TNFAIP3-interacting protein 1 polymorphisms and their association with symptomatic human respiratory syncytial virus infection and bronchiolitis in infants younger than one year from South Africa: A case-control study

Objectives: This study analyzed the association of TNFAIP3-interacting protein 1 (TNIP1) polymorphisms with the symptomatic human respiratory syncytial virus (HRSV) infection and bronchiolitis in infants. Methods: A case-control study was conducted involving 129 hospitalized infants with symptomatic HRSV infection (case group) and 161 healthy infants (control group) in South Africa (2016-2018). Six TNIP1 polymorphisms (rs869976, rs4958881, rs73272842, rs3792783, rs17728338, and rs999011) were genotyped. Genetic associations were evaluated using logistic regression adjusted by age and gender. Results: Both rs73272842 G and rs999011 C alleles were associated with reduced odds for symptomatic HRSV infection (adjusted odd ratio [aOR] = 0.68 [95% confidence interval {CI} = 0.48-0.96] and aOR = 0.36 [95% CI = 0.19-0.68], respectively] and bronchiolitis (aOR = 0.71 [95% CI = 0.50-1.00] and aOR = 0.38 [95% CI = 0.22-0.66], respectively). The significance of these associations was validated using the BCa Bootstrap method (P <0.05). The haplotype GC (composed of rs73272842 and rs999011) was associated with reduced odds of symptomatic HRSV infection (aOR = 0.53 [95% CI = 0.37-0.77]) and bronchiolitis (aOR = 0.62 [95% CI = 0.46-0.84]), which were validated by the BCa Bootstrap method (P = 0.002 for both). Conclusion: TNIP1 rs73272842 G allele and rs999011 C allele were associated with reduced odds of symptomatic HRSV infection and the development of bronchiolitis in infants, suggesting that TNIP1 polymorphisms could impact susceptibility to HRSV illness.The study was funded by Poliomyelitis Research Foundation (grant # 19/27 to FKT), South Africa. The study was also funded by the CIBER -Consorcio Centro de Investigación Biomédica en Red- (CB 2021), Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea – NextGenerationEU (grant #CB21/13/00044 to SR).S

Wastewater-integrated pathogen surveillance dashboards enable real-time, transparent, and interpretable public health risk assessment and dissemination.

Timely pathogen surveillance and reporting is essential for effective public health guidance. Web dashboards have become a key tool for communicating public health information to stakeholders, health care workers, and the broader community. Over the SARS-CoV-2 pandemic, wastewater surveillance has increasingly been incorporated into public health workflows for outbreak monitoring and response, enabling community-representative and low-cost monitoring to supplement clinical surveillance. However, the methods used for visualization and dissemination of clinical and wastewater surveillance data differ across programs, and best practices are yet to be defined. In this work, we demonstrate data workflows and dashboards used to perform wastewater-based public health surveillance in tandem with clinical data across local and national scales, leveraging custom-built, reproducible, and open-source software. Using a centralized data aggregation and analysis hub approach, we establish multiple data pipelines for data storage, wrangling, and standardized analyses, and deploy custom-built web dashboards that allow for immediate public release. We find that our approach is effective across scales, computing architectures, and dissemination strategies, and provides an adaptable model to incorporate additional pathogens and epidemiological data

Emergence of SARS-CoV-2 Omicron lineages BA.4 and BA.5 in South Africa

Three lineages (BA.1, BA.2 and BA.3) of the SARS-CoV-2 Omicron variant of concern predominantly drove South Africa's fourth COVID-19 wave. We have now identified two new lineages, BA.4 and BA.5, responsible for a fifth wave of infections. The spike proteins of BA.4 and BA.5 are identical, and comparable to BA.2 except for the addition of 69-70del (present in the Alpha variant and the BA.1 lineage), L452R (present in the Delta variant), F486V and the wild type amino acid at Q493.The two lineages only differ outside of the spike region. The 69-70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure, on the background of variants not possessing this feature . BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa by the first week of April 2022. Using a multinomial logistic regression model, we estimate growth advantages for BA.4 and BA.5 of 0.08 (95% CI: 0.08 - 0.09) and 0.10 (95% CI: 0.09 - 0.11) per day respectively over BA.2 in South Africa. The continued discovery of genetically diverse Omicron lineages points to the hypothesis that a discrete reservoir, such as human chronic infections and/or animal hosts, is potentially contributing to further evolution and dispersal of the virus

