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1.
Houriiyah Tegally; James E. San; Matthew Cotten; Bryan Tegomoh; Gerald Mboowa; Darren P. Martin; Cheryl Baxter; Monika Moir; Arnold Lambisia; Amadou Diallo; Daniel G. Amoako; Moussa M. Diagne; Abay Sisay; Abdel-Rahman N. Zekri; Abdelhamid Barakat; Abdou Salam Gueye; Abdoul K. Sangare; Abdoul-Salam Ouedraogo; Abdourahmane SOW; Abdualmoniem O. Musa; Abdul K. Sesay; Adamou LAGARE; Adedotun-Sulaiman Kemi; Aden Elmi Abar; Adeniji A. Johnson; Adeola Fowotade; Adewumi M. Olubusuyi; Adeyemi O. Oluwapelumi; Adrienne A. Amuri; Agnes Juru; Ahmad Mabrouk Ramadan; Ahmed Kandeil; Ahmed Mostafa; Ahmed Rebai; Ahmed Sayed; Akano Kazeem; Aladje Balde; Alan Christoffels; Alexander J. Trotter; Allan Campbell; Alpha Kabinet KEITA; Amadou Kone; Amal Bouzid; Amal Souissi; Ambrose Agweyu; Ana V. Gutierrez; Andrew J. Page; Anges Yadouleton; Anika Vinze; Anise N. Happi; Anissa Chouikha; Arash Iranzadeh; Arisha Maharaj; Armel Landry Batchi-Bouyou; Arshad Ismail; Augustina Sylverken; Augustine Goba; Ayoade Femi; Ayotunde Elijah Sijuwola; Azeddine Ibrahimi; Baba Marycelin; Babatunde Lawal Salako; Bamidele S. Oderinde; Bankole Bolajoko; Beatrice Dhaala; Belinda L. Herring; Benjamin Tsofa; Bernard Mvula; Berthe-Marie Njanpop-Lafourcade; Blessing T. Marondera; Bouh Abdi KHAIREH; Bourema Kouriba; Bright Adu; Brigitte Pool; Bronwyn McInnis; Cara Brook; Carolyn Williamson; Catherine Anscombe; Catherine B. Pratt; Cathrine Scheepers; Chantal G. Akoua-Koffi; Charles N. Agoti; Cheikh Loucoubar; Chika Kingsley Onwuamah; Chikwe Ihekweazu; Christian Noel MALAKA; Christophe Peyrefitte; Chukwuma Ewean Omoruyi; Clotaire Donatien Rafai; Collins M. Morang'a; D. James Nokes; Daniel Bugembe Lule; Daniel J. Bridges; Daniel Mukadi-Bamuleka; Danny Park; David Baker; Deelan Doolabh; Deogratius Ssemwanga; Derek Tshiabuila; Diarra Bassirou; Dominic S.Y. Amuzu; Dominique Goedhals; Donald S. Grant; Donwilliams O. Omuoyo; Dorcas Maruapula; Dorcas Waruguru Wanjohi; Ebenezer Foster-Nyarko; Eddy K. Lusamaki; Edgar Simulundu; Edidah M. Ong'era; Edith N. Ngabana; Edward O. Abworo; Edward Otieno; Edwin Shumba; Edwine Barasa; EL BARA AHMED; Elmostafa EL FAHIME; Emmanuel Lokilo; Enatha Mukantwari; Erameh Cyril; Eromon Philomena; Essia Belarbi; Etienne Simon-Loriere; Etile A. Anoh; Fabian Leendertz; Fahn M. Taweh; Fares Wasfi; Fatma Abdelmoula; Faustinos T. Takawira; Fawzi Derrar; Fehintola V Ajogbasile; Florette Treurnicht; Folarin Onikepe; Francine Ntoumi; Francisca M. Muyembe; FRANCISCO NGIAMBUDULU; Frank Edgard ZONGO Ragomzingba; Fred Athanasius DRATIBI; Fred-Akintunwa Iyanu; Gabriel K. Mbunsu; Gaetan Thilliez; Gemma L. Kay; George O. Akpede; George E Uwem; Gert van Zyl; Gordon A. Awandare; Grit Schubert; Gugu P. Maphalala; Hafaliana C. Ranaivoson; Hajar Lemriss; Hannah E Omunakwe; Harris Onywera; Haruka Abe; HELA KARRAY; Hellen Nansumba; Henda Triki; Herve Alberic ADJE KADJO; Hesham Elgahzaly; Hlanai Gumbo; HOTA mathieu; Hugo Kavunga-Membo; Ibtihel Smeti; Idowu B. Olawoye; Ifedayo Adetifa; Ikponmwosa Odia; Ilhem Boutiba-Ben Boubaker; Isaac Ssewanyana; Isatta Wurie; Iyaloo S Konstantinus; Jacqueline Wemboo Afiwa Halatoko; James Ayei; Janaki Sonoo; Jean Bernard LEKANA-DOUKI; Jean-Claude C. Makangara; Jean-Jacques M. Tamfum; Jean-Michel Heraud; Jeffrey G. Shaffer; Jennifer Giandhari; Jennifer Musyoki; Jessica N. Uwanibe; Jinal N. Bhiman; Jiro Yasuda; Joana Morais; Joana Q. Mends; Jocelyn Kiconco; John Demby Sandi; John Huddleston; John Kofi Odoom; John M. Morobe; John O. Gyapong; John T. Kayiwa; Johnson C. Okolie; Joicymara Santos Xavier; Jones Gyamfi; Joseph Humphrey Kofi Bonney; Joseph