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1.
Nat Commun ; 13(1): 5860, 2022 10 04.
Article in English | MEDLINE | ID: covidwho-2050384

ABSTRACT

Omicron lineages BA.4 and BA.5 drove a fifth wave of COVID-19 cases in South Africa. Here, we use the presence/absence of the S-gene target as a proxy for SARS-CoV-2 variant/lineage for infections diagnosed using the TaqPath PCR assay between 1 October 2021 and 26 April 2022. We link national COVID-19 individual-level data including case, laboratory test and hospitalisation data. We assess severity using multivariable logistic regression comparing the risk of hospitalisation and risk of severe disease, once hospitalised, for Delta, BA.1, BA.2 and BA.4/BA.5 infections. After controlling for factors associated with hospitalisation and severe outcome respectively, BA.4/BA.5-infected individuals had a similar odds of hospitalisation (aOR 1.24, 95% CI 0.98-1.55) and severe outcome (aOR 0.72, 95% CI 0.41-1.26) compared to BA.1-infected individuals. Newly emerged Omicron lineages BA.4/BA.5 showed similar severity to the BA.1 lineage and continued to show reduced clinical severity compared to the Delta variant.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Humans , SARS-CoV-2/genetics , South Africa/epidemiology
2.
J Med Virol ; 94(8): 3676-3684, 2022 08.
Article in English | MEDLINE | ID: covidwho-1849500

ABSTRACT

The circulation of Omicron BA.1 led to the rapid increase in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases in South Africa in November 2021, which warranted the use of more rapid detection methods. We, therefore, assessed the ability to detect Omicron BA.1 using genotyping assays to identify specific mutations in SARS-CoV-2 positive samples, Gauteng province, South Africa. The TaqPath™ COVID-19 real-time polymerase chain reaction assay was performed on all samples selected to identify spike gene target failure (SGTF). SARS-CoV-2 genotyping assays were used for the detection of del69/70 and K417N mutation. Whole-genome sequencing was performed on a subset of genotyped samples to confirm these findings. Of the positive samples received, 11.0% (175/1589) were randomly selected to assess if SGTF and genotyping assays, that detect del69/70 and K417N mutations, could identify Omicron BA.1. We identified SGTF in 98.9% (173/175) of samples, of which 88.0% (154/175) had both the del69/70 and K417N mutation. The genotyped samples (45.7%; 80/175) that were sequenced confirmed Omicron BA.1 (97.5%; 78/80). Our data show that genotyping for the detection of the del69/70 and K417N coupled with SGTF is efficient to exclude Alpha and Beta variants and rapidly detect Omicron BA.1. However, we still require assays for the detection of unique mutations that will allow for the differentiation between other Omicron sublineages. Therefore, the use of genotyping assays to detect new dominant or emerging lineages of SARS-CoV-2 will be beneficial in limited-resource settings.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnosis , Genotype , Humans , SARS-CoV-2/genetics , South Africa , Spike Glycoprotein, Coronavirus/genetics
3.
Nat Commun ; 13(1): 1976, 2022 04 08.
Article in English | MEDLINE | ID: covidwho-1783980

ABSTRACT

Global genomic surveillance of SARS-CoV-2 has identified variants associated with increased transmissibility, neutralization resistance and disease severity. Here we report the emergence of the PANGO lineage C.1.2, detected at low prevalence in South Africa and eleven other countries. The initial C.1.2 detection is associated with a high substitution rate, and includes changes within the spike protein that have been associated with increased transmissibility or reduced neutralization sensitivity in SARS-CoV-2 variants of concern or variants of interest. Like Beta and Delta, C.1.2 shows significantly reduced neutralization sensitivity to plasma from vaccinees and individuals infected with the ancestral D614G virus. In contrast, convalescent donors infected with either Beta or Delta show high plasma neutralization against C.1.2. These functional data suggest that vaccine efficacy against C.1.2 will be equivalent to Beta and Delta, and that prior infection with either Beta or Delta will likely offer protection against C.1.2.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Neutralizing , Antibodies, Viral , Humans , Neutralization Tests , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/genetics
4.
Lancet ; 399(10323): 437-446, 2022 01 29.
Article in English | MEDLINE | ID: covidwho-1641746

