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1.
Nature ; 2022 Aug 11.
Article in English | MEDLINE | ID: covidwho-1991629

ABSTRACT

The SARS-CoV-2 Delta variant of concern spread globally, causing resurgences of COVID-19 worldwide1,2. Delta's emergence in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 virus genomes from England together 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 geographic focus of Delta's expansion 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 reduced onward transmission from importations; however transmission chains that later dominated England's Delta wave were seeded before travel restrictions were introduced. Increasing inter-regional travel within England drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from elsewhere. Subsequently, increased levels of local population mixing, not the number of importations, were associated with faster relative growth of Delta. Delta's invasion dynamics depended on spatial heterogeneity in contact patterns, and our findings will inform optimal spatial interventions to reduce transmission of current and future variant of concern, such as Omicron.

2.
Viruses ; 14(6)2022 06 01.
Article in English | MEDLINE | ID: covidwho-1869831

ABSTRACT

The unprecedented pandemic COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with bats as original reservoirs, has once again highlighted the importance of exploring the interface of wildlife diseases and human health. In this study, we identified a novel Betacoronavirus from bank voles (Myodes glareolus) in Grimsö, Sweden, and this virus is designated as Grimso virus. Repeated detection over three years and an overall prevalence of 3.4% suggest that the virus commonly occurs in bank voles. Furthermore, phylogenetic analyses indicate that the Grimso virus belongs to a highly divergent Embecovirus lineage predominantly associated with bank voles. Given that bank voles are one of the most common rodent species in Sweden and Europe, our findings indicate that Grimso virus might be circulating widely in bank voles and further point out the importance of sentinel surveillance of coronaviruses in wild small mammalian animals, especially in wild rodents.


Subject(s)
COVID-19 , Rodent Diseases , Animals , Arvicolinae , COVID-19/veterinary , Phylogeny , SARS-CoV-2/genetics , Sweden/epidemiology
3.
Emerg Infect Dis ; 28(4): 751-758, 2022 04.
Article in English | MEDLINE | ID: covidwho-1771001

ABSTRACT

Limited genomic sampling in many high-incidence countries has impeded studies of severe respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic epidemiology. Consequently, critical questions remain about the generation and global distribution of virus genetic diversity. We investigated SARS-CoV-2 transmission dynamics in Gujarat, India, during the state's first epidemic wave to shed light on spread of the virus in one of the regions hardest hit by the pandemic. By integrating case data and 434 whole-genome sequences sampled across 20 districts, we reconstructed the epidemic dynamics and spatial spread of SARS-CoV-2 in Gujarat. Our findings indicate global and regional connectivity and population density were major drivers of the Gujarat outbreak. We detected >100 virus lineage introductions, most of which appear to be associated with international travel. Within Gujarat, virus dissemination occurred predominantly from densely populated regions to geographically proximate locations that had low population density, suggesting that urban centers contributed disproportionately to virus spread.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Genome, Viral , Genomics , Humans , India/epidemiology , Phylogeny , SARS-CoV-2/genetics
4.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329173

ABSTRACT

We identified a novel Betacoronavirus from bank voles ( Myodes glareolus ) in Grimsö, Sweden. Repeated detection over three years and an overall prevalence of 3.4% suggests the virus commonly occurs in bank voles. Furthermore, phylogenetic analyses indicate the virus belongs to a highly divergent Embecovirus lineage predominantly associated with bank voles.

5.
Mol Biol Evol ; 39(2)2022 02 03.
Article in English | MEDLINE | ID: covidwho-1625216

ABSTRACT

High-throughput sequencing enables rapid genome sequencing during infectious disease outbreaks and provides an opportunity to quantify the evolutionary dynamics of pathogens in near real-time. One difficulty of undertaking evolutionary analyses over short timescales is the dependency of the inferred evolutionary parameters on the timespan of observation. Crucially, there are an increasing number of molecular clock analyses using external evolutionary rate priors to infer evolutionary parameters. However, it is not clear which rate prior is appropriate for a given time window of observation due to the time-dependent nature of evolutionary rate estimates. Here, we characterize the molecular evolutionary dynamics of SARS-CoV-2 and 2009 pandemic H1N1 (pH1N1) influenza during the first 12 months of their respective pandemics. We use Bayesian phylogenetic methods to estimate the dates of emergence, evolutionary rates, and growth rates of SARS-CoV-2 and pH1N1 over time and investigate how varying sampling window and data set sizes affect the accuracy of parameter estimation. We further use a generalized McDonald-Kreitman test to estimate the number of segregating nonneutral sites over time. We find that the inferred evolutionary parameters for both pandemics are time dependent, and that the inferred rates of SARS-CoV-2 and pH1N1 decline by ∼50% and ∼100%, respectively, over the course of 1 year. After at least 4 months since the start of sequence sampling, inferred growth rates and emergence dates remain relatively stable and can be inferred reliably using a logistic growth coalescent model. We show that the time dependency of the mean substitution rate is due to elevated substitution rates at terminal branches which are 2-4 times higher than those of internal branches for both viruses. The elevated rate at terminal branches is strongly correlated with an increasing number of segregating nonneutral sites, demonstrating the role of purifying selection in generating the time dependency of evolutionary parameters during pandemics.