Nyandwi; Josie Everatt; Jouali Farah; Joweria Nakaseegu; Joyce M. Ngoi; Joyce Namulondo; Judith U. Oguzie; Julia C. Andeko; Julius J. Lutwama; Justin O'Grady; Katherine J Siddle; Kathleen Victoir; Kayode T. Adeyemi; Kefentse A. Tumedi; Kevin Sanders Carvalho; Khadija Said Mohammed; Kunda G. Musonda; Kwabena O. Duedu; Lahcen Belyamani; Lamia Fki-Berrajah; Lavanya Singh; Leon Biscornet; Leonardo de Oliveira Martins; Lucious Chabuka; Luicer Olubayo; Lul Lojok Deng; Lynette Isabella Ochola-Oyier; Madisa Mine; Magalutcheemee Ramuth; Maha Mastouri; Mahmoud ElHefnawi; Maimouna Mbanne; Maitshwarelo I. Matsheka; Malebogo Kebabonye; Mamadou Diop; Mambu Momoh; Maria da Luz Lima Mendonca; Marietjie Venter; Marietou F Paye; Martin Faye; Martin M. Nyaga; Mathabo Mareka; Matoke-Muhia Damaris; Maureen W. Mburu; Maximillian Mpina; Claujens Chastel MFOUTOU MAPANGUY; Michael Owusu; Michael R. Wiley; Mirabeau Youtchou Tatfeng; Mitoha Ondo'o Ayekaba; Mohamed Abouelhoda; Mohamed Amine Beloufa; Mohamed G Seadawy; Mohamed K. Khalifa; Mohammed Koussai DELLAGI; Mooko Marethabile Matobo; Mouhamed Kane; Mouna Ouadghiri; Mounerou Salou; Mphaphi B. Mbulawa; Mudashiru Femi Saibu; Mulenga Mwenda; My V.T. Phan; Nabil Abid; Nadia Touil; Nadine Rujeni; Nalia Ismael; Ndeye Marieme Top; Ndongo Dia; Nedio Mabunda; Nei-yuan Hsiao; Nelson Borico Silochi; Ngonda Saasa; Nicholas Bbosa; Nickson Murunga; Nicksy Gumede; Nicole Wolter; Nikita Sitharam; Nnaemeka Ndodo; Nnennaya A. Ajayi; Noel Tordo; Nokuzola Mbhele; Norosoa H Razanajatovo; Nosamiefan Iguosadolo; Nwando Mba; Ojide C. Kingsley; Okogbenin Sylvanus; Okokhere Peter; Oladiji Femi; Olumade Testimony; Olusola Akinola Ogunsanya; Oluwatosin Fakayode; Onwe E. Ogah; Ousmane Faye; Pamela Smith-Lawrence; Pascale Ondoa; Patrice Combe; Patricia Nabisubi; Patrick Semanda; Paul E. Oluniyi; Paulo Arnaldo; Peter Kojo Quashie; Philip Bejon; Philippe Dussart; Phillip A. Bester; Placide K. Mbala; Pontiano Kaleebu; Priscilla Abechi; Rabeh El-Shesheny; Rageema Joseph; Ramy Karam Aziz; Rene Ghislain Essomba; Reuben Ayivor-Djanie; Richard Njouom; Richard O. Phillips; Richmond Gorman; Robert A. Kingsley; Rosemary Audu; Rosina A.A. Carr; Saad El Kabbaj; Saba Gargouri; Saber Masmoudi; Safietou Sankhe; Sahra Isse Mohamed; Salma MHALLA; Salome Hosch; Samar Kamal Kassim; Samar Metha; Sameh Trabelsi; Sanaa Lemriss; Sara Hassan Agwa; Sarah Wambui Mwangi; Seydou Doumbia; Sheila Makiala-Mandanda; Sherihane Aryeetey; Shymaa S. Ahmed; SIDI MOHAMED AHMED; Siham Elhamoumi; Sikhulile Moyo; Silvia Lutucuta; Simani Gaseitsiwe; Simbirie Jalloh; Soafy Andriamandimby; Sobajo Oguntope; Solene Grayo; Sonia Lekana-Douki; Sophie Prosolek; Soumeya Ouangraoua; Stephanie van Wyk; Stephen F. Schaffner; Stephen Kanyerezi; Steve AHUKA-MUNDEKE; Steven Rudder; Sureshnee Pillay; Susan Nabadda; Sylvie Behillil; Sylvie L. Budiaki; Sylvie van der Werf; Tapfumanei Mashe; Tarik Aanniz; Thabo Mohale; Thanh Le-Viet; Thirumalaisamy P. Velavan; Tobias Schindler; Tongai Maponga; Trevor Bedford; Ugochukwu J. Anyaneji; Ugwu Chinedu; Upasana Ramphal; Vincent Enouf; Vishvanath Nene; Vivianne Gorova; Wael H. Roshdy; Wasim Abdul Karim; William K. Ampofo; Wolfgang Preiser; Wonderful T. Choga; Yahaya ALI ALI AHMED; Yajna Ramphal; Yaw Bediako; Yeshnee Naidoo; Yvan Butera; Zaydah R. de Laurent; Ahmed E.O. Ouma; Anne von Gottberg; George Githinji; Matshidiso Moeti; Oyewale Tomori; Pardis C. Sabeti; Amadou A. Sall; Samuel O. Oyola; Yenew K. Tebeje; Sofonias K. Tessema; Tulio de Oliveira; Christian Happi; Richard Lessells; John Nkengasong; Eduan Wilkinson.
medrxiv; 2022.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2022.04.17.22273906