ABSTRACT

BACKGROUND: The SARS-CoV-2 omicron variant of concern was identified in South Africa in November, 2021, and was associated with an increase in COVID-19 cases. We aimed to assess the clinical severity of infections with the omicron variant using S gene target failure (SGTF) on the Thermo Fisher Scientific TaqPath COVID-19 PCR test as a proxy. METHODS: We did data linkages for national, South African COVID-19 case data, SARS-CoV-2 laboratory test data, SARS-CoV-2 genome data, and COVID-19 hospital admissions data. For individuals diagnosed with COVID-19 via TaqPath PCR tests, infections were designated as either SGTF or non-SGTF. The delta variant was identified by genome sequencing. Using multivariable logistic regression models, we assessed disease severity and hospitalisations by comparing individuals with SGTF versus non-SGTF infections diagnosed between Oct 1 and Nov 30, 2021, and we further assessed disease severity by comparing SGTF-infected individuals diagnosed between Oct 1 and Nov 30, 2021, with delta variant-infected individuals diagnosed between April 1 and Nov 9, 2021. FINDINGS: From Oct 1 (week 39), 2021, to Dec 6 (week 49), 2021, 161 328 cases of COVID-19 were reported in South Africa. 38 282 people were diagnosed via TaqPath PCR tests and 29 721 SGTF infections and 1412 non-SGTF infections were identified. The proportion of SGTF infections increased from two (3·2%) of 63 in week 39 to 21 978 (97·9%) of 22 455 in week 48. After controlling for factors associated with hospitalisation, individuals with SGTF infections had significantly lower odds of admission than did those with non-SGTF infections (256 [2·4%] of 10 547 vs 121 [12·8%] of 948; adjusted odds ratio [aOR] 0·2, 95% CI 0·1-0·3). After controlling for factors associated with disease severity, the odds of severe disease were similar between hospitalised individuals with SGTF versus non-SGTF infections (42 [21%] of 204 vs 45 [40%] of 113; aOR 0·7, 95% CI 0·3-1·4). Compared with individuals with earlier delta variant infections, SGTF-infected individuals had a significantly lower odds of severe disease (496 [62·5%] of 793 vs 57 [23·4%] of 244; aOR 0·3, 95% CI 0·2-0·5), after controlling for factors associated with disease severity. INTERPRETATION: Our early analyses suggest a significantly reduced odds of hospitalisation among individuals with SGTF versus non-SGTF infections diagnosed during the same time period. SGTF-infected individuals had a significantly reduced odds of severe disease compared with individuals infected earlier with the delta variant. Some of this reduced severity is probably a result of previous immunity. FUNDING: The South African Medical Research Council, the South African National Department of Health, US Centers for Disease Control and Prevention, the African Society of Laboratory Medicine, Africa Centers for Disease Control and Prevention, the Bill & Melinda Gates Foundation, the Wellcome Trust, and the Fleming Fund.


Subject(s)
COVID-19/physiopathology , Hospitalization/statistics & numerical data , SARS-CoV-2/genetics , Severity of Illness Index , Adolescent , Adult , COVID-19/epidemiology , COVID-19/virology , COVID-19 Nucleic Acid Testing , Child , Child, Preschool , Female , Genome, Viral , Humans , Information Storage and Retrieval , Logistic Models , Male , Middle Aged , Multivariate Analysis , Odds Ratio , South Africa/epidemiology , Young Adult
5.
Nature ; 603(7902): 679-686, 2022 03.
Article in English | MEDLINE | ID: covidwho-1638766

ABSTRACT

The SARS-CoV-2 epidemic in southern Africa has been characterized by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, while the second and third waves were driven by the Beta (B.1.351) and Delta (B.1.617.2) 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, B.1.1.529) 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, which are 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.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , Immune Evasion , SARS-CoV-2/isolation & purification , Antibodies, Neutralizing/immunology , Botswana/epidemiology , COVID-19/immunology , COVID-19/transmission , Humans , Models, Molecular , Mutation , Phylogeny , Recombination, Genetic , SARS-CoV-2/classification , SARS-CoV-2/immunology , South Africa/epidemiology , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/immunology
6.
Science ; 374(6566): 423-431, 2021 Oct 22.
Article in English | MEDLINE | ID: covidwho-1483977

ABSTRACT

The progression of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in Africa has so far been heterogeneous, and the full impact is not yet well understood. In this study, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations predominantly from Europe, which diminished after the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1, and C.1.1. Although distorted by low sampling numbers and blind spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a source for new variants.


