamic model. We find that transmission slowed 35 – 63% upon outbreak detection in summer 2020, but not in fall. This finding may indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics.One Sentence SummaryPhylogenetic and phylodynamic methods quantify the drop in case introductions and local transmission with implementation of public health measures.

Purpose of review To discuss the recent HIV phylogenetic analyses examining HIV transmission patterns among and within risk groups. Recent findings Phylodynamic analysis has recently been applied to multiple HIV outbreaks among people who inject drugs to determine whether HIV transmission is ongoing. Large-scale analyses of datasets of HIV sequences collected for drug-resistance testing provide population-level insights into transmission patterns. One focus across world regions has been to investigate whether age-disparity is a driver of HIV transmission. In sub-Saharan Africa, researchers have examined transmission between heterosexuals and MSM and between high prevalence fishing communities and inland communities. In the US and the UK, cryptic risk groups such as nondisclosed MSM and the partners of transgender women are increasingly being uncovered based on their position in densely sampled molecular transmission networks. Summary Analysis of HIV genetic sequence can resolve viral transmission patterns between risk groups at unprecedented scales and levels of detail. Future research should focus on understanding the effect of missing data on inferences and the biases of different methods. Uncovering groups and patterns obscured from traditional epidemiolocal analyses is exciting but should not compromise the privacy of the groups in question.

Several SARS-CoV-2 variants of concern (VOC) are spreading rapidly in different regions of the world. The underlying mechanisms behind their transmission advantage remain unclear. We measured viral load in 950 individuals and found that infections with variant Alpha exhibit a higher viral load and longer viral shedding compared to non-VOC. We then used a transmission model to analyze the spread of variant Alpha in Geneva, Switzerland, and variant Beta in South Africa. We estimated that Alpha is either associated with a 37% (95% compatibility interval, CI: 25–63%) increase in transmissibility or a 51% (95% CI: 32–80%) increase of the infectious duration, or a combination of the two mechanisms. Assuming 50% immune evasion for Beta, we estimated a 23% (95% CI: 10–37%) increase in transmissibility or a 38% (95% CI: 15–78%) increase of the infectious duration for this variant. Beta is expected to outgrow Alpha in regions where the level of naturally acquired immunity from previously circulating variants exceeds 20% to 40%. Close monitoring of Alpha and Beta in regions with different levels of immunity will help to anticipate the global spread of these and future variants.

With the emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants that may increase transmissibility and/or cause escape from immune responses, there is an urgent need for the targeted surveillance of circulating lineages. It was found that the B.1.1.7 (also 501Y.V1) variant, first detected in the United Kingdom, could be serendipitously detected by the Thermo Fisher TaqPath COVID-19 PCR assay because a key deletion in these viruses, spike Δ69–70, would cause a “spike gene target failure” (SGTF) result. However, a SGTF result is not definitive for B.1.1.7, and this assay cannot detect other variants of concern (VOC) that lack spike Δ69–70, such as B.1.351 (also 501Y.V2), detected in South Africa, and P.1 (also 501Y.V3), recently detected in Brazil. We identified a deletion in the ORF1a gene (ORF1a Δ3675–3677) in all 3 variants, which has not yet been widely detected in other SARS-CoV-2 lineages. Using ORF1a Δ3675–3677 as the primary target and spike Δ69–70 to differentiate, we designed and validated an open-source PCR assay to detect SARS-CoV-2 VOC. Our assay can be rapidly deployed in laboratories around the world to enhance surveillance for the local emergence and spread of B.1.1.7, B.1.351, and P.1., Surveillance for SARS-CoV-2 variants is very important, but sequencing is not always practical or affordable. This study presents a multiplex qPCR that is able to distinguish among different SARS-CoV-2 variants of concern that are currently circulating.

Tools, rules and incentives are buckling under the flood of coronavirus genome sequences — to help control the pandemic, researchers need new approaches. Tools, rules and incentives are buckling under the flood of coronavirus genome sequences — to help control the pandemic, researchers need new approaches.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein (S) plays critical roles in host cell entry. Non-synonymous substitutions affecting S are not uncommon and have become fixed in a number of SARS-CoV-2 lineages. A subset of such mutations enable escape from neutralizing antibodies or are thought to enhance transmission through mechanisms such as increased affinity for the cell entry receptor, angiotensin-converting enzyme 2 (ACE2). Independent genomic surveillance programs based in New Mexico and Louisiana contemporaneously detected the rapid rise of numerous clade 20G (lineage B.1.2) infections carrying a Q677P substitution in S. The variant was first detected in the US on October 23, yet between 01 Dec 2020 and 19 Jan 2021 it rose to represent 27.8% and 11.3% of all SARS-CoV-2 genomes sequenced from Louisiana and New Mexico, respectively. Q677P cases have been detected predominantly in the south central and southwest United States; as of 03 Feb 2021, GISAID data show 499 viral sequences of this variant from the USA. Phylogenetic analyses revealed the independent evolution and spread of at least six distinct Q677H sub-lineages, with first collection dates ranging from mid-August to late November 2020. Four 677H clades from clade 20G (B.1.2), 20A (B.1.234), and 20B (B.1.1.220, and B.1.1.222) each contain roughly 100 or fewer sequenced cases, while a distinct pair of clade 20G clusters are represented by 754 and 298 cases, respectively. Although sampling bias and founder effects may have contributed to the rise of S:677 polymorphic variants, the proximity of this position to the polybasic cleavage site at the S1/S2 boundary are consistent with its potential functional relevance during cell entry, suggesting parallel evolution of a trait that may confer an advantage in spread or transmission. Taken together, our findings demonstrate simultaneous convergent evolution, thus providing an impetus to further evaluate S:677 polymorphisms for effects on proteolytic processing, cell tropism, and transmissibility.