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.

2.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.08.12.21261987

ABSTRACT

BackgroundCommunity surveys of SARS-CoV-2 RT-PCR swab-positivity provide prevalence estimates largely unaffected by biases from who presents for routine case testing. The REal-time Assessment of Community Transmission-1 (REACT-1) has estimated swab-positivity approximately monthly since May 2020 in England from RT-PCR testing of self-administered throat and nose swabs in random non-overlapping cross-sectional community samples. Estimating infection incidence from swab-positivity requires an understanding of the persistence of RT-PCR swab positivity in the community. MethodsDuring round 8 of REACT-1 from 6 January to 22 January 2021, of the 2,282 participants who tested RT-PCR positive, we recruited 896 (39%) from whom we collected up to two additional swabs for RT-PCR approximately 6 and 9 days after the initial swab. We estimated sensitivity and duration of positivity using an exponential model of positivity decay, for all participants and for subsets by initial N-gene cycle threshold (Ct) value, symptom status, lineage and age. Estimates of infection incidence were obtained for the entire duration of the REACT-1 study using P-splines. ResultsWe estimated the overall sensitivity of REACT-1 to detect virus on a single swab as 0.79 (0.77, 0.81) and median duration of positivity following a positive test as 9.7 (8.9, 10.6) days. We found greater median duration of positivity where there was a low N-gene Ct value, in those exhibiting symptoms, or for infection with the Alpha variant. The estimated proportion of positive individuals detected on first swab, P0, was found to be higher for those with an initially low N-gene Ct value and those who were pre-symptomatic. When compared to swab-positivity, estimates of infection incidence over the duration of REACT-1 included sharper features with evident transient increases around the time of key changes in social distancing measures. DiscussionHome self-swabbing for RT-PCR based on a single swab, as implemented in REACT-1, has high overall sensitivity. However, participants time-since-infection, symptom status and viral lineage affect the probability of detection and the duration of positivity. These results validate previous efforts to estimate incidence of SARS-CoV-2 from swab-positivity data, and provide a reliable means to obtain community infection estimates to inform policy response.

