Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 10 de 10
Filter
1.
Commun Med (Lond) ; 2: 65, 2022.
Article in English | MEDLINE | ID: covidwho-1947557

ABSTRACT

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of infections and fatalities globally since its emergence in late 2019. The virus was first detected in Finland in January 2020, after which it rapidly spread among the populace in spring. However, compared to other European nations, Finland has had a low incidence of SARS-CoV-2. To gain insight into the origins and turnover of SARS-CoV-2 lineages circulating in Finland in 2020, we investigated the phylogeographic and -dynamic history of the virus. Methods: The origins of SARS-CoV-2 introductions were inferred via Travel-aware Bayesian time-measured phylogeographic analyses. Sequences for the analyses included virus genomes belonging to the B.1 lineage and with the D614G mutation from countries of likely origin, which were determined utilizing Google mobility data. We collected all available sequences from spring and fall peaks to study lineage dynamics. Results: We observed rapid turnover among Finnish lineages during this period. Clade 20C became the most prevalent among sequenced cases and was replaced by other strains in fall 2020. Bayesian phylogeographic reconstructions suggested 42 independent introductions into Finland during spring 2020, mainly from Italy, Austria, and Spain. Conclusions: A single introduction from Spain might have seeded one-third of cases in Finland during spring in 2020. The investigations of the original introductions of SARS-CoV-2 to Finland during the early stages of the pandemic and of the subsequent lineage dynamics could be utilized to assess the role of transboundary movements and the effects of early intervention and public health measures.

2.
Viruses ; 14(6)2022 06 14.
Article in English | MEDLINE | ID: covidwho-1911635

ABSTRACT

Healthcare workers (HCWs) are known to be at higher risk of developing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections although whether these risks are equal across all occupational roles is uncertain. Identifying these risk factors and understand SARS-CoV-2 transmission pathways in healthcare settings are of high importance to achieve optimal protection measures. We aimed to investigate the implementation of a voluntary screening program for SARS-CoV-2 infections among hospital HCWs and to elucidate potential transmission pathways though phylogenetic analysis before the vaccination era. HCWs of the University Hospital of Liège, Belgium, were invited to participate in voluntary reverse transcriptase-polymerase chain reaction (RT-PCR) assays performed every week from April to December 2020. Phylogenetic analysis of SARS-CoV-2 genomes were performed for a subgroup of 45 HCWs. 5095 samples were collected from 703 HCWs. 212 test results were positive, 15 were indeterminate, and 4868 returned negative. 156 HCWs (22.2%) tested positive at least once during the study period. All SARS-CoV-2 test results returned negative for 547 HCWs (77.8%). Nurses (p < 0.05), paramedics (p < 0.05), and laboratory staff handling respiratory samples (p < 0.01) were at higher risk for being infected compared to the control non-patient facing group. Our phylogenetic analysis revealed that most positive samples corresponded to independent introduction events into the hospital. Our findings add to the growing evidence of differential risks of being infected among HCWs and support the need to implement appropriate protection measures based on each individual's risk profile to guarantee the protection of both HCWs and patients. Furthermore, our phylogenetic investigations highlight that most positive samples correspond to distinct introduction events into the hospital.


Subject(s)
COVID-19 , Belgium/epidemiology , COVID-19/diagnosis , COVID-19/epidemiology , Delivery of Health Care , Health Personnel , Hospitals, University , Humans , Personnel, Hospital , Phylogeny , SARS-CoV-2/genetics
3.
Nat Commun ; 12(1): 5769, 2021 10 01.
Article in English | MEDLINE | ID: covidwho-1447305

ABSTRACT

Distinct SARS-CoV-2 lineages, discovered through various genomic surveillance initiatives, have emerged during the pandemic following unprecedented reductions in worldwide human mobility. We here describe a SARS-CoV-2 lineage - designated B.1.620 - discovered in Lithuania and carrying many mutations and deletions in the spike protein shared with widespread variants of concern (VOCs), including E484K, S477N and deletions HV69Δ, Y144Δ, and LLA241/243Δ. As well as documenting the suite of mutations this lineage carries, we also describe its potential to be resistant to neutralising antibodies, accompanying travel histories for a subset of European cases, evidence of local B.1.620 transmission in Europe with a focus on Lithuania, and significance of its prevalence in Central Africa owing to recent genome sequencing efforts there. We make a case for its likely Central African origin using advanced phylogeographic inference methodologies incorporating recorded travel histories of infected travellers.


