Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 24
Filter
1.
biorxiv; 2023.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2023.01.31.526458

ABSTRACT

Despite millions of SARS-CoV-2 genomes being sequenced and shared globally, manipulating such data sets is still challenging, especially selecting sequences for focused phylogenetic analysis. We present a novel method, uvaia, which is based on partial and exact sequence similarity for quickly extracting database sequences similar to query sequences of interest. Many SARS-CoV-2 phylogenetic analyses rely on very low numbers of ambiguous sites as a measure of quality since ambiguous sites do not contribute to single nucleotide polymorphism (SNP) differences, which uvaia alleviates by using measures of sequence similarity that consider partially ambiguous sites. Such fine-grained definition of similarity allows not only for better phylogenetic analyses, but also for improved classification and biogeographical inferences. Uvaia works natively with compressed files, can use multiple cores and efficiently utilises memory, being able to analyse large data sets on a standard desktop.

2.
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.

3.
medrxiv; 2022.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2022.03.10.22272177

ABSTRACT

Background: The third wave of COVID-19 in England peaked in January 2022 resulting from the rapid transmission of the Omicron variant. However, rates of hospitalisations and deaths were substantially lower than in the first and second waves Methods: In the REal-time Assessment of Community Transmission-1 (REACT-1) study we obtained data from a random sample of 94,950 participants with valid throat and nose swab results by RT-PCR during round 18 (8 February to 1 March 2022). Findings: We estimated a weighted mean SARS-CoV-2 prevalence of 2.88% (95% credible interval [CrI] 2.76-3.00), with a within-round reproduction number (R) overall of 0.94 (0.91-0.96). While within-round weighted prevalence fell among children (aged 5 to 17 years) and adults aged 18 to 54 years, we observed a level or increasing weighted prevalence among those aged 55 years and older with an R of 1.04 (1.00-1.09). Among 1,195 positive samples with sublineages determined, only one (0.1% [0.0-0.5]) corresponded to AY.39 Delta sublineage and the remainder were Omicron: N=390, 32.7% (30.0-35.4) were BA.1; N=473, 39.6% (36.8-42.5) were BA.1.1; and N=331, 27.7% (25.2-30.4) were BA.2. We estimated an R additive advantage for BA.2 (vs BA.1 or BA.1.1) of 0.40 (0.36-0.43). The highest proportion of BA.2 among positives was found in London. Interpretation: In February 2022, infection prevalence in England remained high with level or increasing rates of infection in older people and an uptick in hospitalisations. Ongoing surveillance of both survey and hospitalisations data is required. Funding: Department of Health and Social Care, England.


Subject(s)
Death , COVID-19
4.
medrxiv; 2022.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2022.02.03.22270365

ABSTRACT

Background: Rapid transmission of the SARS-CoV-2 Omicron variant has led to the highest ever recorded case incidence levels in many countries around the world. Methods: The REal-time Assessment of Community Transmission-1 (REACT-1) study has been characterising the transmission of the SARS-CoV-2 virus using RT-PCR test results from self-administered throat and nose swabs from randomly-selected participants in England at ages 5 years and over, approximately monthly since May 2020. Round 17 data were collected between 5 and 20 January 2022 and provide data on the temporal, socio-demographic and geographical spread of the virus, viral loads and viral genome sequence data for positive swabs. Results: From 102,174 valid tests in round 17, weighted prevalence of swab positivity was 4.41% (95% credible interval [CrI], 4.25% to 4.56%), which is over three-fold higher than in December 2021 in England. Of 3,028 sequenced positive swabs, 2,393 lineages were determined and 2,374 (99.2%) were Omicron including 19 (0.80% of all Omicron lineages) cases of BA.2 sub-lineage and one BA.3 (0.04% of all Omicron) detected on 17 January 2022, and only 19 (0.79%) were Delta. The growth of the BA.2 Omicron sub-lineage against BA.1 and its sub-lineage BA.1.1 indicated a daily growth rate advantage of 0.14 (95% CrI, 0.03, 0.28) for BA.2, which corresponds to an additive R advantage of 0.46 (95% CrI, 0.10, 0.92). Within round 17, prevalence was decreasing overall (R=0.95, 95% CrI, 0.93, 0.97) but increasing in children aged 5 to 17 years (R=1.13, 95% CrI, 1.09, 1.18). Those 75 years and older had a swab-positivity prevalence of 2.46% (95% CI, 2.16%, 2.80%) reflecting a high level of infection among a highly vulnerable group. Among the 3,613 swab-positive individuals reporting whether or not they had had previous infection, 2,334 (64.6%) reported previous confirmed COVID-19. Of these, 64.4% reported a positive test from 1 to 30 days before their swab date. Risks of infection were increased among essential/key workers (other than healthcare or care home workers) with mutually adjusted Odds Ratio (OR) of 1.15 (95% CI, 1.05, 1.26), people living in large compared to single-person households (6+ household size OR 1.73; 95% CI, 1.44, 2.08), those living in urban vs rural areas (OR 1.24, 95% CI, 1.13, 1.35) and those living in the most vs least deprived areas (OR 1.34, 95% CI, 1.20, 1.49). Conclusions: We observed unprecedented levels of infection with SARS-CoV-2 in England in January 2022, an almost complete replacement of Delta by Omicron, and evidence for a growth advantage for BA.2 compared to BA.1. The increase in the prevalence of infection with Omicron among children (aged 5 to 17 years) during January 2022 could pose a risk to adults, despite the current trend for prevalence in adults to decline. (Funded by the Department of Health and Social Care in England.)