3.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.08.10.21261847

ABSTRACT

Background The COVID-19 pandemic continues to expand globally, with case numbers rising in many areas of the world, including the Eastern Mediterranean Region. Lebanon experienced its largest wave of COVID-19 infections from January to April 2021. Limited genomic surveillance was undertaken, with just twenty six SARS-CoV-2 genomes available for this period, nine of which were from travellers from Lebanon detected by other countries. Additional genome sequencing is thus needed to allow surveillance of variants in circulation. Methods Nine hundred and five SARS-CoV-2 genomes were sequenced using the ARTIC protocol. The genomes were derived from SARS-CoV-2-positive samples, selected retrospectively from the sentinel COVID-19 surveillance network, to capture diversity of location, sampling time, gender, nationality and age. Results Although sixteen PANGO lineages were circulating in Lebanon in January 2021, by February there were just four, with the Alpha variant accounting for 97% of samples. In the following two months, all samples contained the Alpha variant. However, this had changed dramatically by June and July, when all samples belonged to the Delta variant. Discussion This study provides a ten-fold increase in the number of SARS-CoV-2 genomes available from Lebanon. The Alpha variant, first detected in the UK, rapidly swept through Lebanon, causing the country’s largest wave to date, which peaked in January 2021. The Alpha variant was introduced to Lebanon multiple times despite travel restrictions, but the source of these introductions remains uncertain. The Delta variant was detected in Gambia in travellers from Lebanon in mid-May, suggesting community transmission in Lebanon several weeks before this variant was detected in the country. Prospective sequencing in June/July 2021 showed that the Delta variant had completely replaced the Alpha variant in under six weeks.


Subject(s)
COVID-19
4.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.06.04.21258352

ABSTRACT

BackgroundThe SARS-CoV-2 pandemic continues to expand globally, with case numbers rising in many areas of the world, including the Indian sub-continent. Pakistan has one of the world s largest population, of over 200 million people and is experiencing a severe third wave of infections caused by SARS-CoV-2 that begun in March 2021.In Pakistan, during third wave until now only 12 SARS-CoV-2 genomes have been collected and among these 9 are from Islamabad. This highlights the need for more genome sequencing to allow surveillance of variants in circulation. In fact more genomes are available among travellers with a travel history from Pakistan, than from within the country itself. MethodsFor a better understanding of the circulating variants in Lahore and surrounding areas with a combined population of 11.1 million, within a week of April 2021, 102 samples were sequenced. The samples were randomly collected from 2 hospitals with a diagnostic polymerase chain reaction (PCR) cutoff value of less than 25 cycles. ResultsAnalysis of the lineages shows that B.1.1.7 (first identified in the UK, Alpha variant) dominates, accounting for 97.9% (97/99) of cases, with B.1.351 (first identified in South Africa, Beta variant) accounting for 2.0% (2/99) of cases. No other lineages were observed. DiscussionIn depth analysis of the B.1.1.7 lineages indicates multiple separate introductions and subsequent establishment within the region. Eight samples were identical to genomes observed in Europe (7 UK, 1 Switzerland), indicating recent transmission. Genomes of other samples show evidence that these have evolved, indicating sustained transmission over a period of time either within Pakistan or other countries with low density genome sequencing. Vaccines remain effective against B.1.1.7, however the low level of B.1.351 against which some vaccines are less effective demonstrates the requirement for continued prospective genomic surveillance.