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.Temple University. College of Science and TechnologyBiolog

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

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Molecular epidemiology and characteristics of immune adaptations across the SARS-CoV-2 spike glycoproteins from Gauteng, South Africa, 2020 to 2022

A research report submitted in fulfillment of the requirements for the Doctor of Philosophy, in the Faculty of Health Sciences, School of Pathology, University of the Witwatersrand, Johannesburg, 2024The SARS-CoV-2 global pandemic has been fueled by several variants of concern (VOC) that have gained more efficient transmission or immune evasion properties over time. To better understand the diversity and evolutionary characteristics of SARS-CoV-2 lineages in South Africa we described the analysed the SARS-CoV-2 lineages and VOCs circulating during 2020 to 2022, as well the impact of the S protein and its potential to act as a candidate vaccine. The first objective of this study was to rapidly identify emerging VOCs based on key SARS- CoV-2 S protein mutations. The second objective was to describe the impact of intra-host immune adaptations on the evolution of SARS-CoV-2 S protein genes among individuals with SARS-CoV-2 infections. Thirdly, by timing the emergence SARS-CoV-2 dominant variants we aimed to unravel the significance and abundance of low-frequency lineages that emerged during five COVID-19 waves in South Africa. The final objective was to assess if accounting for diversity among SARS-CoV-2 S protein’s improved predicted epitope coverage of a derived immunogen. Single nucleotide polymorphism (SNP) PCR-based genotyping assays targeting specific mutations were used to detect VOCs that circulated in 2021. The allele frequencies (AF) as determined by SNP PCR analysis and variant calling from FASTQ reads using galaxy.eu were performed to describe intra-host SARS-CoV-2 S protein variants. Whole genome sequencing was performed to identify and analyse SARS-CoV-2 strains circulating in South Africa from 2020 to 2022 and detect low-frequency lineages. Mosaic vaccine suite tools were used to design an optimal S protein construct from sequences generated in this study. The construct was further tested for antigenicity, toxicity, N- and O-linked glycosylation sites and CTL predictions. A combination of P681R and L452R SNPs were detected in 73.6% (538/731) of the samples classified as Delta, while N501Y and del69/70 SNPs were detected in 3.6% (26/731) of samples classified as Alpha. 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. SNP assays detected 5.3% of cases with Delta that displayed heterogeneity at delY144, E484Q, N501Y and P681H. However, heterogeneity was confirmed by sequencing only for the E484Q and Characterisation of SARS-CoV-2 Page 9 of 155 delY144 mutations. Variant calling from FASTQ reads identified intra-host diversity in the S protein among 9% of cases that were infected with Beta, Delta, Omicron BA.1, BA.2.15, and BA.4 lineages. Heterogeneity was primarily identified at positions 19 (1.4%) with T19IR 371 (92.3%) with S371FP, and 484 (1.9%) with E484AK, E484AQ and E484KQ. In 2020, 24 lineages were detected, with B.1 (3%; 8/278), B.1.1 (16%; 45/278), B.1.1.348 (3%; 8/278), B.1.1.52 (5%; 13/278), C.1 (13%; 37/278) and C.2 (2%; 6/278) circulating during the first wave. Beta dominating the second wave of infection in 2020. B.1 and B.1.1 continued to circulate at low frequencies in 2021 and B.1.1 re-emerged in 2022. Beta was outcompeted by Delta in 2021, which was thereafter outcompeted by Omicron sub-lineages during the 4th and 5th waves in 2022. Several significant mutations (del69-70, delY144, E484K, N501Y and D614G) identified in VOCs were also detected in low-frequency lineages. During the 5 waves of infection, B.1 and C.1/ C.2 lineages co-circulated with a dominant VOC. Following our findings of co-circulation of VOCs and other lineages and evidence of quasispecies we investigated if accounting for diversity of SARS-CoV-2 strains would render an improved S immunogen. The optimal mosaic S protein generated had predicted CTL epitope coverage of ~95% to 98% and was classified as an antigen based on a prediction score of 0.47. Reverse translation was used to generate the novel S gene for the expression construct SC2M2. The NTD and RBD regions were non-toxic, and the derived novel S protein comprised 10 additional N-linked glycosylation sites and 4 O-linked glycosylation sites when compared to the Wuhan Hu-1 strain. Our study findings have shown that (i) rapid detection of emerging VOCs was possible using SNP genotyping assays, and can be used by low to middle income countries to detect Alpha, Beta, Delta and Omicron BA.1; (ii) heterogeneity within the S protein encourages escape from neutralising antibodies and the evolution of SARS-CoV-2, which may contribute to the ongoing emergence of new variants associated with continued outbreaks globally; (iii) low frequency lineages that share mutations with VOCs could lead to convergence and recombination events that result in the next novel lineages or variants that may further increase transmissibility, infectivity and escape immunity; and lastly (iv) the novel S expression construct designed, based on previous and currently circulating VOCs and lineages, could potentially be used to develop improved SARS-CoV-2 vaccines.MM202

