Early assessment of the clinical severity of the SARS-CoV-2 Omicron variant in South Africa

BackgroundThe 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. MethodsWe 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. ResultsFrom 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). ConclusionEarly 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.

Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa

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 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) 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.

SARS-CoV-2 reinfection trends in South Africa: analysis of routine surveillance data

IntroductionGlobally, there have been more than 404 million cases of SARS-CoV-2, with 5.8 million confirmed deaths, as of February 2022. South Africa has experienced four waves of SARS-CoV-2 transmission, with the second, third, and fourth waves being driven by the Beta, Delta, and Omicron variants, respectively. A key question with the emergence of new variants is the extent to which they are able to reinfect those who have had a prior natural infection. RationaleWe developed two approaches to monitor routine epidemiological surveillance data to examine whether SARS-CoV-2 reinfection risk has changed through time in South Africa, in the context of the emergence of the Beta (B.1.351), Delta (B.1.617.2), and Omicron (B.1.1.529) variants. We analyze line list data on positive tests for SARS-CoV-2 with specimen receipt dates between 04 March 2020 and 31 January 2022, collected through South Africas National Notifiable Medical Conditions Surveillance System. Individuals having sequential positive tests at least 90 days apart were considered to have suspected reinfections. Our routine monitoring of reinfection risk included comparison of reinfection rates to the expectation under a null model (approach 1) and estimation of the time-varying hazards of infection and reinfection throughout the epidemic (approach 2) based on model-based reconstruction of the susceptible populations eligible for primary and second infections. Results105,323 suspected reinfections were identified among 2,942,248 individuals with laboratory-confirmed SARS-CoV-2 who had a positive test result at least 90 days prior to 31 January 2022. The number of reinfections observed through the end of the third wave in September 2021 was 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: 0.71 (CI95: 0.60-0.85); for wave 3 versus wave 1: 0.54 (CI95: 0.45-0.64)). In contrast, the recent spread of the Omicron variant has been associated with an increase in reinfection hazard coefficient. The estimated hazard ratio for reinfection versus primary infection versus wave 1 was 1.75 (CI95: 1.48-2.10) for the period of Omicron emergence (01 November 2021 to 30 November 2021) and 1.70 (CI95: 1.44-2.04) for wave 4 versus wave 1. Individuals with identified reinfections since 01 November 2021 had experienced primary infections in all three prior waves, and an increase in third infections has been detected since mid-November 2021. Many individuals experiencing third infections had second infections during the third (Delta) wave that ended in September 2021, strongly suggesting that these infections resulted from immune evasion rather than waning immunity. ConclusionPopulation-level evidence suggests that the Omicron variant is associated with substantial ability to evade immunity from prior infection. In contrast, there is no population-wide epidemiological evidence of immune escape associated with the Beta or Delta variants. This finding has important implications for public health planning, particularly in countries like South Africa with high rates of immunity from prior infection. Further development of methods to track reinfection risk during pathogen emergence, including refinements to assess the impact of waning immunity, account for vaccine-derived protection, and monitor the risk of multiple reinfections will be an important tool for future pandemic preparedness.

The continuous evolution of SARS-CoV-2 in South Africa: a new lineage with rapid accumulation of mutations of concern and global detection

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.

Persistent SARS-CoV-2 infection and intra-host evolution in association with advanced HIV infection

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 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.

Emergence and rapid spread of a new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) lineage with multiple spike mutations in South Africa

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.

Major new lineages of SARS-CoV-2 emerge and spread in South Africa during lockdown.

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.