5.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.05.13.21257144

ABSTRACT

BackgroundNational epidemic dynamics of SARS-CoV-2 infections are being driven by: the degree of recent indoor mixing (both social and workplace), vaccine coverage, intrinsic properties of the circulating lineages, and prior history of infection (via natural immunity). In England, infections, hospitalisations and deaths fell during the first two steps of the "roadmap" for exiting the third national lockdown. The third step of the roadmap in England takes place on 17 May 2021. MethodsWe report the most recent findings on community infections from the REal-time Assessment of Community Transmission-1 (REACT-1) study in which a swab is obtained from a representative cross-sectional sample of the population in England and tested using PCR. Round 11 of REACT-1 commenced self-administered swab-collection on 15 April 2021 and completed collections on 3 May 2021. We compare the results of REACT-1 round 11 to round 10, in which swabs were collected from 11 to 30 March 2021. ResultsBetween rounds 10 and 11, prevalence of swab-positivity dropped by 50% in England from 0.20% (0.17%, 0.23%) to 0.10% (0.08%, 0.13%), with a corresponding R estimate of 0.90 (0.87, 0.94). Rates of swab-positivity fell in the 55 to 64 year old group from 0.17% (0.12%, 0.25%) in round 10 to 0.06% (0.04%, 0.11%) in round 11. Prevalence in round 11 was higher in the 25 to 34 year old group at 0.21% (0.12%, 0.38%) than in the 55 to 64 year olds and also higher in participants of Asian ethnicity at 0.31% (0.16%, 0.60%) compared with white participants at 0.09% (0.07%, 0.11%). Based on sequence data for positive samples for which a lineage could be identified, we estimate that 92.3% (75.9%, 97.9%, n=24) of infections were from the B.1.1.7 lineage compared to 7.7% (2.1%, 24.1%, n=2) from the B.1.617.2 lineage. Both samples from the B.1.617.2 lineage were detected in London from participants not reporting travel in the previous two weeks. Also, allowing for suitable lag periods, the prior close alignment between prevalence of infections and hospitalisations and deaths nationally has diverged. DiscussionWe observed marked reductions in prevalence from March to April and early May 2021 in England reflecting the success of the vaccination programme and despite easing of restrictions during lockdown. However, there is potential upwards pressure on prevalence from the further easing of lockdown regulations and presence of the B.1.617.2 lineage. If prevalence rises in the coming weeks, policy-makers will need to assess the possible impact on hospitalisations and deaths. In addition, consideration should be given to other health and economic impacts if increased levels of community transmission occur.


Subject(s)
COVID-19
6.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.05.08.21256867

ABSTRACT

Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained from a variety of sources. Here, we describe lineage dynamics and phylogenetic relationships using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR during the first three months of 2021 as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the B.1.1.7 lineage (first identified in Kent) predominant, driven by a 0.3 unit higher reproduction number over the prior wild type. During January, positive samples were more likely B.1.1.7 in younger and middle-aged adults (aged 18 to 54) than in other age groups. Although individuals infected with the B.1.1.7 lineage were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild type, they were more likely to be antibody positive 6 weeks after infection. Viral load was higher in B.1.1.7 infection as measured by cycle threshold (Ct) values, but did not account for the increased rate of testing positive for antibodies. The presence of infections with non-imported B.1.351 lineage (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing and targeted public health interventions and does not immediately imply similar lineages could not become established in the future. Sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance.


