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1.
preprints.org; 2023.
Preprint in English | PREPRINT-PREPRINTS.ORG | ID: ppzbmed-10.20944.preprints202306.0384.v1

ABSTRACT

The high demand for SARS-CoV-2 tests but limited supply to South African laboratories early in the COVID19 pandemic, resulted in a heterogenous diagnostic footprint of open and closed molecular testing platforms. Novel approaches were required to monitor test quality especially during the introduction of newly circulating variants. The National Health Laboratory Service centrally collected cycle threshold (Ct) values from 1,497,669 test results reported from six commonly used PCR assays in 36 months, and visually monitored changes in their median Ct within a 28-day centered moving average for each assays’ gene targets. This continuous quality monitoring rapidly identified delayed hybridization of RdRp in the Allplex™ SARS-CoV-2 assay due to the Delta (B.1.617.2) variant; S-gene target failure in the TaqPath™ COVID-19 assay due to B.1.1.7 (Alpha) and the B.1.1.529 (Omicron); and recently E-gene delayed hybridization in the Xpert® Xpress SARS-CoV-2 due to XBB.1.5. This near “real-time” monitoring helped inform the need for sequencing and the importance of multiplex molecular nucleic acid amplification technology designs used in diagnostics for patient care. This continuous quality monitoring approach at the granularity of Ct values should be included in ongoing surveillance and with application to other disease use cases that rely on molecular diagnostics.


Subject(s)
Severe Acute Respiratory Syndrome , COVID-19
2.
researchsquare; 2022.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-1792132.v1

ABSTRACT

Omicron lineages BA.4 and BA.5 drove a fifth wave of COVID-19 cases in South Africa. We assessed the severity of BA.4/BA.5 infections using the presence/absence of the S-gene target for infections diagnosed using the TaqPath PCR assay between 1 October 2021 and 26 April 2022. We linked national COVID-19 individual-level data including case, laboratory test and hospitalisation data. We assessed 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 (aOR1.24, 95% CI 0.98–1.55) and severe outcome (aOR 0.71, 95%CI 0.41–1.25) compared to BA.1-infected individuals. Newly emerged Omicron lineages BA.4/BA.5 continue to show reduced clinical severity compared to previous variants, as observed for Omicron BA.1.


Subject(s)
COVID-19
3.
Raquel Viana; Sikhulile Moyo; Daniel Gyamfi Amoako; Houriiyah Tegally; Cathrine Scheepers; Richard J Lessells; Jennifer Giandhari; Nicole Wolter; Josie Everatt; Andrew Rambaut; Christian Althaus; Eduan Wilkinson; Adriano Mendes; Amy Strydom; Michaela Davids; Simnikiwe Mayaphi; Simani Gaseitsiwe; Wonderful T Choga; Dorcas Maruapula; Boitumelo Zuze; Botshelo Radibe; Legodile Koopile; Roger Shapiro; Shahin Lockman; Mpaphi B. Mbulawa; Thongbotho Mphoyakgosi; Pamela Smith-Lawrence; Mosepele Mosepele; Mogomotsi Matshaba; Kereng Masupu; Mohammed Chand; Charity Joseph; Lesego Kuate-Lere; Onalethatha Lesetedi-Mafoko; Kgomotso Moruisi; Lesley Scott; Wendy Stevens; Constantinos Kurt Wibmer; Anele Mnguni; Arshad Ismail; Boitshoko Mahlangu; Darren P. Martin; Verity Hill; Rachel Colquhoun; Modisa S. Motswaledi; James Emmanuel San; Noxolo Ntuli; Gerald Motsatsi; Sureshnee Pillay; Thabo Mohale; Upasana Ramphal; Yeshnee Naidoo; Naume Tebeila; Marta Giovanetti; Koleka Mlisana; Carolyn Williamson; Nei-yuan Hsiao; Nokukhanya Msomi; Kamela Mahlakwane; Susan Engelbrecht; Tongai Maponga; Wolfgang Preiser; Zinhle Makatini; Oluwakemi Laguda-Akingba; Lavanya Singh; Ugochukwu J. Anyaneji; Monika Moir; Stephanie van Wyk; Derek Tshiabuila; Yajna Ramphal; Arisha Maharaj; Sergei Pond; Alexander G Lucaci; Steven Weaver; Maciej F Boni; Koen Deforche; Kathleen Subramoney; Diana Hardie; Gert Marais; Deelan Doolabh; Rageema Joseph; Nokuzola Mbhele; Luicer Olubayo; Arash Iranzadeh; Alexander E Zarebski; Joseph Tsui; Moritz UG Kraemer; Oliver G Pybus; Dominique Goedhals; Phillip Armand Bester; Martin M Nyaga; Peter N Mwangi; Allison Glass; Florette Treurnicht; Marietjie Venter; Jinal N. Bhiman; Anne von Gottberg; Tulio de Oliveira.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.12.19.21268028