Subject(s)
COVID-19/epidemiology , Epidemiological Monitoring , Genomics , Pandemics , SARS-CoV-2/genetics , Africa/epidemiology , COVID-19/transmission , COVID-19/virology , Genetic Variation , Humans , SARS-CoV-2/isolation & purification
7.
Nat Med ; 27(3): 440-446, 2021 03.
Article in English | MEDLINE | ID: covidwho-1319035

ABSTRACT

The first severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in South Africa was identified on 5 March 2020, and by 26 March the country was in full lockdown (Oxford stringency index of 90)1. Despite the early response, by November 2020, over 785,000 people in South Africa were infected, which accounted for approximately 50% of all known African infections2. In this study, we analyzed 1,365 near whole genomes and report the identification of 16 new lineages of SARS-CoV-2 isolated between 6 March and 26 August 2020. Most of these lineages have unique mutations that have not been identified elsewhere. We also show that three lineages (B.1.1.54, B.1.1.56 and C.1) spread widely in South Africa during the first wave, comprising ~42% of all infections in the country at the time. The newly identified C lineage of SARS-CoV-2, C.1, which has 16 nucleotide mutations as compared with the original Wuhan sequence, including one amino acid change on the spike protein, D614G (ref. 3), was the most geographically widespread lineage in South Africa by the end of August 2020. An early South African-specific lineage, B.1.106, which was identified in April 2020 (ref. 4), became extinct after nosocomial outbreaks were controlled in KwaZulu-Natal Province. Our findings show that genomic surveillance can be implemented on a large scale in Africa to identify new lineages and inform measures to control the spread of SARS-CoV-2. Such genomic surveillance presented in this study has been shown to be crucial in the identification of the 501Y.V2 variant in South Africa in December 2020 (ref. 5).


Subject(s)
COVID-19/epidemiology , COVID-19/virology , SARS-CoV-2/genetics , Datasets as Topic , Genome, Viral , Humans , Molecular Typing , Mutation , Pandemics , Phylogeny , Phylogeography , Real-Time Polymerase Chain Reaction , SARS-CoV-2/classification , SARS-CoV-2/isolation & purification , Sequence Analysis, RNA , South Africa/epidemiology , Whole Genome Sequencing
8.
Nature ; 592(7854): 438-443, 2021 04.
Article in English | MEDLINE | ID: covidwho-1164876

ABSTRACT

Continued uncontrolled transmission of SARS-CoV-2 in many parts of the world is creating conditions for substantial evolutionary changes to the virus1,2. Here we describe a newly arisen lineage of SARS-CoV-2 (designated 501Y.V2; also known as B.1.351 or 20H) that is defined by eight mutations in the spike protein, including three substitutions (K417N, E484K and N501Y) at residues in its receptor-binding domain that may have functional importance3-5. This lineage was identified in South Africa after the first wave of the epidemic in a severely affected metropolitan area (Nelson Mandela Bay) that is located on the coast of the Eastern Cape province. This lineage spread rapidly, and became dominant in Eastern Cape, Western Cape and KwaZulu-Natal provinces within weeks. Although the full import of the mutations is yet to be determined, the genomic data-which show rapid expansion and displacement of other lineages in several regions-suggest that this lineage is associated with a selection advantage that most plausibly results from increased transmissibility or immune escape6-8.


Subject(s)
COVID-19/virology , Mutation , Phylogeny , Phylogeography , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , COVID-19/epidemiology , COVID-19/immunology , COVID-19/transmission , DNA Mutational Analysis , Evolution, Molecular , Genetic Fitness , Humans , Immune Evasion , Models, Molecular , SARS-CoV-2/immunology , SARS-CoV-2/pathogenicity , Selection, Genetic , South Africa/epidemiology , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/metabolism , Time Factors
9.
Microbiol Resour Announc ; 9(27)2020 Jul 02.
Article in English | MEDLINE | ID: covidwho-630676

ABSTRACT

As a contribution to the global efforts to track and trace the ongoing coronavirus pandemic, here we present the sequence, phylogenetic analysis, and modeling of nonsynonymous mutations for a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome that was detected in a South African patient with coronavirus disease 2019 (COVID-19).

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