Subject(s)
COVID-19
7.
Eduan Wilkinson; Marta Giovanetti; Houriiyah Tegally; James E San; Richard Lessels; Diego Cuadros; Darren P Martin; Abdel-Rahman N Zekri; Abdoul Sangare; Abdoul Salam Ouedraogo; Abdul K Sesay; Adnene Hammami; Adrienne A Amuri; Ahmad Sayed; Ahmed Rebai; Aida Elargoubi; Alpha K Keita; Amadou A Sall; Amadou Kone; Amal Souissi; Ana V Gutierrez; Andrew Page; Arnold Lambisia; Arash Iranzadeh; Augustina Sylverken; Azeddine Ibrahimi; Bourema Kouriba; Bronwyn Kleinhans; Beatrice Dhaala; Cara Brook; Carolyn Williamson; Catherine B Pratt; Chantal G Akoua-Koffi; Charles Agoti; Collins M Moranga; James D Nokes; Daniel J Bridges; Daniel L Bugembe; Deelan Doolabh; Deogratius Ssemwanga; Derek Tshabuila; Diarra Bassirou; Dominic S.Y. Amuzu; Dominique Goedhals; Dorcas Maruapula; Edith N Ngabana; Eddy Lusamaki; Edidah Moraa; Elmostafa El Fahime; Emerald Jacob; Emmanuel Lokilo; Enatha Mukantwari; Essia Belarbi; Etienne Simon-Loriere; Etile A Anoh; Fabian Leendertz; Faida Ajili; Fares Wasfi; Faustinos T Takawira; Fawzi Derrar; Feriel Bouzid; Francisca M Muyembe; Frank Tanser; Gabriel Mbunsu; Gaetan Thilliez; Gert van Zyl; Grit Schubert; George Githinji; Gordon A Awandare; Haruka Abe; Hela H Karray; Hellen Nansumba; Hesham A Elgahzaly; Hlanai Gumbo; Ibtihel Smeti; Ikhlass B Ayed; Imed Gaaloul; Ilhem B.B. Boubaker; Inbal Gazy; Isaac Ssewanyana; Jean B Lekana-Douk; Jean-Claude C Makangara; Jean-Jacques M Tamfum; Jean M Heraud; Jeffrey G Shaffer; Jennifer Giandhari; Jingjing Li; Jiro Yasuda; Joana Q Mends; Jocelyn Kiconco; Jonathan A Edwards; John Morobe; John N Nkengasong; John Gyapong; John T Kayiwa; Jones Gyamfi; Jouali Farah; Joyce M Ngoi; Joyce Namulondo; Julia C Andeko; Julius J Lutwama; Justin O Grady; Kefenstse A Tumedi; Khadija Said; Kim Hae-Young; Kwabena O Duedu; Lahcen Belyamani; Lavanya Singh; Leonardo de O. Martins; Madisa Mine; Mahmoud el Hefnawi; Mahjoub Aouni; Maha Mastouri; Maitshwarelo I Matsheka; Malebogo Kebabonye; Manel Turki; Martin Nyaga; Matoke Damaris; Matthew Cotten; Maureen W Mburu; Maximillian Mpina; Michael R Wiley; Mohamed A Ali; Mohamed K Khalifa; Mohamed G Seadawy; Mouna Ouadghiri; Mulenga Mwenda; Mushal Allam; My V.T. Phan; Nabil Abid; Nadia Touil; Najla Kharrat; Nalia Ismael; Nedio Mabunda; Nei-yuan Hsiao; Nelson Silochi; Ngonda Saasa; Nicola Mulder; Patrice Combe; Patrick Semanda; Paul E Oluniyi; Paulo Arnaldo; Peter K Quashie; Reuben Ayivor-Djanie; Philip A Bester; Philippe Dussart; Placide K Mbala; Pontiano Kaleebu; Richard Njouom; Richmond Gorman; Robert A Kingsley; Rosina A.A. Carr; Saba Gargouri; Saber Masmoudi; Samar Kassim; Sameh Trabelsi; Sami Kammoun; Sanaa Lemriss; Sara H Agwa; Sebastien Calvignac-Spencer; Seydou Doumbia; Sheila M Madinda; Sherihane Aryeetey; Shymaa S Ahmed; Sikhulile Moyo; Simani Gaseitsiwe; Edgar Simulundu; Sonia Lekana-Douki; Soumeya Ouangraoua; Steve A Mundeke; Sumir Panji; Sureshnee Pillay; Susan Engelbrecht; Susan Nabadda; Sylvie Behillil; Sylvie van der Werf; Tarik Aanniz; Tapfumanei Mashe; Thabo Mohale; Thanh Le-Viet; Tobias Schindler; Upasana Ramphal; Magalutcheemee Ramuth; Vagner Fonseca; Vincent Enouf; Wael H Roshdy; William Ampofo; Wolfgang Preiser; Wonderful T Choga; Yaw Bediako; Yenew K. Tebeje; Yeshnee Naidoo; Zaydah de Laurent; Sofonias K Tessema; Tulio de Oliveira.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.05.12.21257080

ABSTRACT

The progression of the SARS-CoV-2 pandemic in Africa has so far been heterogeneous and the full impact is not yet well understood. Here, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations, predominantly from Europe, which diminished following the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1 and C.1.1. Although distorted by low sampling numbers and blind-spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a breeding ground for new variants.