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants respectively. 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) 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, 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)
Severe Acute Respiratory Syndrome
4.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.12.19.21268038

ABSTRACT

A new SARS-CoV-2 variant of concern, Omicron (B.1.1.529), has been identified based on genomic sequencing and epidemiological data in South Africa. Presumptive Omicron cases in South Africa have grown extremely rapidly, despite high prior exposure and moderate vaccination coverage. The available evidence suggests that Omicron spread is at least in part due to evasion of this immune protection, though Omicron may also exhibit higher intrinsic transmissibility. Using detailed laboratory and epidemiological data from South Africa, we estimate the constraints on these two characteristics of the new variant and their relationship. Our estimates and associated uncertainties provide essential information to inform projection and scenario modeling analyses, which are crucial planning tools for governments around the world. One Sentence Summary We report a region of plausibility for the relative transmissibility and immune escape characteristics of the SARS-CoV-2 Omicron variant estimated by integrating laboratory and epidemiological data from South Africa.

5.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.12.21.21268116

ABSTRACT

ABSTRACT Background The SARS-CoV-2 Omicron variant of concern (VOC) almost completely replaced other variants in South Africa during November 2021, and was associated with a rapid increase in COVID-19 cases. We aimed to assess clinical severity of individuals infected with Omicron, using S Gene Target Failure (SGTF) on the Thermo Fisher Scientific TaqPath COVID-19 PCR test as a proxy. Methods We performed data linkages for (i) SARS-CoV-2 laboratory tests, (ii) COVID-19 case data, (iii) genome data, and (iv) the DATCOV national hospital surveillance system for the whole of South Africa. For cases identified using Thermo Fisher TaqPath COVID-19 PCR, infections were designated as SGTF or non-SGTF. Disease severity was assessed using multivariable logistic regression models comparing SGTF-infected individuals diagnosed between 1 October to 30 November to (i) non-SGTF in the same period, and (ii) Delta infections diagnosed between April and November 2021. Results From 1 October through 6 December 2021, 161,328 COVID-19 cases were reported nationally; 38,282 were tested using TaqPath PCR and 29,721 SGTF infections were identified. The proportion of SGTF infections increased from 3% in early October (week 39) to 98% in early December (week 48). On multivariable analysis, after controlling for factors associated with hospitalisation, individuals with SGTF infection had lower odds of being admitted to hospital compared to non-SGTF infections (adjusted odds ratio (aOR) 0.2, 95% confidence interval (CI) 0.1-0.3). Among hospitalised individuals, after controlling for factors associated with severe disease, the odds of severe disease did not differ between SGTF-infected individuals compared to non-SGTF individuals diagnosed during the same time period (aOR 0.7, 95% CI 0.3-1.4). Compared to earlier Delta infections, after controlling for factors associated with severe disease, SGTF-infected individuals had a lower odds of severe disease (aOR 0.3, 95% CI 0.2-0.5). Conclusion Early analyses suggest a reduced risk of hospitalisation among SGTF-infected individuals when compared to non-SGTF infected individuals in the same time period. Once hospitalised, risk of severe disease was similar for SGTF- and non-SGTF infected individuals, while SGTF-infected individuals had a reduced risk of severe disease when compared to earlier Delta-infected individuals. Some of this reducton is likely a result of high population immunity.