Subject(s)
COVID-19/transmission , COVID-19/virology , SARS-CoV-2/genetics , Africa, Central/epidemiology , Antibodies, Neutralizing/immunology , COVID-19/epidemiology , Europe/epidemiology , Humans , Immune Evasion/genetics , Mutation , Phylogeny , Phylogeography , SARS-CoV-2/classification , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/genetics , Travel/statistics & numerical data
4.
Sci Rep ; 11(1): 18580, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1428900

ABSTRACT

At the end of 2020, several new variants of SARS-CoV-2-designated variants of concern-were detected and quickly suspected to be associated with a higher transmissibility and possible escape of vaccine-induced immunity. In Belgium, this discovery has motivated the initiation of a more ambitious genomic surveillance program, which is drastically increasing the number of SARS-CoV-2 genomes to analyse for monitoring the circulation of viral lineages and variants of concern. In order to efficiently analyse the massive collection of genomic data that are the result of such increased sequencing efforts, streamlined analytical strategies are crucial. In this study, we illustrate how to efficiently map the spatio-temporal dispersal of target mutations at a regional level. As a proof of concept, we focus on the Belgian province of Liège that has been consistently sampled throughout 2020, but was also one of the main epicenters of the second European epidemic wave. Specifically, we employ a recently developed phylogeographic workflow to infer the regional dispersal history of viral lineages associated with three specific mutations on the spike protein (S98F, A222V and S477N) and to quantify their relative importance through time. Our analytical pipeline enables analysing large data sets and has the potential to be quickly applied and updated to track target mutations in space and time throughout the course of an epidemic.


Subject(s)
Genome, Viral , Mutation , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/genetics , Belgium , Epidemiological Monitoring , Humans
5.
Viruses ; 13(7)2021 07 13.
Article in English | MEDLINE | ID: covidwho-1314760

ABSTRACT

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


Subject(s)
COVID-19/virology , Military Personnel , SARS-CoV-2/classification , SARS-CoV-2/genetics , Afghanistan/epidemiology , Belgium , COVID-19/epidemiology , China/epidemiology , Democratic Republic of the Congo/epidemiology , Genome, Viral , Genomics , Humans , Mali/epidemiology , Molecular Epidemiology , Mutation , Niger/epidemiology , Phylogeny , Travel , Whole Genome Sequencing
6.
Nature ; 595(7869): 713-717, 2021 07.
Article in English | MEDLINE | ID: covidwho-1287812

ABSTRACT

After the first wave of SARS-CoV-2 infections in spring 2020, Europe experienced a resurgence of the virus starting in late summer 2020 that was deadlier and more difficult to contain1. Relaxed intervention measures and summer travel have been implicated as drivers of the second wave2. Here we build a phylogeographical model to evaluate how newly introduced lineages, as opposed to the rekindling of persistent lineages, contributed to the resurgence of COVID-19 in Europe. We inform this model using genomic, mobility and epidemiological data from 10 European countries and estimate that in many countries more than half of the lineages circulating in late summer resulted from new introductions since 15 June 2020. The success in onward transmission of newly introduced lineages was negatively associated with the local incidence of COVID-19 during this period. The pervasive spread of variants in summer 2020 highlights the threat of viral dissemination when restrictions are lifted, and this needs to be carefully considered in strategies to control the current spread of variants that are more transmissible and/or evade immunity. Our findings indicate that more effective and coordinated measures are required to contain the spread through cross-border travel even as vaccination is reducing disease burden.


