Molecular Epidemiology and Diversity of SARS-CoV-2 in Ethiopia, 2020-2022 (preprint)

Ethiopia is the second most populous country in Africa and the sixth most affected by COVID-19 on the continent. Despite having experienced five infection waves, >499 000 cases, and ~7 500 COVID-19-related deaths as of January 2023, there is still no detailed genomic epidemiological report on the introduction and spread of SARS-CoV-2 in Ethiopia. In this study, we reconstructed and elucidated the COVID-19 epidemic dynamics. Specifically, we investigated the introduction, local transmission, ongoing evolution, and spread of SARS-CoV-2 during the first four infection waves using 353 high-quality near-whole genomes sampled in Ethiopia. Our results show that whereas viral introductions seeded the first wave, subsequent waves were seeded by local transmission. The B.1.480 lineage emerged in the first wave and notably remained in circulation even after the emergence of the Alpha variant. The B.1.480 was out-competed by the Delta variant. Notably, Ethiopia lack of local sequencing capacity was further limited by sporadic, uneven, and insufficient sampling that limited the incorporation of genomic epidemiology in the epidemic public health response in Ethiopia. These results highlight Ethiopia role in SARS-CoV-2 dissemination and the urgent need for balanced, near-real-time genomic sequencing.

Comparing SARS-CoV-2 sequencing methodologies during early phase detection of the Delta variant in South Africa (preprint)

Background: Genomic surveillance, with the aid of next-generation sequencing (NGS) technologies, revolutionized the SARS-CoV-2 pandemic. Coupled with high-performance analysis software, methodologies such as the Ion Torrent S5 and Illumina MiSeq dramatically improved the genomic surveillance capacity within South Africa during the height of the pandemic. Using de-identified remnant samples collected from Eastern Cape and analysis software, Genome Detective and NextClade, we compared the sequencing process, genomic coverage, quantification of mutations, and clade classification from sequence data generated by these two common “benchtop” NGS platforms. Results: Sequence data analysis revealed success rates of 175/183 (96%) and 172/183 (94%) on the Ion Torrent S5 and Illumina MiSeq, respectively. Internal quality metrics were assessed in terms of genomic coverage (>80%) and the number of mutations identified (<100). A greater number of higher-genomic coverage sequences were generated on the Ion Torrent S5 (99%) than on the Illumina MiSeq (80%) and <100 mutations was obtained by both platforms. Ion Torrent S5 generated high coverage sequences from samples having a broader range of viral loads (VL) compared to the Illumina MiSeq, which was less successful in sequencing samples with lower viral loads. Clade assignments were comparable across platforms which accurately differentiated between Beta (<45%) and Delta (≤30%) VOCs. A disparity in clade assignment was observed in <10% of sequences due to poor coverage obtained on the Illumina MiSeq, followed by a failure rate of ≤6% across the two platforms. Manual library preparation found both methods similar in terms of sample processing, handling of larger sample quantities, and clade assignment for SARS-CoV-2. Variability between the Ion Torrent S5 and Illumina MiSeq was observed in sequencing run duration (3,5 hrs vs 36 hrs), sequencing process (semi-automation vs manual), genomic coverage (99% vs 80%), and viral load requirements (broad range vs high VL). Conclusion: The Illumina MiSeq and Ion Torrent S5 are both reliable platforms capable of performing WGS with the use of amplicons and providing specific, accurate, and high throughput analysis of the SARS-CoV-2 whole viral genomes. Both sequencing platforms are feasible platforms for the genomic surveillance of SARS-CoV-2, each with its specific advantages and trade-offs.

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

Investment in Africa over the past year with regards to SARS-CoV-2 genotyping has led to a massive increase in the number of sequences, exceeding 100,000 genomes generated to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence within their own borders, coupled with a decrease in sequencing turnaround time. Findings from this genomic surveillance underscores the heterogeneous nature of the pandemic but we observe repeated dissemination of SARS-CoV-2 variants within the continent. Sustained investment for genomic surveillance in Africa is needed as the virus continues to evolve, particularly in the low vaccination landscape. These investments are very crucial for preparedness and response for future pathogen outbreaks.

Comparison of SARS-CoV-2 sequencing using the ONT GridION and the Illumina MiSeq (preprint)

Background: Over 4 million SARS-CoV-2 genomes have been sequenced globally in the past 2 years. This has been crucial in elucidating transmission chains within communities, the development of new diagnostic methods, vaccines, and antivirals. Although several sequencing technologies have been employed, Illumina and Oxford Nanopore remain the two most commonly used platforms. The sequence quality between these two platforms warrants a comparison of the genomes produced by the two technologies. Here, we compared the sequence quality produced by the Oxford Nanopore Technology GridION and the Illumina MiSeq for 28 sequencing runs. Results: Our results show that the MiSeq had a significantly higher number of sequences classified by Nextclade as good and mediocre compared to the GridION. The MiSeq also had a significantly higher sequence coverage and mutation counts than the GridION. Conclusion: Due to the low sequence coverage, high number of indels, and sensitivity to viral load noted with the GridION when compared to MiSeq, we can conclude that the MiSeq is more favourable for genomic surveillance, as successful genomic surveillance is dependent on high quality, near-whole genome sequences.

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

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.

Rapid replacement of the Beta variant by the Delta variant in South Africa (preprint)

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.