Recent reports suggest that some SARS-CoV-2 genetic variants, such as B.1.1.7, might be more transmissible and are quickly spreading around the world. As the emergence of more transmissible variants could exacerbate the pandemic, we provide public health guidance for increased surveillance and measures to reduce community transmission.

The rapid spread of the SARS-CoV-2 lineages B.1.1.7 (N501Y.V1) throughout the UK, B.1.351 (N501Y.V2) in South Africa, and P.1 (B.1.1.28.1; N501Y.V3) in Brazil has led to the definition of variants of concern (VoCs) and recommendations by the European Center for Disease Prevention and Control (ECDC) and World Health Organization (WHO) for lineage specific surveillance. In Switzerland, during the last weeks of December 2020, we established a nationwide screening protocol across multiple laboratories, focusing first on epidemiological definitions based on travel history and the S gene dropout in certain diagnostic systems. In January 2021, we validated and implemented an N501Y-specific PCR to rapidly screen for VoCs, which are then confirmed using amplicon sequencing or whole genome sequencing (WGS). A total of 3492 VoCs have been identified since the detection of the first Swiss case in October 2020, with 1370 being B1.1.7, 61 B.1.351, and none P.1. The remaining 2061 cases of VoCs have been described without further lineage specification. In this paper, we describe the nationwide coordination and implementation process across laboratories, public health institutions, and researchers, the first results of our N501Y-specific variant screening, and the phylogenetic analysis of all available WGS data in Switzerland, that together identified the early introduction events and subsequent community spreading of the VoCs.

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 evolutionary mechanisms by which SARS-CoV-2 viruses adapt to mammalian hosts and, potentially, undergo antigenic evolution depend on the ways genetic variation is generated and selected within and between individual hosts. Using domestic cats as a model, we show that SARS-CoV-2 consensus sequences remain largely unchanged over time within hosts, while dynamic sub-consensus diversity reveals processes of genetic drift and weak purifying selection. We further identify a notable variant at amino acid position 655 in Spike (H655Y), which was previously shown to confer escape from human monoclonal antibodies. This variant arises rapidly and persists at intermediate frequencies in index cats. It also becomes fixed following transmission in two of three pairs. These dynamics suggest this site may be under positive selection in this system and illustrate how a variant can quickly arise and become fixed in parallel across multiple transmission pairs. Transmission of SARS-CoV-2 in cats involved a narrow bottleneck, with new infections founded by fewer than ten viruses. In RNA virus evolution, stochastic processes like narrow transmission bottlenecks and genetic drift typically act to constrain the overall pace of adaptive evolution. Our data suggest that here, positive selection in index cats followed by a narrow transmission bottleneck may have instead accelerated the fixation of S H655Y, a potentially beneficial SARS-CoV-2 variant. Overall, our study suggests species- and context-specific adaptations are likely to continue to emerge. This underscores the importance of continued genomic surveillance for new SARS-CoV-2 variants as well as heightened scrutiny for signatures of SARS-CoV-2 positive selection in humans and mammalian model systems., Author summary Through ongoing human adaptation, spill-back events from other animal intermediates, or with the distribution of vaccines and therapeutics, the landscape of SARS-CoV-2 genetic variation is certain to change. The evolutionary mechanisms by which SARS-CoV-2 will continue to adapt to mammalian hosts depend on genetic variation generated within and between hosts. Here, using domestic cats as a model, we show that within-host SARS-CoV-2 genetic variation is predominantly influenced by genetic drift and purifying selection. Transmission of SARS-CoV-2 between hosts is defined by a narrow transmission bottleneck, involving 2–5 viruses. We further identify a notable variant at amino acid position 655 in Spike (H655Y), which arises rapidly and is transmitted in cats. Spike H655Y has been previously shown to confer escape from human monoclonal antibodies and is currently found in over 1,000 human sequences. Overall, our study suggests species- and context-specific adaptations are likely to continue to emerge, underscoring the importance of continued genomic surveillance in humans and non-human mammalian hosts.

