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1.
Tegally, Houriiyah, San, James, Cotten, Matthew, Tegomoh, Bryan, Mboowa, Gerald, Martin, Darren, Baxter, Cheryl, Moir, Monika, Lambisia, Arnold, Diallo, Amadou, Amoako, Daniel, Diagne, Moussa, Sisay, Abay, Zekri, Abdel-Rahman, Barakat, Abdelhamid, Gueye, Abdou Salam, Sangare, Abdoul, Ouedraogo, Abdoul-Salam, Sow, Abdourahmane, Musa, Abdualmoniem, Sesay, Abdul, Lagare, Adamou, Kemi, Adedotun-Sulaiman, Abar, Aden Elmi, Johnson, Adeniji, Fowotade, Adeola, Olubusuyi, Adewumi, Oluwapelumi, Adeyemi, Amuri, Adrienne, Juru, Agnes, Ramadan, Ahmad Mabrouk, Kandeil, Ahmed, Mostafa, Ahmed, Rebai, Ahmed, Sayed, Ahmed, Kazeem, Akano, Balde, Aladje, Christoffels, Alan, Trotter, Alexander, Campbell, Allan, Keita, Alpha Kabinet, Kone, Amadou, Bouzid, Amal, Souissi, Amal, Agweyu, Ambrose, Gutierrez, Ana, Page, Andrew, Yadouleton, Anges, Vinze, Anika, Happi, Anise, Chouikha, Anissa, Iranzadeh, Arash, Maharaj, Arisha, Batchi-Bouyou, Armel Landry, Ismail, Arshad, Sylverken, Augustina, Goba, Augustine, Femi, Ayoade, Sijuwola, Ayotunde Elijah, Ibrahimi, Azeddine, Marycelin, Baba, Salako, Babatunde Lawal, Oderinde, Bamidele, Bolajoko, Bankole, Dhaala, Beatrice, Herring, Belinda, Tsofa, Benjamin, Mvula, Bernard, Njanpop-Lafourcade, Berthe-Marie, Marondera, Blessing, Khaireh, Bouh Abdi, Kouriba, Bourema, Adu, Bright, Pool, Brigitte, McInnis, Bronwyn, Brook, Cara, Williamson, Carolyn, Anscombe, Catherine, Pratt, Catherine, Scheepers, Cathrine, Akoua-Koffi, Chantal, Agoti, Charles, Loucoubar, Cheikh, Onwuamah, Chika Kingsley, Ihekweazu, Chikwe, Malaka, Christian Noël, Peyrefitte, Christophe, Omoruyi, Chukwuma Ewean, Rafaï, Clotaire Donatien, Morang’a, Collins, Nokes, James, Lule, Daniel Bugembe, Bridges, Daniel, Mukadi-Bamuleka, Daniel, Park, Danny, Baker, David, Doolabh, Deelan, Ssemwanga, Deogratius, Tshiabuila, Derek, Bassirou, Diarra, Amuzu, Dominic S. Y.; Goedhals, Dominique, Grant, Donald, Omuoyo, Donwilliams, Maruapula, Dorcas, Wanjohi, Dorcas Waruguru, Foster-Nyarko, Ebenezer, Lusamaki, Eddy, Simulundu, Edgar, Ong’era, Edidah, Ngabana, Edith, Abworo, Edward, Otieno, Edward, Shumba, Edwin, Barasa, Edwine, Ahmed, El Bara, Kampira, Elizabeth, Fahime, Elmostafa El, Lokilo, Emmanuel, Mukantwari, Enatha, Cyril, Erameh, Philomena, Eromon, Belarbi, Essia, Simon-Loriere, Etienne, Anoh, Etilé, Leendertz, Fabian, Taweh, Fahn, Wasfi, Fares, Abdelmoula, Fatma, Takawira, Faustinos, Derrar, Fawzi, Ajogbasile, Fehintola, Treurnicht, Florette, Onikepe, Folarin, Ntoumi, Francine, Muyembe, Francisca, Ngiambudulu, Francisco, Zongo Ragomzingba, Frank Edgard, Dratibi, Fred Athanasius, Iyanu, Fred-Akintunwa, Mbunsu, Gabriel, Thilliez, Gaetan, Kay, Gemma, Akpede, George, George, Uwem, van Zyl, Gert, Awandare, Gordon, Schubert, Grit, Maphalala, Gugu, Ranaivoson, Hafaliana, Lemriss, Hajar, Omunakwe, Hannah, Onywera, Harris, Abe, Haruka, Karray, Hela, Nansumba, Hellen, Triki, Henda, Adje Kadjo, Herve Albéric, Elgahzaly, Hesham, Gumbo, Hlanai, mathieu, Hota, Kavunga-Membo, Hugo, Smeti, Ibtihel, Olawoye, Idowu, Adetifa, Ifedayo, Odia, Ikponmwosa, Boubaker, Ilhem Boutiba-Ben, Ssewanyana, Isaac, Wurie, Isatta, Konstantinus, Iyaloo, Afiwa Halatoko, Jacqueline Wemboo, Ayei, James, Sonoo, Janaki, Lekana-Douki, Jean Bernard, Makangara, Jean-Claude, Tamfum, Jean-Jacques, Heraud, Jean-Michel, Shaffer, Jeffrey, Giandhari, Jennifer, Musyoki, Jennifer, Uwanibe, Jessica, Bhiman, Jinal, Yasuda, Jiro, Morais, Joana, Mends, Joana, Kiconco, Jocelyn, Sandi, John Demby, Huddleston, John, Odoom, John Kofi, Morobe, John, Gyapong, John, Kayiwa, John, Okolie, Johnson, Xavier, Joicymara Santos, Gyamfi, Jones, Kofi Bonney, Joseph Humphrey, Nyandwi, Joseph, Everatt, Josie, Farah, Jouali, Nakaseegu, Joweria, Ngoi, Joyce, Namulondo, Joyce, Oguzie, Judith, Andeko, Julia, Lutwama, Julius, O’Grady, Justin, Siddle, Katherine, Victoir, Kathleen, Adeyemi, Kayode, Tumedi, Kefentse, Carvalho, Kevin Sanders, Mohammed, Khadija Said, Musonda, Kunda, Duedu, Kwabena, Belyamani, Lahcen, Fki-Berrajah, Lamia, Singh, Lavanya, Biscornet, Leon, Le.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-334191