Subject(s)
COVID-19
5.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.11.03.21265877

ABSTRACT

Background: The third wave of COVID-19 in England coincided with the rapid spread of the Delta variant of SARS-CoV-2 from the end of May 2021. Case incidence data from the national testing programme (Pillar 2) in England may be affected by changes in testing behaviour and other biases. Community surveys may provide important contextual information to inform policy and the public health response. Methods: We estimated patterns of community prevalence of SARS-CoV-2 infection in England using RT-PCR swab-positivity, demographic and other risk factor data from round 15 (interim) of the REal-time Assessment of Community Transmission-1 (REACT-1) study (round 15a, carried out from 19 to 29 October 2021). We compared these findings with those from round 14 (9 to 27 September 2021). Results: During mid- to late-October 2021 (round 15a) weighted prevalence was 1.72% (1.61%, 1.84%) compared to 0.83% (0.76%, 0.89%) in September 2021 (round 14). The overall reproduction number (R) from round 14 to round 15a was 1.12 (1.11, 1.14) with increases in prevalence over this period (September to October) across age groups and regions except Yorkshire and The Humber. However, within round 15a (mid- to late-October) there was evidence of a fall in prevalence with R of 0.76 (0.65, 0.88). The highest weighted prevalence was observed among children aged 5 to 12 years at 5.85% (5.10%, 6.70%) and 13 to 17 years at 5.75% (5.02%, 6.57%). At regional level, there was an almost four-fold increase in weighted prevalence in South West from round 14 at 0.59% (0.43%,0.80%) to round 15a at 2.18% (1.84%, 2.58%), with highest smoothed prevalence at subregional level also found in South West in round 15a. Age, sex, key worker status, and presence of children in the home jointly contributed to the risk of swab-positivity. Among the 126 sequenced positive swabs obtained up until 23 October, all were Delta variant; 13 (10.3%) were identified as the AY.4.2 sub-lineage. Discussion: We observed the highest overall prevalence of swab-positivity seen in the REACT-1 study in England to date in round 15a (October 2021), with a two-fold rise in swab-positivity from round 14 (September 2021). Despite evidence of a fall in prevalence from mid- to late-October 2021, prevalence remains high, particularly in school-aged children, with evidence also of higher prevalence in households with one or more children. Thus, vaccination of children aged 12 and over remains a high priority (with possible extension to children aged 5-12) to help reduce within-household transmission and disruptions to education, as well as among adults, to lessen the risk of serious disease among those infected.


Subject(s)
COVID-19
6.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.10.09.21264695

ABSTRACT

The SARS-CoV-2 ARTIC amplicon protocol is the most widely used genome sequencing method for SARS-CoV-2, accounting for over 43% of publicly-available genome sequences. The protocol utilises 98 primers to amplify ~400bp fragments of the SARS-CoV-2 genome covering all 30,000 bases. Understanding the analytical performance metrics of this protocol will improve how the data is used and interpreted. Different concentrations of SARS-CoV-2 control material were used to establish the limit of detection (LoD) of the ARTIC protocol. Results demonstrated the LoD was a minimum of 25-50 virus particles per mL. The sensitivity of ARTIC was comparable to the published sensitivities of commercial diagnostics assays and could therefore be used to confirm diagnostic testing results. A set of over 3,600 clinical samples from three UK regions were then evaluated to compare the protocols performance to clinical diagnostic assays (Roche Lightcycler 480 II, AusDiagnostics, Roche Cobas, Hologic Panther, Corman RdRp, Roche Flow, ABI QuantStudio 5, Seegene Nimbus, Qiagen Rotorgene, Abbott M2000, Thermo TaqPath, Xpert). We developed a Python tool, RonaLDO, to perform this validation (available under the GNU GPL3 open-source licence from https://github.com/quadram-institute-bioscience/ronaldo). Positives detected by diagnostic platforms were generally supported by sequencing data; platforms that used RT-qPCR were the best predictors of whether the sample would subsequently sequence successfully. To maximise success of sample sequencing for phylogenetic analysis, samples with Ct <31 should be chosen. For diagnostic tests that do not provide a quantifiable Ct value, adding a quantification step is recommended. The ARTIC SARS-CoV-2 sequencing protocol is highly sensitive, capable of detecting SARS-CoV-2 in samples with Cts in the high 30s. However, to routinely obtain whole genome coverage, samples with Ct <31 are recommended. Comparing different virus detection methods close to their LoD was challenging and significant discordance was observed.