Objectives The four seasonal coronaviruses 229E, NL63, OC43, and HKU1 are frequent causes of respiratory infections and show annual and seasonal variation. Increased understanding about these patterns could be informative about the epidemiology of SARS-CoV-2. Methods Results from PCR diagnostics for the seasonal coronaviruses, and other respiratory viruses, were obtained for 55,190 clinical samples analyzed at the Karolinska University Hospital, Stockholm, Sweden, between 14 September 2009 and 2 April 2020. Results Seasonal coronaviruses were detected in 2130 samples (3.9 %) and constituted 8.1 % of all virus detections. OC43 was most commonly detected (28.4 % of detections), followed by NL63 (24.0 %), HKU1 (17.6 %), and 229E (15.3 %). The overall fraction of positive samples was similar between seasons, but at species level there were distinct biennial alternating peak seasons for the Alphacoronaviruses, 229E and NL63, and the Betacoronaviruses, OC43 and HKU1, respectively. The Betacoronaviruses peaked earlier in the winter season (Dec-Jan) than the Alphacoronaviruses (Feb-Mar). Coronaviruses were detected across all ages, but diagnostics were more frequently requested for paediatric patients than adults and the elderly. OC43 and 229E incidence was relatively constant across age strata, while that of NL63 and HKU1 decreased with age. Conclusions Both the Alphacoronaviruses and Betacoronaviruses showed alternating biennial winter incidence peaks, which suggests some type of immune mediated interaction. Symptomatic reinfections in adults and the elderly appear relatively common. Both findings may be of relevance for the epidemiology of SARS-CoV-2.

Summary and statement of need The analysis of human pathogens requires a diverse collection of bioinformatics tools. These tools include standard genomic and phylogenetic software and custom software developed to handle the relatively numerous and short genomes of viruses and bacteria. Researchers increasingly depend on the outputs of these tools to infer transmission dynamics of human diseases and make actionable recommendations to public health officials (Black et al., 2020; Gardy et al., 2015). In order to enable real-time analyses of pathogen evolution, bioinformatics tools must scale rapidly with the number of samples and be flexible enough to adapt to a variety of questions and organisms. To meet these needs, we developed Augur, a bioinformatics toolkit designed for phylogenetic analyses of human pathogens.

Cross-reactive CD4+ T cells that recognize severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are more commonly detected in the peripheral blood of unexposed individuals compared with SARS-CoV-2–reactive CD8+ T cells. However, large numbers of memory CD8+ T cells reside in tissues, feasibly harboring localized SARS-CoV-2–specific immune responses. To test this idea, we performed a comprehensive functional and phenotypic analysis of virus-specific T cells in tonsils, a major lymphoid tissue site in the upper respiratory tract, and matched peripheral blood samples obtained from children and adults before the emergence of COVID-19 (coronavirus disease 2019). We found that SARS-CoV-2–specific memory CD4+ T cells could be found at similar frequencies in the tonsils and peripheral blood in unexposed individuals, whereas functional SARS-CoV-2–specific memory CD8+ T cells were almost only detectable in the tonsils. Tonsillar SARS-CoV-2–specific memory CD8+ T cells displayed a follicular homing and tissue-resident memory phenotype, similar to tonsillar Epstein-Barr virus–specific memory CD8+ T cells, but were functionally less potent than other virus-specific memory CD8+ T cell responses. The presence of preexisting tissue-resident memory CD8+ T cells in unexposed individuals could potentially enable rapid sentinel immune responses against SARS-CoV-2. Title in Web of Science: Identification of resident memory CD8(+) T cells with functional specificity for SARS-CoV-2 in unexposed oropharyngeal lymphoid tissue

With the emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants that may increase transmissibility and/or cause escape from immune responses, there is an urgent need for the targeted surveillance of circulating lineages. It was found that the B.1.1.7 (also 501Y.V1) variant, first detected in the United Kingdom, could be serendipitously detected by the Thermo Fisher TaqPath Coronavirus Disease 2019 (COVID-19) PCR assay because a key deletion in these viruses, spike Δ69-70, would cause a "spike gene target failure" (SGTF) result. However, a SGTF result is not definitive for B.1.1.7, and this assay cannot detect other variants of concern (VOC) that lack spike Δ69-70, such as B.1.351 (also 501Y.V2), detected in South Africa, and P.1 (also 501Y.V3), recently detected in Brazil. We identified a deletion in the ORF1a gene (ORF1a Δ3675-3677) in all 3 variants, which has not yet been widely detected in other SARS-CoV-2 lineages. Using ORF1a Δ3675-3677 as the primary target and spike Δ69-70 to differentiate, we designed and validated an open-source PCR assay to detect SARS-CoV-2 VOC. Our assay can be rapidly deployed in laboratories around the world to enhance surveillance for the local emergence and spread of B.1.1.7, B.1.351, and P.1.

A variant of SARS-CoV-2 emerged in early summer 2020, presumably in Spain, and has since spread to multiple European countries. The variant was first observed in Spain in June and has been at frequencies above 40% since July. Outside of Spain, the frequency of this variant has increased from very low values prior to 15th July to 40-70% in Switzerland, Ireland, and the United Kingdom in September. It is also prevalent in Norway, Latvia, the Netherlands, and France. Little can be said about other European countries because few recent sequences are available. Sequences in this cluster (20A.EU1) differ from ancestral sequences at 6 or more positions, including the mutation A222V in the spike protein and A220V in the nucleoprotein. We show that this variant was exported from Spain to other European countries multiple times and that much of the diversity of this cluster in Spain is observed across Europe. It is currently unclear whether this variant is spreading because of a transmission advantage of the virus or whether high incidence in Spain followed by dissemination through tourists is sufficient to explain the rapid rise in multiple countries., This work was supported by the SNF through grant numbers 31CA30 196046 (to RAN, EBH) and 31CA30 196267 and core funding by the University of Basel. SeqCOVID-SPAIN is funded by the Instituto de Salud Carlos III project COV20/00140, Spanish National Research Council and ERC StG 638553 to IC.