Subject(s)
COVID-19/transmission , COVID-19/virology , SARS-CoV-2/isolation & purification , COVID-19/epidemiology , COVID-19/prevention & control , Europe/epidemiology , Genome, Viral/genetics , Humans , Incidence , Locomotion , Phylogeny , Phylogeography , SARS-CoV-2/classification , SARS-CoV-2/genetics , SARS-CoV-2/pathogenicity , Time Factors , Travel/statistics & numerical data
7.
PLoS Pathog ; 17(5): e1009571, 2021 05.
Article in English | MEDLINE | ID: covidwho-1236598

ABSTRACT

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


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , SARS-CoV-2/genetics , Genome, Viral/genetics , Humans , New York City/epidemiology , Phylogeny , Phylogeography , Prevalence , SARS-CoV-2/classification , SARS-CoV-2/isolation & purification
8.
Curr Protoc ; 1(4): e98, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1173795

ABSTRACT

Advances in sequencing technologies have tremendously reduced the time and costs associated with sequence generation, making genomic data an important asset for routine public health practices. Within this context, phylogenetic and phylogeographic inference has become a popular method to study disease transmission. In a Bayesian context, these approaches have the benefit of accommodating phylogenetic uncertainty, and popular implementations provide the possibility to parameterize the transition rates between locations as a function of epidemiological and ecological data to reconstruct spatial spread while simultaneously identifying the main factors impacting the spatial spread dynamics. Recent developments enable researchers to make use of travel history data of infected individuals in the reconstruction of pathogen spread, offering increased inference accuracy and mitigating sampling bias. Here, we describe a detailed workflow to reconstruct the spatial spread of a pathogen through Bayesian phylogeographic analysis in discrete space using these novel approaches, implemented in BEAST. The individual protocols focus on how to incorporate molecular data, covariates of spread, and individual travel history data into the analysis. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Creating a SARS-CoV-2 MSA using sequences from GISAID Basic Protocol 2: Setting up a discrete trait phylogeographic reconstruction in BEAUti Basic Protocol 3: Phylogeographic reconstruction incorporating travel history information Basic Protocol 4: Visualizing ancestral spatial trajectories for specific taxa.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , SARS-CoV-2/genetics , Travel/statistics & numerical data , Bayes Theorem , COVID-19/genetics , COVID-19/transmission , Computational Biology/methods , Databases, Nucleic Acid , Humans , Phylogeny , Phylogeography/methods , SARS-CoV-2/classification , SARS-CoV-2/isolation & purification , Sequence Analysis, DNA/methods , Software , United States/epidemiology
9.
Mol Biol Evol ; 38(4): 1608-1613, 2021 04 13.
Article in English | MEDLINE | ID: covidwho-900448

ABSTRACT

Since the start of the COVID-19 pandemic, an unprecedented number of genomic sequences of SARS-CoV-2 have been generated and shared with the scientific community. The unparalleled volume of available genetic data presents a unique opportunity to gain real-time insights into the virus transmission during the pandemic, but also a daunting computational hurdle if analyzed with gold-standard phylogeographic approaches. To tackle this practical limitation, we here describe and apply a rapid analytical pipeline to analyze the spatiotemporal dispersal history and dynamics of SARS-CoV-2 lineages. As a proof of concept, we focus on the Belgian epidemic, which has had one of the highest spatial densities of available SARS-CoV-2 genomes. Our pipeline has the potential to be quickly applied to other countries or regions, with key benefits in complementing epidemiological analyses in assessing the impact of intervention measures or their progressive easement.


Subject(s)
COVID-19/transmission , COVID-19/virology , Genome, Viral , Phylogeography , SARS-CoV-2/genetics , Belgium , COVID-19/epidemiology , Evolution, Molecular , Genomics , Humans , Likelihood Functions , Mutation , Patient Isolation , Phylogeny , Physical Distancing , Spatio-Temporal Analysis , Workflow
10.
Nat Commun ; 11(1): 5110, 2020 10 09.
Article in English | MEDLINE | ID: covidwho-841957

ABSTRACT

Spatiotemporal bias in genome sampling can severely confound discrete trait phylogeographic inference. This has impeded our ability to accurately track the spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, despite the availability of unprecedented numbers of SARS-CoV-2 genomes. Here, we present an approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2. We demonstrate that including travel history data yields i) more realistic hypotheses of virus spread and ii) higher posterior predictive accuracy compared to including only sampling location. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations. 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.


Subject(s)
Betacoronavirus/genetics , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Travel , Bayes Theorem , Betacoronavirus/classification , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/virology , Genome, Viral/genetics , Humans , Pandemics , Phylogeny , Phylogeography , Pneumonia, Viral/virology , SARS-CoV-2 , Travel/statistics & numerical data
SELECTION OF CITATIONS
SEARCH DETAIL