Characterisation of RSV Fusion Proteins from South African Patients with RSV Disease, 2019 to 2020

Respiratory syncytial virus (RSV) is classified into RSV-A and RSV-B, which are further classified into genotypes based on variability in the G gene. The fusion (F) protein is highly conserved; however, variability within antigenic sites has been reported. This study aimed to characterise F proteins from RSV strains detected in South Africa from 2019 to 2020. Patients of all ages, from whom respiratory samples were submitted to the National Health Laboratory Service at Charlotte Maxeke Johannesburg Academic Hospital, South Africa during 2019 to 2020, were included. Complete RSV F genes were amplified for next-generation sequencing. MEGA X software was used for phylogenetic analysis. The overall prevalence of RSV was 5.8% (101/1734). Among 101 RSV positive samples only 69.3% (70/101) were available for characterization of the RSV F protein gene. Among cases included for F gene characterisation, viral co-infections were observed in 50% (35/70) and 25.7% (18/70) were admitted to intensive care units (ICU). About 74.2% (23/31) of F gene sequences cluster with other African NA1/ON1 genotypes. At antigenic site I, the V384I mutation was replaced by V384T in South African strains. The S275F mutation was seen in a single South African strain. The N120 N-linked glycosylation site was present in 25.8% (8/31) of RSV-A F proteins described in this study. For the first time, we detected the rare S275F mutation that is associated with palivizumab resistance

Exploring the Epidemiological Surveillance of Hepatitis A in South Africa: A 2023 Perspective

Hepatitis A (HAV) presents a significant global health concern with diverse clinical manifestations primarily transmitted through fecal–oral routes, emphasizing the critical role of sanitation and water cleanliness in transmission dynamics. Age-related variations, notably asymptomatic presentation in children, add complexity. The World Health Organization’s (WHO) endemicity classification aids in understanding prevalence and control strategies. This study examines 2023 South African epidemiological data on HAV cases, evaluating age distribution, incidence rates, and provincial disparities. Data from the national surveillance system and weather services were analyzed. Findings reveal distinct age-related trends, with the highest seroprevalence observed in the 5–9 age group with the most burdened areas located in the Western Cape, KwaZulu-Natal, and Gauteng provinces. Furthermore, seasonal rainfall variations correlate with increased incidence in Western Cape and KZN. The amalgamation of results suggest a potential epidemiological shift, emphasizing the need for updated immunization strategies. Noteworthy patterns, like the rise in 5–9-year-olds, may be influenced by factors such as school clustering and migration. Provincial disparities and the impact of climatic events underscore the necessity for dynamic vaccination strategies and surveillance network enhancements. This study highlights the urgency for improved understanding and response to HAV in South Africa