Following its emergence in late 2019, SARS-CoV-2 has caused a global pandemic resulting in unprecedented efforts to reduce transmission and develop therapies and vaccines (WHO Emergency Committee, 2020; Zhu et al., 2020). Rapidly generated viral genome sequences have allowed the spread of the virus to be tracked via phylogenetic analysis (Hadfield et al., 2018; Pybus et al., 2020; Worobey et al., 2020). While the virus spread globally in early 2020 before borders closed, intercontinental travel has since been greatly reduced, allowing continent-specific variants to emerge. However, within Europe travel resumed in the summer of 2020, and the impact of this travel on the epidemic is not well understood. Here we report on a novel SARS-CoV-2 variant, 20A.EU1, that emerged in Spain in early summer, and subsequently spread to multiple locations in Europe, accounting for the majority of sequences by autumn. We find no evidence of increased transmissibility of this variant, but instead demonstrate how rising incidence in Spain, resumption of travel across Europe, and lack of effective screening and containment may explain the variant’s success. Despite travel restrictions and quarantine requirements, we estimate 20A.EU1 was introduced hundreds of times to countries across Europe by summertime travellers, likely undermining local efforts to keep SARS-CoV-2 cases low. Our results demonstrate how genomic surveillance is critical to understanding how travel can impact SARS-CoV-2 transmission, and thus for informing future containment strategies as travel resumes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 35 million people globally, with more than 1 million deaths recorded by WHO as of Oct 12, 2020. As a second wave of COVID-19 affects Europe, and with winter approaching, we need clear communication about the risks posed by COVID-19 and effective strategies to combat them. Here, we share our view of the current evidence-based consensus on COVID-19.

Pathogen genomes provide insights into their evolution and epidemic spread. We sequenced 1,439 SARS-CoV-2 genomes from Switzerland, representing 3-7% of all confirmed cases per week. Using these data, we demonstrate that no one lineage became dominant, pointing against evolution towards general lower virulence. On an epidemiological level, we report no evidence of cryptic transmission before the first confirmed case. We find many early viral introductions from Germany, France, and Italy and many recent introductions from Germany and France. Over the summer, we quantify the number of non-traceable infections stemming from introductions, quantify the effective reproductive number, and estimate the degree of undersampling. Our framework can be applied to quantify evolution and epidemiology in other locations or for other pathogens based on genomic data.One Sentence SummaryWe quantify SARS-CoV-2 spread in Switzerland based on genome sequences from our nation-wide sequencing effort.

ObjectivesThe four seasonal coronaviruses 229E, NL63, OC43, and HKU1 are frequent causes of respiratory infections and show annual and seasonal variation. Increased understanding about these patterns could be informative about the epidemiology of SARS-CoV-2.MethodsResults from PCR diagnostics for the seasonal coronaviruses, and other respiratory viruses, were obtained for 55,190 clinical samples analysed at the Karolinska University Hospital, Stockholm, Sweden, between 14 September 2009 and 2 April 2020.ResultsSeasonal coronaviruses were detected in 2,130 samples (3.9%) and constituted 8.1% of all virus detections. OC43 was most commonly detected (28.4% of detections), followed by NL63 (24.0%), HKU1 (17.6%), and 229E (15.3%). The overall fraction of positive samples was similar between seasons, but at species level there were distinct biennial alternating peak seasons for the Alphacoronaviruses, 229E and NL63, and the Betacoronaviruses, OC43 and HKU1, respectively. The Betacoronaviruses peaked earlier in the winter season (Dec-Jan) than the Alphacoronaviruses (Feb-Mar). Coronaviruses were detected across all ages, but diagnostics were more frequently requested for paediatric patients than adults and the elderly. OC43 and 229E incidence was relatively constant across age strata, while that of NL63 and HKU1 decreased with age.ConclusionsBoth the Alphacoronaviruses and Betacoronaviruses showed alternating biennial winter incidence peaks, which suggests some type of immune mediated interaction. Symptomatic reinfections in adults and the elderly appear relatively common. Both findings may be of relevance for the epidemiology of SARS-CoV-2.

The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatic tools and resources, and advocate for greater openness, interoperability, accessibility and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a clear and present need for a fit-for-purpose, open source SARS-CoV-2 contextual data standard. As such, we have developed an extension to the INSDC pathogen package, providing a SARS-CoV-2 contextual data specification based on harmonisable, publicly available, community standards. The specification is implementable via a collection template, as well as an array of protocols and tools to support the harmonisation and submission of sequence data and contextual information to public repositories. Well-structured, rich contextual data adds value, promotes reuse, and enables aggregation and integration of disparate data sets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19.

