Investment in SARS-CoV-2 sequencing in Africa over the past year has led to a major increase in the number of sequences generated, now exceeding 100,000 genomes, used to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence domestically, and highlight that local sequencing enables faster turnaround time 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 shed light on 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 re-emerging 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 geographic and evolutionary origins of the SARS-CoV-2 Omicron variant (BA.1), which was first detected mid-November 2021 in Southern Africa, remain unknown. We tested 13,097 COVID-19 patients sampled between mid-2021 to early 2022 from 22 African countries for BA.1 by real-time RT-PCR. By November-December 2021, BA.1 had replaced the Delta variant in all African sub-regions following a South-North gradient, with a peak Rt of 4.1. Polymerase chain reaction and near-full genome sequencing data revealed genetically diverse Omicron ancestors already existed across Africa by August 2021. Mutations, altering viral tropism, replication and immune escape, gradually accumulated in the spike gene. Omicron ancestors were therefore present in several African countries months before Omicron dominated transmission. These data also indicate that travel bans are ineffective in the face of undetected and widespread infection.

Targeted next-generation sequencing (tNGS) from clinical specimens has the potential to become a comprehensive tool for routine drug-resistance (DR) prediction of Mycobacterium tuberculosis complex strains (MTBC), the causative agent of tuberculosis (TB). However, TB mainly affects low- and middle-income countries, in which the implementation of new technologies have specific needs and challenges. We propose a model for programmatic implementation of tNGS in settings with no or low previous sequencing capacity/experience. We highlight the major challenges and considerations for a successful implementation. This model has been applied to build NGS capacity in Namibia, an upper middle-income country located in Southern Africa and suffering from a high-burden of TB and TB-HIV, and we describe herein the outcomes of this process.

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