Subject(s)
COVID-19
6.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.11.11.21266068

ABSTRACT

Objective: To examine whether SARS-CoV-2 reinfection risk has changed through time in South Africa, in the context of the emergence of the Beta and Delta variants Design: Retrospective analysis of routine epidemiological surveillance data Setting: Line list data on SARS-CoV-2 with specimen receipt dates between 04 March 2020 and 30 June 2021, collected through South Africa's National Notifiable Medical Conditions Surveillance System Participants: 1,551,655 individuals with laboratory-confirmed SARS-CoV-2 who had a positive test result at least 90 days prior to 30 June 2021. Individuals having sequential positive tests at least 90 days apart were considered to have suspected reinfections. Main outcome measures: Incidence of suspected reinfections through time; comparison of reinfection rates to the expectation under a null model (approach 1); empirical estimates of the time-varying hazards of infection and reinfection throughout the epidemic (approach 2) Results: 16,029 suspected reinfections were identified. The number of reinfections observed through the end of June 2021 is consistent with the null model of no change in reinfection risk (approach 1). Although increases in the hazard of primary infection were observed following the introduction of both the Beta and Delta variants, no corresponding increase was observed in the reinfection hazard (approach 2). Contrary to expectation, the estimated hazard ratio for reinfection versus primary infection was lower during waves driven by the Beta and Delta variants than for the first wave (relative hazard ratio for wave 2 versus wave 1: 0.75 (95% CI: 0.59-0.97); for wave 3 versus wave 1: 0.70 (95% CI: 0.55-0.90)). Although this finding may be partially explained by changes in testing availability, it is also consistent with a scenario in which variants have increased transmissibility but little or no evasion of immunity. Conclusion: We conclude there is no population-wide epidemiological evidence of immune escape and recommend ongoing monitoring of these trends.

7.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.09.23.21264018

ABSTRACT

The Beta variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in South Africa in late 2020 and rapidly became the dominant variant, causing over 95% of infections in the country during and after the second epidemic wave. Here we show rapid replacement of the Beta variant by the Delta variant, a highly transmissible variant of concern (VOC) that emerged in India and subsequently spread around the world. The Delta variant was imported to South Africa primarily from India, spread rapidly in large monophyletic clusters to all provinces, and became dominant within three months of introduction. This was associated with a resurgence in community transmission, leading to a third wave which was associated with a high number of deaths. We estimated a growth advantage for the Delta variant in South Africa of 0.089 (95% confidence interval [CI] 0.084-0.093) per day which corresponds to a transmission advantage of 46% (95% CI 44-48) compared to the Beta variant. These data provide additional support for the increased transmissibility of the Delta variant relative to other VOC and highlight how dynamic shifts in the distribution of variants contribute to the ongoing public health threat.


Subject(s)
Coronavirus Infections
8.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.08.20.21262342

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 emergence of C.1.2, associated with a high substitution rate, includes changes within the spike protein that have been associated with increased transmissibility or reduced neutralization sensitivity in SARS-CoV-2 VOC/VOIs. 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 showed 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.

9.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.06.03.21258228

ABSTRACT

While most people effectively clear SARS-CoV-2, there are several reports of prolonged infection in immunosuppressed individuals. Here we present a case of prolonged infection of greater than 6 months with the shedding of high titter SARS-CoV-2 in an individual with advanced HIV and antiretroviral treatment failure. Through whole-genome sequencing at multiple time points, we demonstrate the early emergence of the E484K substitution associated with escape from neutralizing antibodies, followed by other escape mutations and the N501Y substitution found in most variants of concern. This provides support to the hypothesis of intra-host evolution as one mechanism for the emergence of SARS-CoV-2 variants with immune evasion properties.