Recombination is an important feature of HIV evolution, occurring both within and between the major branches of diversity (subtypes). The Ugandan epidemic is primarily composed of two subtypes, A1 and D, that have been co-circulating for 50 years, frequently recombining in dually infected patients. Here, we investigate the frequency of recombinants in this population and the location of breakpoints along the genome. As part of the PANGEA-HIV consortium, 1,472 consensus genome sequences over 5 kb have been obtained from 1,857 samples collected by the MRC/UVRI & LSHTM Research unit in Uganda, 465 (31.6 per cent) of which were near full-length sequences (>8 kb). Using the subtyping tool SCUEAL, we find that of the near full-length dataset, 233 (50.1 per cent) genomes contained only one subtype, 30.8 per cent A1 (n = 143), 17.6 per cent D (n = 82), and 1.7 per cent C (n = 8), while 49.9 per cent (n = 232) contained more than one subtype (including A1/D (n = 164), A1/C (n = 13), C/D (n = 9); A1/C/D (n = 13), and 33 complex types). K-means clustering of the recombinant A1/D genomes revealed a section of envelope (C2gp120-TMgp41) is often inherited intact, whilst a generalized linear model was used to demonstrate significantly fewer breakpoints in the gag–pol and envelope C2-TM regions compared with accessory gene regions. Despite similar recombination patterns in many recombinants, no clearly supported circulating recombinant form (CRF) was found, there was limited evidence of the transmission of breakpoints, and the vast majority (153/164; 93 per cent) of the A1/D recombinants appear to be unique recombinant forms. Thus, recombination is pervasive with clear biases in breakpoint location, but CRFs are not a significant feature, characteristic of a complex, and diverse epidemic. 1. Introduction 2. Methods 2.1 Sample collection 2.2 Sequencing and alignment 2.3 Subtyping 2.4 Identification of transmitted breakpoints 2.5 Recombination pattern classification 2.6 Breakpoint and genome location model framework 3. Results 3.1 Subtype distribution 3.2 Identification of CRFs and transmitted breakpoints 3.3 Recombinant groupings 3.4 Breakpoint distribution 4. Discussion

A series of unfortunate events The history of how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread around the planet has been far from clear. Several narratives have been propagated by social media and, in some cases, national policies were forged in response. Now that many thousands of virus sequences are available, two studies analyzed some of the key early events in the spread of SARS-CoV-2. Bedford et al. found that the virus arrived in Washington state in late January or early February. The viral genome from the first case detected had mutations similar to those found in Chinese samples and rapidly spread and dominated subsequent undetected community transmission. The other viruses detected had origins in Europe. Worobey et al. found that early introductions into Germany and the west coast of the United States were extinguished by vigorous public health efforts, but these successes were largely unrecognized. Unfortunately, several major travel events occurred in February, including repatriations from China, with lax public health follow-up. Serial, independent introductions triggered the major outbreaks in the United States and Europe that still hold us in the grip of control measures. Science, this issue p. 571, p. 564, The first case of SARS-CoV-2 in Washington state occurred at the end of January and, by going undetected, sparked community transmission., After its emergence in Wuhan, China, in late November or early December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus rapidly spread globally. Genome sequencing of SARS-CoV-2 allows the reconstruction of its transmission history, although this is contingent on sampling. We analyzed 453 SARS-CoV-2 genomes collected between 20 February and 15 March 2020 from infected patients in Washington state in the United States. We find that most SARS-CoV-2 infections sampled during this time derive from a single introduction in late January or early February 2020, which subsequently spread locally before active community surveillance was implemented.

With two-thirds of the global population projected to be living in urban areas by 2050, understanding the transmission patterns of viral pathogens within cities is crucial for effective prevention strategies. Here, in unprecedented spatial resolution, we analysed the socioeconomic determinants of influenza transmission in a European city. We combined geographical and epidemiological data with whole genome sequencing of influenza viruses at the scale of urban quarters and statistical blocks, the smallest geographic subdivisions within a city. We observed annually re-occurring geographic clusters of influenza incidences, mainly associated with net income, and independent of population density and living space. Vaccination against influenza was also mainly associated with household income and was linked to the likelihood of influenza-like illness within an urban quarter. Transmissions patterns within and between quarters were complex. High-resolution city-level epidemiological studies combined with social science surveys such as this will be essential for understanding seasonal and pandemic transmission chains and delivering tailored public health information and vaccination programs at the municipal level.

Summary The novel coronavirus SARS-CoV-2 was first detected in the Pacific Northwest region of the United States in January 2020, with subsequent COVID-19 outbreaks detected in all 50 states by early March. To uncover the sources of SARS-CoV-2 introductions and patterns of spread within the United States, we sequenced nine viral genomes from early reported COVID-19 patients in Connecticut. Our phylogenetic analysis places the majority of these genomes with viruses sequenced from Washington state. By coupling our genomic data with domestic and international travel patterns, we show that early SARS-CoV-2 transmission in Connecticut was likely driven by domestic introductions. Moreover, the risk of domestic importation to Connecticut exceeded that of international importation by mid-March regardless of our estimated effects of federal travel restrictions. This study provides evidence of widespread sustained transmission of SARS-CoV-2 within the United States and highlights the critical need for local surveillance., Graphical Abstract, Highlights • Connecticut’s COVID-19 outbreak resulted from multiple domestic virus introductions • SARS-CoV-2 genomic data indicate that coast-to-coast spread occurred in the United States • Risk of introduction by domestic air travel exceeded international travel in March • Restrictions on international travel did not significantly alter risk estimates, Using genomics and air travel information, the spread of SARS-CoV-2 in the United States from coast to coast is shown to be more a consequence of domestic introductions than of international travel.

