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Insights into SARS-CoV-2 in Angola during the COVID-19 peak: Molecular epidemiology and genome surveillance
Authors:Ngiambudulu M. Francisco  Stephanie van Wyk  Monika Moir  James Emmanuel San  Cruz S. Sebastião  Houriiyah Tegally  Joicymara Xavier  Akhil Maharaj  Zoraima Neto  Pedro Afonso  Domingos Jandondo  Joana Paixão  Julio Miranda  Kumbelembe David  Luzia Inglês  Amilton Pereira  Agostinho Paulo  Raisa Rivas Carralero  Helga Reis Freitas  Franco Mufinda  Silvia Lutucuta  Mahan Ghafari  Marta Giovanetti  Jennifer Giandhari  Sureshnee Pillay  Yeshnee Naidoo  Lavanya Singh  Derek Tshiabuila  Darren Patrick Martin  Lucious Chabuka  Wonderful Choga  Dorcas Wanjohi  Sarah Mwangi  Yusasha Pillay  Yenew Kebede  Edwin Shumba  Pascale Ondoa  Cheryl Baxter  Eduan Wilkinson  Sofonias Kifle Tessema  Aris Katzourakis  Richard Lessells  Tulio de Oliveira  Joana Morais
Affiliation:1. Grupo de Investigação Microbiana e Imunológica, Instituto Nacional de Investigação em Saúde, Luanda, Angola;2. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa;3. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

Contribution: Formal analysis (equal), ​Investigation (equal), Methodology (equal);4. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa

Contribution: Formal analysis (equal), ​Investigation (equal);5. Grupo de Investigação Microbiana e Imunológica, Instituto Nacional de Investigação em Saúde, Luanda, Angola

Centro de Investigação em Saúde de Angola (CISA), Caxito, Angola

Contribution: ​Investigation (equal), Methodology (equal);6. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa

Contribution: Formal analysis (equal), ​Investigation (equal), Methodology (equal);7. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

Contribution: ​Investigation (equal), Methodology (equal), Visualization (equal);8. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

Contribution: ​Investigation (equal), Methodology (equal), Validation (equal);9. Ministério da Saúde, Luanda, Angola

Contribution: ​Investigation (equal), Methodology (equal), Visualization (equal);10. Grupo de Investigação Microbiana e Imunológica, Instituto Nacional de Investigação em Saúde, Luanda, Angola

Contribution: Formal analysis (equal), ​Investigation (equal), Methodology (equal);11. Grupo de Investigação Microbiana e Imunológica, Instituto Nacional de Investigação em Saúde, Luanda, Angola

Contribution: Formal analysis (equal), Funding acquisition (equal), ​Investigation (equal), Methodology (equal);12. Grupo de Investigação Microbiana e Imunológica, Instituto Nacional de Investigação em Saúde, Luanda, Angola

Contribution: Funding acquisition (equal), ​Investigation (equal), Methodology (equal);13. Grupo de Investigação Microbiana e Imunológica, Instituto Nacional de Investigação em Saúde, Luanda, Angola

Contribution: ​Investigation (equal), Methodology (equal), Validation (equal);14. Grupo de Investigação Microbiana e Imunológica, Instituto Nacional de Investigação em Saúde, Luanda, Angola

Contribution: Data curation (equal), ​Investigation (equal), Methodology (equal);15. Grupo de Investigação Microbiana e Imunológica, Instituto Nacional de Investigação em Saúde, Luanda, Angola

Contribution: Data curation (equal), Formal analysis (equal), ​Investigation (equal);16. Direcção Nacional de Saúde Pública, Ministério da Saúde, Luanda, Angola

Contribution: Data curation (equal), ​Investigation (equal), Methodology (equal);17. Ministério da Saúde, Luanda, Angola

Contribution: ​Investigation (equal), Validation (equal), Visualization (equal);18. Ministério da Saúde, Luanda, Angola

Contribution: Formal analysis (equal), Validation (equal), Visualization (equal);19. KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa

Contribution: Formal analysis (equal), ​Investigation (equal), Methodology (equal);20. Reference Laboratory of Flavivirus, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil

Contribution: Conceptualization (equal), Formal analysis (equal), Funding acquisition (equal);21. KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa

Contribution: Data curation (equal), Formal analysis (equal), ​Investigation (equal), Methodology (equal);22. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

Contribution: Data curation (equal), Formal analysis (equal), ​Investigation (equal);23. Division of Computational Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa

Institute of Infectious Disease and Molecular Medicine (IDM), Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa

Contribution: Formal analysis (equal), ​Investigation (equal), Methodology (equal), Software (equal);24. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

Contribution: Formal analysis (equal), Software (equal), Supervision (equal), Validation (equal);25. Africa CDC Institute of Pathogen Genomics, Africa Centre for Disease Control and Prevention, Addis Ababa, Ethiopia

Contribution: ​Investigation (equal), Methodology (equal), Validation (equal);26. Africa CDC Institute of Pathogen Genomics, Africa Centre for Disease Control and Prevention, Addis Ababa, Ethiopia

Contribution: Resources (equal), Software (equal), Supervision (equal), Validation (equal);27. Africa CDC Institute of Pathogen Genomics, Africa Centre for Disease Control and Prevention, Addis Ababa, Ethiopia

Contribution: Resources (equal), Validation (equal), Visualization (equal);28. African Society for Laboratory Medicine, Addis Ababa, Ethiopia

Contribution: Resources (equal), Software (equal), Validation (equal);29. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa

Contribution: Resources (equal), Validation (equal), Visualization (equal);30. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa

Contribution: Formal analysis (equal), ​Investigation (equal), Methodology (equal), Writing - review & editing (equal);31. Africa CDC Institute of Pathogen Genomics, Africa Centre for Disease Control and Prevention, Addis Ababa, Ethiopia

Contribution: Resources (equal), Software (equal), Validation (equal), Visualization (equal);32. Department of Biology, Oxford University, Oxford, UK

Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Contribution: ​Investigation (equal), Methodology (equal), Validation (equal);33. KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa

Contribution: Resources (equal), Software (equal), Validation (equal), Visualization (equal);34. Center for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa

Contribution: Funding acquisition (equal), Project administration (equal);35. Grupo de Investigação Microbiana e Imunológica, Instituto Nacional de Investigação em Saúde, Luanda, Angola

Contribution: Funding acquisition (equal), Project administration (equal)
Abstract:

Background

In Angola, COVID-19 cases have been reported in all provinces, resulting in >105,000 cases and >1900 deaths. However, no detailed genomic surveillance into the introduction and spread of the SARS-CoV-2 virus has been conducted in Angola. We aimed to investigate the emergence and epidemic progression during the peak of the COVID-19 pandemic in Angola.

Methods

We generated 1210 whole-genome SARS-CoV-2 sequences, contributing West African data to the global context, that were phylogenetically compared against global strains. Virus movement events were inferred using ancestral state reconstruction.

Results

The epidemic in Angola was marked by four distinct waves of infection, dominated by 12 virus lineages, including VOCs, VOIs, and the VUM C.16, which was unique to South-Western Africa and circulated for an extended period within the region. Virus exchanges occurred between Angola and its neighboring countries, and strong links with Brazil and Portugal reflected the historical and cultural ties shared between these countries. The first case likely originated from southern Africa.

Conclusion

A lack of a robust genome surveillance network and strong dependence on out-of-country sequencing limit real-time data generation to achieve timely disease outbreak responses, which remains of the utmost importance to mitigate future disease outbreaks in Angola.
Keywords:Angola  COVID-19  genomic surveillance  SARS-CoV-2  variants of concern
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