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1.
Nat Med ; 2022 Jun 27.
Article in English | MEDLINE | ID: covidwho-1908212

ABSTRACT

Three lineages (BA.1, BA.2 and BA.3) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant of concern predominantly drove South Africa's fourth Coronavirus Disease 2019 (COVID-19) wave. We have now identified two new lineages, BA.4 and BA.5, responsible for a fifth wave of infections. The spike proteins of BA.4 and BA.5 are identical, and similar to BA.2 except for the addition of 69-70 deletion (present in the Alpha variant and the BA.1 lineage), L452R (present in the Delta variant), F486V and the wild-type amino acid at Q493. The two lineages differ only outside of the spike region. The 69-70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure, on the background of variants not possessing this feature. BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa by the first week of April 2022. Using a multinomial logistic regression model, we estimated growth advantages for BA.4 and BA.5 of 0.08 (95% confidence interval (CI): 0.08-0.09) and 0.10 (95% CI: 0.09-0.11) per day, respectively, over BA.2 in South Africa. The continued discovery of genetically diverse Omicron lineages points to the hypothesis that a discrete reservoir, such as human chronic infections and/or animal hosts, is potentially contributing to further evolution and dispersal of the virus.

2.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-335264

ABSTRACT

South Africa’s fourth COVID-19 wave was driven predominantly by three lineages (BA.1, BA.2 and BA.3) of the SARS-CoV-2 Omicron variant of concern. We have now identified two new lineages, BA.4 and BA.5. The spike proteins of BA.4 and BA.5 are identical, and comparable to BA.2 except for the addition of 69-70del, L452R, F486V and the wild type amino acid at Q493. The 69-70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure with the TaqPath™ COVID-19 qPCR assay. BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa from the first week of April 2022 onwards. Using a multinomial logistic regression model, we estimate growth advantages for BA.4 and BA.5 of 0.08 (95% CI: 0.07 - 0.09) and 0.12 (95% CI: 0.09 - 0.15) per day respectively over BA.2 in South Africa.

3.
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.

4.
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
5.
Emerg Infect Dis ; 28(5): 1021-1025, 2022 05.
Article in English | MEDLINE | ID: covidwho-1760189

ABSTRACT

Genomic surveillance in Uganda showed rapid replacement of severe acute respiratory syndrome coronavirus 2 over time by variants, dominated by Delta. However, detection of the more transmissible Omicron variant among travelers and increasing community transmission highlight the need for near-real-time genomic surveillance and adherence to infection control measures to prevent future pandemic waves.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Humans , Pandemics , SARS-CoV-2/genetics , Uganda/epidemiology
6.
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.

7.
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.

8.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-294571

ABSTRACT

At the end of 2020, the Network for Genomic Surveillance in South Africa (NGS-SA) detected a SARS-CoV-2 variant of concern (VOC) in South Africa (501Y.V2 or PANGO lineage B.1.351)1. 501Y.V2 is associated with increased transmissibility and resistance to neutralizing antibodies elicited by natural infection and vaccination2,3. 501Y.V2 has since spread to over 50 countries around the world and has contributed to a significant resurgence of the epidemic in southern Africa. In order to rapidly characterize the spread of this and other emerging VOCs and variants of interest (VOIs), NGS-SA partnered with the Africa Centres for Disease Control and Prevention and the African Society of Laboratory Medicine through the Africa Pathogen Genomics Initiative to strengthen SARS-CoV-2 genomic surveillance across the region.

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