Switzerland is among the countries with the highest number of coronavirus disease-2019 (COVID-19) cases per capita in the world. There are likely many people with undetected SARS-CoV-2 infection because testing efforts are currently not detecting all infected people, including some with clinical disease compatible with COVID-19. Testing on its own will not stop the spread of SARS-CoV-2. Testing is part of a strategy. The World Health Organization recommends a combination of measures: rapid diagnosis and immediate isolation of cases, rigorous tracking and precautionary self-isolation of close contacts. In this article, we explain why the testing strategy in Switzerland should be strengthened urgently, as a core component of a combination approach to control COVID-19.

Almost half of the confirmed COVID-19 cases detected so far in the United Kingdom are part of a large cluster of 13 British nationals who tested positive for SARS-CoV-2 in the UK, Spain, and France. Transmissions among this cluster occurred at a ski resort in France, and originated from a single infected traveller returning from a conference in Singapore where he acquired the virus. At least 21 individuals were exposed to the virus, tested, and quarantined, with 13 of those testing positive between the period of 6th Feb and 15th Feb. Here, all publicly available information about the primarily UK/France cluster is consolidated, providing a complete and accessible summary of the cases and their connections. Notable in this cluster are the number of individuals infected, the apparent absence of any severe illness among those infected, and a case of a `delayed positive' test during isolation after initially testing negative, at least 7 days after last possible contact.

A novel coronavirus (SARS-CoV-2) first detected in Wuhan, China, has spread rapidly since December 2019, causing more than 80,000 confirmed infections and 2,700 fatalities (as of Feb 27, 2020). Imported cases and transmission clusters of various sizes have been reported globally suggesting a pandemic is likely.Here, we explore how seasonal variation in transmissibility could modulate a SARS-CoV-2 pandemic. Data from routine diagnostics show a strong and consistent seasonal variation of the four endemic coronaviruses (229E, HKU1, NL63, OC43) and we parameterize our model for SARS-CoV-2 using these data. The model allows for many subpopulations of different size with variable parameters. Simulations of different scenarios show that plausible parameters result in a small peak in early 2020 in temperate regions of the Northern Hemisphere and a larger peak in winter 2020/2021. Variation in transmission and migration rates can result in substantial variation in prevalence between regions.While the uncertainty in parameters is large, the scenarios we explore show that transient reductions in the incidence rate might be due to a combination of seasonal variation and infection control efforts but do not necessarily mean the epidemic is contained. Seasonal forcing on SARS-CoV-2 should thus be taken into account in the further monitoring of the global transmission. The likely aggregated effect of seasonal variation, infection control measures, and transmission rate variation is a prolonged pandemic wave with lower prevalence at any given time, thereby providing a window of opportunity for better preparation of health care systems.

Enterovirus D68 (EV-D68) was detected in 93 patients from five European countries between 1 January 2019 and 15 January 2020, a season with expected low circulation. Patients were primarily children (n = 67, median age: 4 years), 59 patients required hospitalisation and five had severe neurologic manifestations. Phylogenetic analysis revealed two clusters in the B3 subclade and subclade A2/D. This circulation of EV-D68 associated with neurological manifestations stresses the importance of surveillance and diagnostics beyond expected peak years.

The novel coronavirus SARS-CoV-2 was first detected in the Pacific Northwest region of the United States in January 2020, with subsequent COVID-19 outbreaks detected in all 50 states by early March. To uncover the sources of SARS-CoV-2 introductions and patterns of spread within the United States, we sequenced nine viral genomes from early reported COVID-19 patients in Connecticut. Our phylogenetic analysis places the majority of these genomes with viruses sequenced from Washington state. By coupling our genomic data with domestic and international travel patterns, we show that early SARS-CoV-2 transmission in Connecticut was likely driven by domestic introductions. Moreover, the risk of domestic importation to Connecticut exceeded that of international importation by mid-March regardless of our estimated effects of federal travel restrictions. This study provides evidence of widespread sustained transmission of SARS-CoV-2 within the United States and highlights the critical need for local surveillance.

Worldwide outbreaks of enterovirus D68 (EV-D68) in 2014 and 2016 have caused serious respiratory and neurological disease. To investigate diversity, spread, and evolution of EV-D68 we performed near full-length deep sequencing in 54 samples obtained in Sweden during the 2014 and 2016 outbreaks. In most samples, intrapatient variability was low and dominated by rare synonymous variants, but three patients showed evidence of dual infections with distinct EV-D68 variants from the same subclade. Interpatient evolution showed a very strong temporal signal, with an evolutionary rate of 0.0039 ± 0.0001 substitutions per site and year. Phylogenetic trees reconstructed from the sequences suggest that EV-D68 was introduced into Stockholm several times during the 2016 outbreak. Putative neutralization targets in the BC and DE loops of the VP1 protein were slightly more diverse within-host and tended to undergo more frequent substitution than other genomic regions. However, evolution in these loops did not appear to have been driven the emergence of the 2016 B3-subclade directly from the 2014 B1-subclade. Instead, the most recent ancestor of both clades was dated to 2009. The study provides a comprehensive description of the intra- and interpatient evolution of EV-D68, including the first report of intrapatient diversity and dual infections. The new data along with publicly available EV-D68 sequences are included in an interactive phylodynamic analysis on nextstrain.org/enterovirus/d68 to facilitate timely EV-D68 tracking in the future.