7.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.09.02.21262979

ABSTRACT

BackgroundThe prevalence of SARS-CoV-2 infection continues to drive rates of illness and hospitalisations despite high levels of vaccination, with the proportion of cases caused by the Delta lineage increasing in many populations. As vaccination programs roll out globally and social distancing is relaxed, future SARS-CoV-2 trends are uncertain. MethodsWe analysed prevalence trends and their drivers using reverse transcription-polymerase chain reaction (RT-PCR) swab-positivity data from round 12 (between 20 May and 7 June 2021) and round 13 (between 24 June and 12 July 2021) of the REal-time Assessment of Community Transmission-1 (REACT-1) study, with swabs sent to non-overlapping random samples of the population ages 5 years and over in England. ResultsWe observed sustained exponential growth with an average doubling time in round 13 of 25 days (lower Credible Interval of 15 days) and an increase in average prevalence from 0.15% (0.12%, 0.18%) in round 12 to 0.63% (0.57%, 0.18%) in round 13. The rapid growth across and within rounds appears to have been driven by complete replacement of Alpha variant by Delta, and by the high prevalence in younger less-vaccinated age groups, with a nine-fold increase between rounds 12 and 13 among those aged 13 to 17 years. Prevalence among those who reported being unvaccinated was three-fold higher than those who reported being fully vaccinated. However, in round 13, 44% of infections occurred in fully vaccinated individuals, reflecting imperfect vaccine effectiveness against infection despite high overall levels of vaccination. Using self-reported vaccination status, we estimated adjusted vaccine effectiveness against infection in round 13 of 49% (22%, 67%) among participants aged 18 to 64 years, which rose to 58% (33%, 73%) when considering only strong positives (Cycle threshold [Ct] values < 27); also, we estimated adjusted vaccine effectiveness against symptomatic infection of 59% (23%, 78%), with any one of three common COVID-19 symptoms reported in the month prior to swabbing. Sex (round 13 only), ethnicity, household size and local levels of deprivation jointly contributed to the risk of higher prevalence of swab-positivity. DiscussionFrom end May to beginning July 2021 in England, where there has been a highly successful vaccination campaign with high vaccine uptake, infections were increasing exponentially driven by the Delta variant and high infection prevalence among younger, unvaccinated individuals despite double vaccination continuing to effectively reduce transmission. Although slower growth or declining prevalence may be observed during the summer in the northern hemisphere, increased mixing during the autumn in the presence of the Delta variant may lead to renewed growth, even at high levels of vaccination.


Subject(s)
COVID-19
8.
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.06.17.21259103

ABSTRACT

BackgroundEngland entered a third national lockdown from 6 January 2021 due to the COVID-19 pandemic. Despite a successful vaccine rollout during the first half of 2021, cases and hospitalisations have started to increase since the end of May as the SARS-CoV-2 Delta (B.1.617.2) variant increases in frequency. The final step of relaxation of COVID-19 restrictions in England has been delayed from 21 June to 19 July 2021. MethodsThe REal-time Assessment of Community Transmision-1 (REACT-1) study measures the prevalence of swab-positivity among random samples of the population of England. Round 12 of REACT-1 obtained self-administered swab collections from participants from 20 May 2021 to 7 June 2021; results are compared with those for round 11, in which swabs were collected from 15 April to 3 May 2021. ResultsBetween rounds 11 and 12, national prevalence increased from 0.10% (0.08%, 0.13%) to 0.15% (0.12%, 0.18%). During round 12, we detected exponential growth with a doubling time of 11 (7.1, 23) days and an R number of 1.44 (1.20, 1.73). The highest prevalence was found in the North West at 0.26% (0.16%, 0.41%) compared to 0.05% (0.02%, 0.12%) in the South West. In the North West, the locations of positive samples suggested a cluster in Greater Manchester and the east Lancashire area. Prevalence in those aged 5-49 was 2.5 times higher at 0.20% (0.16%, 0.26%) compared with those aged 50 years and above at 0.08% (0.06%, 0.11%). At the beginning of February 2021, the link between infection rates and hospitalisations and deaths started to weaken, although in late April 2021, infection rates and hospital admissions started to reconverge. When split by age, the weakened link between infection rates and hospitalisations at ages 65 years and above was maintained, while the trends converged below the age of 65 years. The majority of the infections in the younger group occurred in the unvaccinated population or those without a stated vaccine history. We observed the rapid replacement of the Alpha (B.1.1.7) variant of SARS-CoV-2 with the Delta variant during the period covered by rounds 11 and 12 of the study. DiscussionThe extent to which exponential growth continues, or slows down as a consequence of the continued rapid roll-out of the vaccination programme, including to young adults, requires close monitoring. Data on community prevalence are vital to track the course of the epidemic and inform ongoing decisions about the timing of further lifting of restrictions in England.