8.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.03.15.21253590

ABSTRACT

BackgroundMitigation of SARS-CoV-2 transmission from international travel is a priority. Travellers from countries with travel restrictions (closed travel-corridors) were required to quarantine for 14 days over Summer 2020 in England. We describe the genomic epidemiology of travel-related cases in England and evaluate the effectiveness of this travel policy. MethodsBetween 27/05/2020 and 13/09/2020, probable travel-related SARS-CoV-2 cases and their contacts were identified and combined with UK SARS-CoV-2 sequencing data. The epidemiology and demographics of cases was identified, and the number of contacts per case modelled using negative binomial regression to estimate the effect of travel restriction, and any variation by age, sex and calendar date. Unique travel-related SARS-CoV-2 genomes in the COG-UK dataset were identified to estimate the effect travel restrictions on cluster size generated from these. The Polecat Clustering Tool was used to identify a travel-related SARS-CoV-2 cluster of infection. Findings4,207 travel-related SARS-CoV-2 cases are identified. 51.2% (2155/4207) of cases reported travel to one of three countries; 21.0% (882) Greece, 16.3% (685) Croatia and 14.0% (589) Spain. Median number of contacts per case was 3 (IQR 1-5), and greatest for the 16-20 age-group (9.0, 95% C.I.=5.6-14.5), which saw the largest attenuation by travel restriction. Travel restriction was associated with a 40% (rate ratio=0.60, 95% C.I.=0.37-0.95) lower rate of contacts. 827/4207 (19.7%) of cases had high-quality SARS-CoV-2 genomes available. Fewer genomically-linked cases were observed for index cases related to countries with travel restrictions compared to cases from non-travel restriction countries (rate ratio=0.17, 95% C.I.=0.05-0.52). A large travel-related cluster dispersed across England is identified through genomics, confirmed with contact-tracing data. InterpretationThis study demonstrates the efficacy of travel restriction policy in reducing the onward transmission of imported cases. FundingWellcome Trust, Biotechnology and Biological Sciences Research Council, UK Research & Innovation, National Institute of Health Research, Wellcome Sanger Institute. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, medRxiv, bioRxiv, Web of Science and Scopus for the terms (COVID-19 OR SARS-COV-2) AND (imported or importation) AND (sequenc* OR genom* or WGS). We filtered the 55 articles identified through this search and rejected any that did not undertake SARS-CoV-2 sequencing as part of an epidemiological investigation for importation into a different country. The remaining 20 papers were reviewed in greater detail to understand the patterns of importation and the methods used in each case. Added value of this studyThis is the first published study on importations of SARS-CoV-2 into England using genomics. Plessis et al., (2021) used a predictive model to infer the number of importations in to the UK from all SARS-CoV-2 genomes generated before 26th June 2020. The current study assesses the period 27/05/2020 to 13/09/2020 and presents findings of case-reported travel linked to genomic data. Two unpublished reports exist for Wales and Scotland, although only examine a comparatively small number of importations. Implications of all the available evidenceThis large-scale study has a number of findings that are pertinent to public health and of global significance, not available from prior evidence to our knowledge. The study demonstrates travel restrictions, through the implementation of travel-corridors, are effective in reducing the number of contacts per case based on observational data. Age has a significant effect on the number of contacts and this can be mitigated with travel restrictions. Analysis of divergent clusters indicates travel restrictions can reduce the number of onwards cases following a travel-associated case. Analysis of divergent clusters can allow for importations to be identified from genomics, as subsequently evidenced by cluster characteristics derived from contact tracing. The majority of importations of SARS-CoV-2 in England over Summer 2020 were from coastal European countries. The highest number of cases and onward contacts were from Greece, which was largely exempt from self-isolation requirements (bar some islands in September at the end of the study period). Systematic monitoring of imported SARS-CoV-2 cases would help refine implementation of travel restrictions. Finally, along with multiple studies, this study highlights the use of genomics to monitor and track importations of SARS-CoV-2 mutations of interest; this will be of particular use as the repertoire of clinically relevant SARS-CoV-2 variants expand over time and globally.


Subject(s)
COVID-19
9.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.01.04.20232520

ABSTRACT

Zimbabwe reported its first case of SARS-Cov-2 infection in March 2020, and case numbers increased to more than 8,099 to 16th October 2020. An understanding of the SARS-Cov-2 outbreak in Zimbabwe will assist in the implementation of effective public health interventions to control transmission. Nasopharyngeal samples from 92,299 suspected and confirmed COVID-19 cases reported in Zimbabwe between 20 March and 16 October 2020 were obtained. Available demographic data associated with those cases identified as positive (8,099) were analysed to describe the national breakdown of positive cases over time in more detail (geographical location, sex, age and travel history). The whole genome sequence (WGS) of one hundred SARS-CoV-2-positive samples from the first 120 days of the epidemic in Zimbabwe was determined to identify their relationship to one another and WGS from global samples. Overall, a greater proportion of infections were in males (55.5%) than females (44.85%), although in older age groups more females were affected than males. Most COVID-19 cases (57 %) were in the 20-40 age group. Eight lineages, from at least 25 separate introductions into the region were found using comparative genomics. Of these, 95% had the D614G mutation on the spike protein which was associated with higher transmissibility than the ancestral strain. Early introductions and spread of SARS-CoV-2 were predominantly associated with genomes common in Europe and the United States of America (USA), and few common in Asia at this time. As the pandemic evolved, travel-associated cases from South Africa and other neighbouring countries were also recorded. Transmission within quarantine centres occurred when travelling nationals returning to Zimbabwe. International and regional migration followed by local transmission were identified as accounting for the development of the SARS-CoV-2 epidemic in Zimbabwe. Based on this, rapid implementation of public health interventions are critical to reduce local transmission of SARS-CoV-2. Impact of the predominant G614 strain on severity of symptoms in COVID-19 cases needs further investigation.