Background. The United Kingdom human immunodeficiency virus (HIV) epidemic was historically dominated by HIV subtype B transmission among men who have sex with men (MSM). Now 50% of diagnoses and prevalent infections are among heterosexual individuals and mainly involve non-B subtypes. Between 2002 and 2010, the prevalence of non-B diagnoses among MSM increased from 5.4% to 17%, and this study focused on the drivers of this change. Methods. Growth between 2007 and 2009 in transmission clusters among 14 000 subtype A1, C, D, and G sequences from the United Kingdom HIV Drug Resistance Database was analysed by risk group. Results. Of 1148 clusters containing at least 2 sequences in 2007, >75% were pairs and >90% were heterosexual. Most clusters (71.4%) did not grow during the study period. Growth was significantly lower for small clusters and higher for clusters of ≥7 sequences, with the highest growth observed for clusters comprising sequences from MSM and people who inject drugs (PWID). Risk group (P < .0001), cluster size (P < .0001), and subtype (P < .01) were predictive of growth in a generalized linear model. Discussion. Despite the increase in non-B subtypes associated with heterosexual transmission, MSM and PWID are at risk for non-B infections. Crossover of subtype C from heterosexuals to MSM has led to the expansion of this subtype within the United Kingdom.

Patients who do not disclose their sexuality, including men who do not disclose same-sex behaviour, are difficult to characterise through traditional epidemiological approaches such as interviews. Using a recently developed method to detect large networks of viral sequences from time-resolved trees, we localised non-disclosed men who have sex with men (MSM) in UK transmission networks, gaining crucial insight into the behaviour of this group.For this phylogenetic analysis, we obtained HIV pol sequences from the UK HIV Drug Resistance Database (UKRDB), a central repository for resistance tests done as part of routine clinical care throughout the UK. Sequence data are linked to demographic and clinical data held by the UK Collaborative HIV Cohort study and the national HIV/AIDS reporting system database. Initially, we reconstructed maximum likelihood phylogenies from these sequences, then sequences were selected for time-resolved analysis in BEAST if they were clustered with at least one other sequence at a genetic distance of 4·5% or less with support of at least 90%. We used time-resolved phylogenies to create networks by linking together nodes if sequences shared a common ancestor within the previous 5 years. We identified potential non-disclosed MSM (pnMSM), defined as self-reported heterosexual men who clustered only with men. We measured the network position of pnMSM, including betweenness (a measure of connectedness and importance) and assortativity (the propensity for nodes sharing attributes to link).14 405 individuals were in the network, including 8452 MSM, 1743 heterosexual women and 1341 heterosexual men. 249 pnMSM were identified (18·6% of all clustered heterosexual men) in the network. pnMSM were more likely to be black African (p0·0001), less likely to be infected with subtype B (p=0·006), and were slightly older (p=0·002) than the MSM they clustered with. Mean betweenness centrality was lower for pnMSM than for MSM (1·31, 95% CI 0·48-2·15 in pnMSM vs 2·24, 0·98-3·51 in MSM; p=0·002), indicating that pnMSM were in peripheral positions in MSM clusters. Assortativity by risk group was higher than expected (0·037 vs -0·037, p=0·01) signifying that pnMSM were linked to each other. We found that self-reported heterosexual men were more likely to link MSM and heterosexual women than heterosexual women were to link MSM and heterosexual men (Fisher's exact test p=0·0004; OR 2·24) but the number of such transmission chains was small (only 54 in total vs 32 in women).pnMSM are a subgroup distinct from both MSM and from heterosexual men. They are more likely to choose sexual partners who are also pnMSM and might exhibit lower-risk sexual behaviour than MSM (eg, choosing low-risk partners or consistently using condoms). Heterosexual men are the group most likely to be diagnosed with late-stage disease (ie, low CD4 counts) and non-disclosed MSM might put female partners at higher risk than heterosexual men because non-disclosed MSM have male partners. Hence, pnMSM require specific consideration to ensure they are included in public health interventions.National Institutes of Health.

We compared the behavior of two approaches (Cluster Picker and HIV-TRACE) at varying genetic distances to identify transmission clusters. We used three HIV gp41 sequence datasets originating from the Rakai Community Cohort Study: (1) next-generation sequence (NGS) data from nine linked couples; (2) NGS data from longitudinal sampling of 14 individuals; and (3) Sanger consensus sequences from a cross-sectional dataset (n = 1,022) containing 91 epidemiologically linked heterosexual couples. We calculated the optimal genetic distance threshold to separate linked versus unlinked NGS datasets using a receiver operating curve analysis. We evaluated the number, size, and composition of clusters detected by Cluster Picker and HIV-TRACE at six genetic distance thresholds (1%-5.3%) on all three datasets. We further tested the effect of using all NGS, versus only a single variant for each patient/time point, for datasets (1) and (2). The optimal gp41 genetic distance threshold to distinguish linked and unlinked couples and individuals was 5.3% and 4%, respectively. HIV-TRACE tended to detect larger and fewer clusters, whereas Cluster Picker detected more clusters containing only two sequences. For NGS datasets (1) and (2), HIV-TRACE and Cluster Picker detected all linked pairs at 3% and 4% genetic distances, respectively. However, at 5.3% genetic distance, 20% of couples in dataset (3) did not cluster using either program, and for >1/3 of couples cluster assignment were discordant. We suggest caution in choosing thresholds for clustering analyses in a generalized epidemic.