ABSTRACT

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. One-Sentence Summary Expanding Africa SARS-CoV-2 sequencing capacity in a fast evolving pandemic.

2.
BMC Genomics ; 23(1): 319, 2022 Apr 22.
Article in English | MEDLINE | ID: covidwho-1799119

ABSTRACT

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 SARS-CoV-2 consensus genomes obtained from 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 consensus genomes classified by Nextclade as good and mediocre compared to the GridION. The MiSeq also had a significantly higher genome coverage and mutation counts than the GridION. CONCLUSION: Due to the low genome coverage, high number of indels, and sensitivity to SARS-CoV-2 viral load noted with the GridION when compared to MiSeq, we can conclude that the MiSeq is more favourable for SARS-CoV-2 genomic surveillance, as successful genomic surveillance is dependent on high quality, near-whole consensus genomes.


Subject(s)
COVID-19 , SARS-CoV-2 , Genome, Viral , High-Throughput Nucleotide Sequencing/methods , Humans , SARS-CoV-2/genetics , Whole Genome Sequencing/methods
3.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-328633

ABSTRACT

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.

4.
Nature ; 603(7902): 679-686, 2022 03.
Article in English | MEDLINE | ID: covidwho-1638766

ABSTRACT

The SARS-CoV-2 epidemic in southern Africa has been characterized by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, while the second and third waves were driven by the Beta (B.1.351) and Delta (B.1.617.2) 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, B.1.1.529) 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, which are 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.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , Immune Evasion , SARS-CoV-2/isolation & purification , Antibodies, Neutralizing/immunology , Botswana/epidemiology , COVID-19/immunology , COVID-19/transmission , Humans , Models, Molecular , Mutation , Phylogeny , Recombination, Genetic , SARS-CoV-2/classification , SARS-CoV-2/immunology , South Africa/epidemiology , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/immunology
5.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-296139

ABSTRACT

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.

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