Tracing the spatial origins and spread of SARS-CoV-2 Omicron lineages in South Africa

Abstract

Since November 2021, five genetically distinct SARS-CoV-2 Omicron lineages (BA.1–BA.5) are believed to have emerged in southern Africa, with four (BA.1, BA.2, BA.4, and BA.5) spreading globally and collectively dominating SARS-CoV-2 diversity. In 2023, BA.2.86, a highly divergent BA.2 lineage that rose to prominence worldwide, was first detected in Israel and Denmark, but the subsequent diversity of South African sequences suggests it too emerged in the region. Using Bayesian phylogeographic inference, we reconstruct the origins and dispersal patterns of BA.1–BA.5 and BA.2.86. Our findings suggest that Gauteng province in South Africa likely played a key role in the emergence and/or amplification of multiple Omicron lineages, though regions with limited sampling may have also contributed. The challenge of precisely tracing these origins highlights the need for broader genomic surveillance across the region to strengthen early detection, track viral evolution, and improve preparedness for future threats.

Description

DATA AVAILABILITY : All of the SARS-CoV-2 sequences analysed and presented here are publicly accessible through the GISAID platform (https://www.gisaid.org/), using the GISAID identifier: EPI_SET_250304tq (https://doi.org/10.55876/gis8.250304tq). For a summary of the sequences included in the respective analyses please refer to Supplementary Table 1. A detailed breakdown of sequences included in the respective analyses can be found on our Github repository: https://github.com/CERIKRISP/SARS-CoV-2-Omicron-origins-South-Africa. Other publicly available data used in this study are as follows: sequence designation list available on the PANGO GitHub repository (github.com/covlineages/pango-designation/milestones); case count data from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (https://github.com/CSSEGISandData/COVID-19); case data from COVID-19 South Africa (https://www.covid19sa.org/provincial-breakdown); custom python script (https://github.com/CERI-KRISP/SARS_CoV_2_VOC_dissemination) used to derive the number of state changes over the span of the tree; geospatial boundary data from the Humanitarian Data Exchange programme (https://data.humdata.org/) and Natural Earth (https://www.naturalearthdata.com/); and gridded population count datasets from World Pop (https://hub.worldpop.org/).

Keywords

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Southern Africa, Israel, Denmark

Sustainable Development Goals

SDG-03: Good health and well-being

Citation

Dor, G., Wilkinson, E., Martin, D.P. et al. 2025, 'Tracing the spatial origins and spread of SARS-CoV-2 Omicron lineages in South Africa', Nature Communications, vol. 16, no. 1, art. 4937, pp. 1-10. https://doi.org/10.1038/s41467-025-60081-0 .