Clonality and the mechanisms by which populations become established can affect the level and pattern of genetic diversity, which can in turn affect the ecology and evolution of those populations. We used amplified fragment length polymorphisms (AFLPs) to examine genetic diversity and clonality in four isolated populations of the rhizomatous pale pitcher plant, Sarracenia alata Alph. Wood, with particular emphasis on determining the extent of clonal spread and the likely mechanisms by which these populations became established. Genetic variation was greater within (87%) than between (13%) populations. The interpopulation genetic differentiation was a function of geographic distance. The mean (± SE) genetic diversity (HE) within populations was 0.126 ± 0.006, and the percentage of polymorphic loci within populations ranged from 58.9 to 72.4% (64.3 ± 2.89, mean ± SE). We found no repeated multilocus genotypes among our samples, nor was there evidence of bimodality of genetic differences among indiv...

Viral phylogenetic methods contribute to understanding how HIV spreads in populations, and thereby help guide the design of prevention interventions. So far, most analyses have been applied to well-sampled concentrated HIV-1 epidemics in wealthy countries. To direct the use of phylogenetic tools to where the impact of HIV-1 is greatest, the Phylogenetics And Networks for Generalized HIV Epidemics in Africa (PANGEA-HIV) consortium generates full-genome viral sequences from across sub-Saharan Africa. Analyzing these data presents new challenges, since epidemics are principally driven by heterosexual transmission and a smaller fraction of cases is sampled. Here, we show that viral phylogenetic tools can be adapted and used to estimate epidemiological quantities of central importance to HIV-1 prevention in sub-Saharan Africa. We used a community-wide methods comparison exercise on simulated data, where participants were blinded to the true dynamics they were inferring. Two distinct simulations captured generalized HIV-1 epidemics, before and after a large community-level intervention that reduced infection levels. Five research groups participated. Structured coalescent modeling approaches were most successful: phylogenetic estimates of HIV-1 incidence, incidence reductions, and the proportion of transmissions from individuals in their first 3 months of infection correlated with the true values (Pearson correlation > 90%), with small bias. However, on some simulations, true values were markedly outside reported confidence or credibility intervals. The blinded comparison revealed current limits and strengths in using HIV phylogenetics in challenging settings, provided benchmarks for future methods’ development, and supports using the latest generation of phylogenetic tools to advance HIV surveillance and prevention., Molecular Biology and Evolution, 34 (1), ISSN:0737-4038, ISSN:1537-1719

Phylogenetic clustering approaches can elucidate HIV transmission dynamics. Comparisons across countries are essential for evaluating public health policies. Here, we used a standardised approach to compare the UK HIV Drug Resistance Database and the Swiss HIV Cohort Study while maintaining data-protection requirements. Clusters were identified in subtype A1, B and C pol phylogenies. We generated degree distributions for each risk group and compared distributions between countries using Kolmogorov-Smirnov (KS) tests, Degree Distribution Quantification and Comparison (DDQC) and bootstrapping. We used logistic regression to predict cluster membership based on country, sampling date, risk group, ethnicity and sex. We analysed >8,000 Swiss and >30,000 UK subtype B sequences. At 4.5% genetic distance, the UK was more clustered and MSM and heterosexual degree distributions differed significantly by the KS test. The KS test is sensitive to variation in network scale, and jackknifing the UK MSM dataset to the size of the Swiss dataset removed the difference. Only heterosexuals varied based on the DDQC, due to UK male heterosexuals who clustered exclusively with MSM. Their removal eliminated this difference. In conclusion, the UK and Swiss HIV epidemics have similar underlying dynamics and observed differences in clustering are mainly due to different population sizes.

HIV molecular epidemiology studies analyse viral pol gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the PANGEA_HIV project) with a known transmission tree. We sub-sampled a simulated dataset of 4662 sequences into different combinations of genes (gag-pol-env, gag-pol, gag, pol, env and partial pol) and sampling depths (100%, 60%, 20% and 5%), generating 100 replicates for each case. We built maximum-likelihood trees for each combination using RAxML (GTR + Γ), and compared their topologies to the corresponding true tree’s using CompareTree. The accuracy of the trees was significantly proportional to the length of the sequences used, with the gag-pol-env datasets showing the best performance and gag and partial pol sequences showing the worst. The lowest sampling depths (20% and 5%) greatly reduced the accuracy of tree reconstruction and showed high variability among replicates, especially when using the shortest gene datasets. In conclusion, using longer sequences derived from nearly whole genomes will improve the reliability of phylogenetic reconstruction. With low sample coverage, results can be highly variable, particularly when based on short sequences.