Subject(s)
COVID-19 , Genomic Instability
10.
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.09.28.20201475

ABSTRACT

The COVID-19 pandemic has spread rapidly throughout the world. In the UK, the initial peak was in April 2020; in the county of Norfolk (UK) and surrounding areas, which has a stable, low-density population, over 3,200 cases were reported between March and August 2020. As part of the activities of the national COVID-19 Genomics Consortium (COG-UK) we undertook whole genome sequencing of the SARS-CoV-2 genomes present in positive clinical samples from the Norfolk region. These samples were collected by four major hospitals, multiple minor hospitals, care facilities and community organisations within Norfolk and surrounding areas. We combined clinical metadata with the sequencing data from regional SARS-CoV-2 genomes to understand the origins, genetic variation, transmission and expansion (spread) of the virus within the region and provide context nationally. Data were fed back into the national effort for pandemic management, whilst simultaneously being used to assist local outbreak analyses. Overall, 1,565 positive samples (172 per 100,000 population) from 1,376 cases were evaluated; for 140 cases between two and six samples were available providing longitudinal data. This represented 42.6% of all positive samples identified by hospital testing in the region and encompassed those with clinical need, and health and care workers and their families. 1,035 cases had genome sequences of sufficient quality to provide phylogenetic lineages. These genomes belonged to 26 distinct global lineages, indicating that there were multiple separate introductions into the region. Furthermore, 100 genetically-distinct UK lineages were detected demonstrating local evolution, at a rate of ~2 SNPs per month, and multiple co-occurring lineages as the pandemic progressed. Our analysis: identified a sublineage associated with 6 care facilities; found no evidence of reinfection in longitudinal samples; ruled out a nosocomial outbreak; identified 16 lineages in key workers which were not in patients indicating infection control measures were effective; found the D614G spike protein mutation which is linked to increased transmissibility dominates the samples and rapidly confirmed relatedness of cases in an outbreak at a food processing facility. The large-scale genome sequencing of SARS-CoV-2-positive samples has provided valuable additional data for public health epidemiology in the Norfolk region, and will continue to help identify and untangle hidden transmission chains as the pandemic evolves.


Subject(s)
COVID-19
11.
biorxiv; 2020.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2020.06.24.162156

ABSTRACT

The COVID-19 pandemic has spread to almost every country in the world since it started in China in late 2019. Controlling the pandemic requires a multifaceted approach including whole genome sequencing to support public health interventions at local and national levels. One of the most widely used methods for sequencing is the ARTIC protocol, a tiling PCR approach followed by Oxford Nanopore sequencing (ONT) of up to 24 samples at a time. There is a need for a higher throughput method to reduce cost per genome. Here we present CoronaHiT, a method capable of multiplexing up to 95 small genomes on a single Nanopore flowcell, which uses transposase mediated addition of adapters and PCR based addition of symmetric barcodes. We demonstrate the method using 48 and 94 SARS-CoV-2 genomes per flowcell, amplified using the ARTIC protocol, and compare performance with Illumina and ARTIC ONT sequencing. Results demonstrate that all sequencing methods produce inaccurate genomes when the RNA extract from SARS-CoV-2 positive clinical sample has a cycle threshold (Ct) >= 32. Results from set same set of 23 samples with a broad range of Cts show that the consensus genomes have >90% coverage (GISAID criteria) for 78.2% of samples for CoronaHiT-48, 73.9% for CoronaHiT-94, 78.2% for Illumina and 73.9% for ARTIC ONT, and all have the same clustering on a maximum likelihood tree. In conclusion, we demonstrate that CoronaHiT can multiplex up to 94 SARS-CoV-2 genomes per nanopore flowcell without compromising the quality of the resulting genomes while reducing library preparation complexity and significantly reducing cost. This protocol will aid the rapid expansion of SARS-CoV-2 genome sequencing globally, to help control the pandemic.


Subject(s)
COVID-19
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