Subject(s)
COVID-19 , Influenza A Virus, H1N1 Subtype , Influenza, Human , Bayes Theorem , Humans , Influenza A Virus, H1N1 Subtype/genetics , Influenza, Human/epidemiology , Phylogeny , SARS-CoV-2
6.
Science ; 371(6530): 708-712, 2021 02 12.
Article in English | MEDLINE | ID: covidwho-1066806

ABSTRACT

The United Kingdom's COVID-19 epidemic during early 2020 was one of world's largest and was unusually well represented by virus genomic sampling. We determined the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes, including 26,181 from the UK sampled throughout the country's first wave of infection. Using large-scale phylogenetic analyses combined with epidemiological and travel data, we quantified the size, spatiotemporal 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 tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whereas lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , Genome, Viral , SARS-CoV-2/genetics , COVID-19/prevention & control , COVID-19/transmission , Chain of Infection , Communicable Disease Control , Communicable Diseases, Imported/epidemiology , Communicable Diseases, Imported/virology , Epidemics , Humans , Phylogeny , Travel , United Kingdom/epidemiology
7.
Nat Commun ; 11(1): 2688, 2020 05 27.
Article in English | MEDLINE | ID: covidwho-432476

ABSTRACT

Severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) coronaviruses (CoVs) are zoonotic pathogens with high fatality rates and pandemic potential. Vaccine development focuses on the principal target of the neutralizing humoral immune response, the spike (S) glycoprotein. Coronavirus S proteins are extensively glycosylated, encoding around 66-87 N-linked glycosylation sites per trimeric spike. Here, we reveal a specific area of high glycan density on MERS S that results in the formation of oligomannose-type glycan clusters, which were absent on SARS and HKU1 CoVs. We provide a comparison of the global glycan density of coronavirus spikes with other viral proteins including HIV-1 envelope, Lassa virus glycoprotein complex, and influenza hemagglutinin, where glycosylation plays a known role in shielding immunogenic epitopes. Overall, our data reveal how organisation of glycosylation across class I viral fusion proteins influence not only individual glycan compositions but also the immunological pressure across the protein surface.


Subject(s)
Glycoproteins/immunology , Middle East Respiratory Syndrome Coronavirus , Polysaccharides , Spike Glycoprotein, Coronavirus/immunology , Viral Fusion Proteins/immunology , Coronavirus Infections/immunology , Coronavirus Infections/virology , Cryoelectron Microscopy , Epitopes/chemistry , Epitopes/immunology , Epitopes/metabolism , Glycoproteins/chemistry , Glycoproteins/ultrastructure , Glycosylation , HEK293 Cells , HIV-1/immunology , HIV-1/metabolism , Humans , Immune Evasion/physiology , Lassa virus/immunology , Lassa virus/metabolism , Middle East Respiratory Syndrome Coronavirus/immunology , Middle East Respiratory Syndrome Coronavirus/metabolism , Orthomyxoviridae/immunology , Orthomyxoviridae/metabolism , Polysaccharides/chemistry , Polysaccharides/immunology , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/ultrastructure , Viral Fusion Proteins/chemistry , Viral Fusion Proteins/ultrastructure , Viral Proteins/chemistry , Viral Proteins/immunology , Viral Proteins/ultrastructure
8.
Cell ; 181(5): 997-1003.e9, 2020 05 28.
Article in English | MEDLINE | ID: covidwho-60418

ABSTRACT

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2 infection and was first reported in central China in December 2019. Extensive molecular surveillance in Guangdong, China's 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 because of 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 province's large-scale intensive surveillance and intervention measures. Despite these successes, COVID-19 surveillance in Guangdong is still required, because the number of cases imported from other countries has increased.


Subject(s)
Betacoronavirus/genetics , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Bayes Theorem , COVID-19 , China/epidemiology , Coronavirus Infections/virology , Epidemiological Monitoring , Humans , Likelihood Functions , Pandemics , Pneumonia, Viral/virology , SARS-CoV-2 , Travel
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