Subject(s)
COVID-19
9.
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.

10.
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
11.
researchsquare; 2021.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-520627.v1

ABSTRACT

Understanding the drivers for spread of SARS-CoV-2 in higher education settings is important to limit transmission between students, and onward spread into at-risk populations. In this study, we prospectively sequenced 482 SARS-CoV-2 isolates derived from asymptomatic student screening and symptomatic testing of students and staff at the University of Cambridge from 5 October to 6 December 2020. We performed a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. After a limited number of viral introductions into the university, the majority of student cases were linked to a single genetic cluster, likely dispersed across the university following social gatherings at a venue outside the university. We identified considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and dramatically reduced following a national lockdown. We observed that transmission clusters were largely segregated within the university or within the community. This study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.

12.
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
13.
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
14.
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.01.04.425128

ABSTRACT

Soluble ACE2 (sACE2) decoy receptors are promising agents to inhibit SARS-CoV-2 as they are not affected by common escape mutations in viral proteins. However, their success may be limited by their relatively poor potency. To address these challenges, we developed a highly active multimeric sACE2 decoy receptor via a SunTag system that could neutralize both pseudoviruses bearing SARS-CoV-2 spike protein and SARS-CoV-2 clinical isolates. This fusion protein demonstrated a neutralization efficiency nearly 250-fold greater than monomeric sACE2. SunTag in combination with a more potent version of sACE2 achieved near complete neutralization at a sub-nanomolar range, which is comparable with clinical monoclonal antibodies. We demonstrate that this activity is due to greater occupancy of the multimeric decoy receptors on Spike protein as compared to monomeric sACE2. Overall, these highly potent multimeric sACE2 decoy receptors offer a promising treatment approach against SARS-CoV-2 infections including its novel variants.


Subject(s)
Severe Acute Respiratory Syndrome , COVID-19
15.
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.01.05.425478

ABSTRACT

COVID-19 is caused by the SARS-CoV-2 (SC2) virus and is more prevalent and severe in the elderly and patients with comorbid diseases (CM). Because chitinase 3-like-1 (CHI3L1) is induced during aging and CM, the relationships between CHI3L1 and SC2 were investigated. Here we demonstrate that CHI3L1 is a potent stimulator of the SC2 receptor ACE2 and viral spike protein priming proteases (SPP), that ACE2 and SPP are induced during aging and that anti-CHI3L1, kasugamycin and inhibitors of phosphorylation, abrogate these ACE2- and SPP- inductive events. Human studies also demonstrated that the levels of circulating CHI3L1 are increased in the elderly and patients with CM where they correlate with COVID-19 severity. These studies demonstrate that CHI3L1 is a potent stimulator of ACE2 and SPP; that this induction is a major mechanism contributing to the effects of aging during SC2 infection and that CHI3L1 coopts the CHI3L1 axis to augment SC2 infection. CHI3L1 plays a critical role in the pathogenesis of and is an attractive therapeutic target in COVID-19.


Subject(s)
COVID-19 , Disease
16.
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.01.06.425396

ABSTRACT

The antiviral restriction factor, tetherin, blocks the release of several different families of enveloped viruses, including the Coronaviridae. Tetherin is an interferon-induced protein that forms parallel homodimers between the host cell and viral particles, linking viruses to the surface of infected cells and inhibiting their release. We demonstrate that SARS-CoV-2 downregulates tetherin to aid its release from cells, and investigate potential proteins involved in this process. Loss of tetherin from cells caused an increase in SARS-CoV-2 viral titre. We find SARS-CoV-2 spike protein to be responsible for tetherin downregulation, rather than ORF7a as previously described for the 2002-2003 SARS-CoV. We instead find ORF7a to be responsible for Golgi fragmentation, and expression of ORF7a in cells recapitulates Golgi fragmentation observed in SARS-CoV-2 infected cells.