Subject(s)
COVID-19 , HIV Infections
10.
ssrn; 2021.
Preprint in English | PREPRINT-SSRN | ID: ppzbmed-10.2139.ssrn.3792114

ABSTRACT

Background: We describe the epidemiology of COVID-19 in South Africa following importation and during implementation of stringent lockdown measures.Methods: Using national surveillance data including demographics, laboratory test data, clinical presentation, risk exposures (travel history, contacts and occupation) and outcomes of persons undergoing COVID-19 testing or hospitalised with COVID-19 at sentinel surveillance sites, we generated and interpreted descriptive statistics, epidemic curves, and initial reproductive numbers (Rt).Findings: From 4 March to 30 April 2020, 271,670 SARS-CoV-2 PCR tests were performed (462 tests/100,000 persons). Of these, 7,892 (2.9%) persons tested positive (median age 37 years (interquartile range 28-49 years), 4,568 (58%) male, cumulative incidence of 13.4 cases/100,000 persons). Hospitalization records were found for 1,271 patients (692 females (54%)) of whom 186 (14.6%) died. Amongst 2,819 cases with data, 489/2819 (17.3%) travelled internationally within 14 days prior to diagnosis, mostly during March 2020 (466 (95%)). Cases diagnosed in April compared with March were younger (median age, 37 vs. 40 years), less likely female (38% vs. 53%) and resident in a more populous province (98% vs. 91%). The national initial Rt was 2.08 (95% confidence interval (CI): 1.71-2.51).Interpretation: The first eight weeks following COVID-19 importation were characterised by early predominance of imported cases and relatively low mortality and transmission rates. Despite stringent lockdown measures, the second month following importation was characterised by community transmission and increasing disease burden in more populous provinces.Funding Statement: South African National and provincial health departments.Declaration of Interests: We declare no competing interests.Ethics Approval Statement: Surveillance activities for NMC including SARS-COV-2 infection are conducted by the NICD according to National Health Act Regulations. Publication of surveillance data in the peer-reviewed literature was approved by the University of the Witwatersrand Human Research Ethics Committee (Medical) protocol M160667.


Subject(s)
COVID-19
11.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.12.21.20248640

ABSTRACT

Continued uncontrolled transmission of the severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) in many parts of the world is creating the conditions for significant virus evolution. Here, we describe a new SARS-CoV-2 lineage (501Y.V2) characterised by eight lineage-defining mutations in the spike protein, including three at important residues in the receptor-binding domain (K417N, E484K and N501Y) that may have functional significance. This lineage emerged in South Africa after the first epidemic wave in a severely affected metropolitan area, Nelson Mandela Bay, located on the coast of the Eastern Cape Province. This lineage spread rapidly, becoming within weeks the dominant lineage in the Eastern Cape and Western Cape Provinces. Whilst the full significance of the mutations is yet to be determined, the genomic data, showing the rapid displacement of other lineages, suggest that this lineage may be associated with increased transmissibility.

12.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.10.28.20221143

ABSTRACT

In March 2020, the first cases of COVID-19 were reported in South Africa. The epidemic spread very fast despite an early and extreme lockdown and infected over 600,000 people, by far the highest number of infections in an African country. To rapidly understand the spread of SARS-CoV-2 in South Africa, we formed the Network for Genomics Surveillance in South Africa (NGS-SA). Here, we analyze 1,365 high quality whole genomes and identify 16 new lineages of SARS-CoV-2. Most of these unique lineages have mutations that are found hardly anywhere else in the world. We also show that three lineages spread widely in South Africa and contributed to ~42% of all of the infections in the country. This included the first identified C lineage of SARS-CoV-2, C.1, which has 16 mutations as compared with the original Wuhan sequence. C.1 was the most geographically widespread lineage in South Africa, causing infections in multiple provinces and in all of the eleven districts in KwaZulu-Natal (KZN), the most sampled province. Interestingly, the first South-African specific lineage, B.1.106, which was identified in April 2020, became extinct after nosocomial outbreaks were controlled. Our findings show that genomic surveillance can be implemented on a large scale in Africa to identify and control the spread of SARS-CoV-2.


Subject(s)
COVID-19
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