Dataset Information

Multiple Early Introductions of SARS-CoV-2 to Cape Town, South Africa.

ABSTRACT: Cape Town was the first city in South Africa to experience the full impact of the coronavirus disease 2019 (COVID-19) pandemic. We acquired samples from all suspected cases and their contacts during the first month of the pandemic from Tygerberg Hospital. Nanopore sequencing generated SARS-CoV-2 whole genomes. Phylogenetic inference with maximum likelihood and Bayesian methods were used to determine lineages that seeded the local epidemic. Three patients were known to have travelled internationally and an outbreak was detected in a nearby supermarket. Sequencing of 50 samples produced 46 high-quality genomes. The sequences were classified as lineages: B, B.1, B.1.1.1, B.1.1.161, B.1.1.29, B.1.8, B.39, and B.40. All the sequences from persons under investigation (PUIs) in the supermarket outbreak (lineage B.1.8) fall within a clade from the Netherlands with good support (p > 0.9). In addition, a new mutation, 5209A>G, emerged within the Cape Town cluster. The molecular clock analysis suggests that this occurred around 13 March 2020 (95% confidence interval: 9-17 March). The phylogenetic reconstruction suggests at least nine early introductions of SARS-CoV-2 into Cape Town and an early localized transmission in a shopping environment. Genomic surveillance was successfully used to investigate and track the spread of early introductions of SARS-CoV-2 in Cape Town.

SUBMITTER: Engelbrecht S

PROVIDER: S-EPMC8005015 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Multiple Early Introductions of SARS-CoV-2 to Cape Town, South Africa.

Engelbrecht Susan S Delaney Kayla K Kleinhans Bronwyn B Wilkinson Eduan E Tegally Houriiyah H Stander Tania T van Zyl Gert G Preiser Wolfgang W de Oliveira Tulio T

Viruses 20210322 3

Cape Town was the first city in South Africa to experience the full impact of the coronavirus disease 2019 (COVID-19) pandemic. We acquired samples from all suspected cases and their contacts during the first month of the pandemic from Tygerberg Hospital. Nanopore sequencing generated SARS-CoV-2 whole genomes. Phylogenetic inference with maximum likelihood and Bayesian methods were used to determine lineages that seeded the local epidemic. Three patients were known to have travelled internationa ...[more]

PMID: 33810168

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Project description:BackgroundCoronavirus disease 2019 (COVID-19) is associated with hematological abnormalities of variable severity. The full blood count (FBC) and leukocyte differential count (DIFF) could facilitate the prediction of disease severity and outcome in COVID-19. This study aimed to assess the hematological parameters in early severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and their correlation with disease outcome.MethodsA retrospective cross-sectional descriptive study was performed. Adults with a FBC and positive SARS-CoV-2 polymerase chain reaction results between March 1, and June 31, 2020 were reviewed. Basic hematological parameters (FBC, DIFF) and human immunodeficiency virus (HIV) status were recorded. Outcome measures were admission to a general ward or intensive care unit (ICU), recovery or death.ResultsSix hundred and eighty-five cases median age 51 years, were analyzed. Forty-four percent were males and fourteen percent were HIV-positive with no association between death and/or ICU admission (p = 0.522 and p = 0.830, respectively). Leucocytosis was predictive of ICU admission (odds ratio [OR]: 2.4, confidence interval [CI]: 1.77-3.8186) and neutrophilia, of both mortality (OR: 1.5, CI: 1.0440-2.0899) and ICU admission (OR: 4, CI: 2.5933-6.475). Median lymphocyte count was decreased and d-dimer raised, showing no significant association with outcome. Raised neutrophil-to-lymphocyte-ratio (NLR) was associated with increased odds of mortality (OR: 2.5, CI: 1.3556-3.2503) and ICU admission (OR: 4.8, CI: 2.4307-9.5430) as was monocyte-to-lymphocyte-ratio (MLR) (OR: 2, CI: 1.3132-2.9064) and (OR: 2.3, CI: 1.0608-1.9935), respectively. Hospital admission and older age were significantly associated with mortality (p = 0.0008 and p < 0.0001), respectively.ConclusionEvidence-based interpretation of routine laboratory parameters, readily available in resource-constrained settings, may identify patients at increased risk of mortality. The FBC, DIFF, NLR, and MLR should form part of the early COVID-19 investigation.

Project description:In low- and middle-income countries where SARS-CoV-2 testing is limited, seroprevalence studies can help describe and characterise the extent of the pandemic, as well as elucidate protection conferred by prior exposure. We conducted repeated cross-sectional serosurveys (July 2020 -November 2021) using residual samples from patients from Cape Town, South Africa, sent for routine laboratory studies for non-COVID-19 conditions. SARS-CoV-2 anti-nucleocapsid antibodies and linked clinical information were used to investigate: (1) seroprevalence over time and risk factors associated with seropositivity, (2) ecological comparison of seroprevalence between subdistricts, (3) case ascertainment rates, and (4) the relative protection against COVID-19 associated with seropositivity and vaccination statuses. Among the subset sampled, seroprevalence of SARS-CoV-2 in Cape Town increased from 39.19% (95% confidence interval [CI] 37.23-41.19) in July 2020 to 67.8% (95%CI 66.31-69.25) in November 2021. Poorer communities had both higher seroprevalence and COVID-19 mortality. Only 10% of seropositive individuals had a recorded positive SARS-CoV-2 test. Using COVID-19 hospital admission and death data at the Provincial Health Data Centre, antibody positivity before the start of the Omicron BA.1 wave (28 November 2021) was strongly protective for severe disease (adjusted odds ratio [aOR] 0.15; 95%CI 0.05-0.46), with additional benefit in those who were also vaccinated (aOR 0.07, 95%CI 0.01-0.35). The high population seroprevalence in Cape Town was attained at the cost of substantial COVID-19 mortality. At the individual level, seropositivity was highly protective against subsequent infections and severe COVID-19 disease. In low-income communities, where diagnostic testing capacity is often limited, surveillance systems dependent on them will underestimate the true extent of an outbreak. Rapidly conducted seroprevalence studies can play an important role in addressing this.

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Dataset Information

Multiple Early Introductions of SARS-CoV-2 to Cape Town, South Africa.

Publications

Multiple Early Introductions of SARS-CoV-2 to Cape Town, South Africa.

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