Subject(s)
Severe Acute Respiratory Syndrome
17.
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.01.05.425339

ABSTRACT

A novel coronavirus, SARS-CoV-2, has caused over 8538 million cases and over 1.8 1 million deaths worldwide since it occurred twelve months ago in Wuhan, China. Here we first analyzed 4,013 full-length SARS-CoV-2 genomes from different continents over a 14-week timespan since the outbreak in Wuhan, China. 2,954 unique nucleotide substitutions were identified with 31 of the 4,013 genomes remaining as ancestral type, and 952 (32.2%) mutations recurred in more than one genome. A viral genotype from the Seafood Market in Wuhan featured with two concurrent mutations was the dominant genotype (80.9%) of the pandemic. We also identified unique genotypic compositions from different geographic locations, and time-series viral genotypic dynamics in the early phase that reveal transmission routes and subsequent expansion. We also used the same approach to analyze 261,350 full-length SARS-CoV-2 genomes from the world over 12 months since the outbreak (i.e. all the available viral genomes in the GISAID database as of 25 December 2020). Our study indicates the viral genotypes can be utilized as molecular barcodes in combination with epidemiologic data to monitor the spreading routes of the pandemic and evaluate the effectiveness of control measures.


Subject(s)
COVID-19
18.
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.01.05.425420

ABSTRACT

To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results indicate that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation that was mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings identify biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.


Subject(s)
COVID-19 , Inflammation
19.
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.01.05.425516

ABSTRACT

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is a positive-strand RNA virus. Viral genome is capped at the 5'-end, followed by an untranslated region (UTR). There is poly-A tail at 3'-end, preceded by an UTR. Self-interaction between the RNA regulatory elements present within 5'- and 3'-UTRs as well as their interaction with host/virus-encoded proteins mediate the function of 5'- and 3'-UTRs. Using RNA-protein interaction detection (RaPID) assay coupled to liquid chromatography with tandem mass-spectrometry, we identified host interaction partners of SARS-CoV-2 5'- and 3'-UTRs and generated an RNA-protein interaction network. By combining these data with the previously known protein-protein interaction data proposed to be involved in virus replication, we generated the RNA-protein-protein interaction (RPPI) network, likely to be essential for controlling SARS-CoV-2 replication. Notably, bioinformatics analysis of the RPPI network revealed the enrichment of factors involved in translation initiation and RNA metabolism. Lysosome-associated membrane protein-2a (Lamp2a) was one of the host proteins that interact with the 5'-UTR. Further studies showed that Lamp2 level is upregulated in SARS-CoV-2 infected cells and overexpression of Lamp2a and Lamp2b variants reduced viral RNA level in infected cells and vice versa. In summary, our study provides an useful resource of SARS-CoV-2 5'- and 3'-UTR binding proteins and reveal the antiviral function of host Lamp2 protein.


Subject(s)
Coronavirus Infections , Severe Acute Respiratory Syndrome
20.
biorxiv; 2021.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2021.01.05.425508

ABSTRACT

Background: When a virus that has grown in a nonhuman host starts an epidemic in the human population, human cells may not provide growth conditions ideal for the virus. Therefore, the invasion of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which is usually prevalent in the bat population, into the human population is thought to have necessitated changes in the viral genome for efficient growth in the new environment. In the present study, to understand host-dependent changes in coronavirus genomes, we focused on the mono- and oligonucleotide compositions of SARS-CoV-2 genomes and investigated how these compositions changed time-dependently in the human cellular environment. We also compared the oligonucleotide compositions of SARS-CoV-2 and other coronaviruses prevalent in humans or bats to investigate the causes of changes in the host environment. Results: Time-series analyses of changes in the nucleotide compositions of SARS-CoV-2 genomes revealed a group of mono- and oligonucleotides whose compositions changed in a common direction for all clades, even though viruses belonging to different clades should evolve independently. Interestingly, the compositions of these oligonucleotides changed towards those of coronaviruses that have been prevalent in humans for a long period and away from those of bat coronaviruses. Conclusions: Clade-independent, time-dependent changes are thought to have biological significance and should relate to viral adaptation to a new host environment, providing important clues for understanding viral host adaptation mechanisms.


Subject(s)
Coronavirus Infections
SELECTION OF CITATIONS
SEARCH DETAIL