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1.
Preprint in English | medRxiv | ID: ppmedrxiv-22275086

ABSTRACT

RT-qPCR tests based on RNA extraction from nasopharyngeal swab samples are promoted as the "gold standard" for SARS-CoV-2 detection. However, self-collected saliva samples offer a non-invasive alternative more suited to high-throughput testing. This study evaluated the performance of TaqPath COVID-19 Fast PCR Combo Kit 2.0 assay for detection of SARS-CoV-2 in raw saliva relative to a lab-developed direct RT-qPCR test (SalivaDirect-based PCR) and a RT-qPCR test based on RNA extraction from NPS samples. Both samples were collected from symptomatic and asymptomatic individuals (N=615). Saliva samples were tested for SARS-CoV-2 using the TaqPath COVID-19 Fast PCR Combo Kit 2.0 and the SalivaDirect-based PCR, while RNA extracts from NPS samples were tested by RT-qPCR according to the Irish national testing system. The TaqPath COVID-19 Fast PCR detected SARS-CoV-2 in 52 saliva samples, of which 51 were also positive with the SalivaDirect-based PCR. 49 samples displayed concordant results with the NPS extraction-based method, while three samples were positive on raw saliva. Among the negative samples, 10 discordant cases were found with the TaqPath COVID-19 Fast PCR (PPA-85.7%; NPA-99.5%), when compared to the RNA extraction-based NPS method, performing similarly to the SalivaDirect-based PCR (PPA-87.5%; NPA-99.5%). The direct RT-qPCR testing of saliva samples shows high concordance with NPS extraction-based method for SARS-CoV-2 detection, providing a cost-effective and highly-scalable system for high-throughput COVID-19 rapid-testing.

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.
Preprint in English | medRxiv | ID: ppmedrxiv-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. One-Sentence SummaryExpanding Africa SARS-CoV-2 sequencing capacity in a fast evolving pandemic.

3.
Preprint in English | medRxiv | ID: ppmedrxiv-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.

4.
Preprint in English | medRxiv | ID: ppmedrxiv-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.

5.
Preprint in English | medRxiv | ID: ppmedrxiv-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.

6.
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.
Preprint in English | medRxiv | ID: ppmedrxiv-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.

7.
Preprint in English | medRxiv | ID: ppmedrxiv-20248606

ABSTRACT

AimSARS-CoV-2 has been detected in stool samples of COVID-19 patients, with potential implications for faecal-oral transmission. Compared to swab samples, the complexity of the stool matrix poses a challenge in the detection of the virus that has not yet been solved. The aim of this study was to establish a sensitive and reliable method for detecting SARS-CoV-2 in stool samples. MethodsStool samples from individuals free of SARS-CoV-2 were homogenised in saline buffer and spiked with a known titre of inactivated virus ranging from 50 to 750 viral particles per 100 mg stool. Debris was removed via centrifugation and supernatants were concentrated by ultrafiltration. RNA was then extracted from the concentrated material using a commercial kit and SARS-CoV-2 was detected via real-time reverse-transcription polymerase chain reaction (RT-qPCR) using the CDC primers and probes. ResultsThe RNA extraction procedure we used allowed the detection of SARS-CoV-2 via RT-qPCR in most of the stool samples tested. We could detect as few as 50 viral particles per 100 mg of stool. However, high variability was observed across samples at low viral titres. The primer set targeting the N1 region provided more reliable and precise results and for this primer set our method had a limit of detection of 1 viral particle per mg of stool. ConclusionsHere we describe a sensitive method for detecting SARS-CoV-2 in stool samples. This method can be used to establish the persistence of SARS-CoV-2 in stool and ensure the safety of clinical practices such as faecal microbiota transplant (FMT).

8.
Preprint in English | medRxiv | ID: ppmedrxiv-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.

9.
Preprint in English | medRxiv | ID: ppmedrxiv-20229989

ABSTRACT

BackgroundClinical metagenomics (CMg) is being evaluated for translation from a research tool into routine diagnostic service, but its potential to significantly improve management of acutely unwell patients has not been demonstrated. The SARS-CoV-2 pandemic provides impetus to determine that benefit given increased risk of secondary infection and nosocomial transmission by multi-drug resistant (MDR) pathogens linked with expansion of critical care capacity. MethodsProspective evaluation of CMg using nanopore sequencing was performed on 43 respiratory samples over 14 weeks from a cohort of 274 intubated patients across seven COVID-19 intensive care units. ResultsBacteria or fungi were cultured from 200 (73%) patients, with a predominance of Klebsiella spp. (31%) and C. striatum (7%) amongst other common respiratory pathogens. An 8 hour CMg workflow was 93% sensitive and 81% specific for bacterial identification compared to culture, and reported presence or absence of {beta}-lactam resistance genes carried by Enterobacterales that would modify initial guideline-recommended antibiotics in every case. CMg was also 100% concordant with quantitative PCR for detecting Aspergillus fumigatus (4 positive and 39 negative samples). Single nucleotide polymorphism (SNP)-typing using 24 hour sequence data identified an MDR-K. pneumoniae ST307 outbreak involving 4 patients and an MDR-C. striatum outbreak potentially involving 14 patients across three ICUs. ConclusionCMg testing for ICU patients provides same-day pathogen detection and antibiotic resistance prediction that significantly improves initial treatment of nosocomial pneumonia and rapidly detects unsuspected outbreaks of MDR-pathogens.

10.
Preprint in English | medRxiv | ID: ppmedrxiv-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. Major pointsIn Norfolk and surrounding regions O_LI100 distinct UK lineages were identified. C_LIO_LI16 UK lineages found in key workers were not observed in patients or in community care. C_LIO_LI172 genomes from SARS-CoV-2 positive samples sequenced per 100,000 population representing 42.6% of all positive cases. C_LIO_LISARS-CoV-2 genomes from 1035 cases sequenced to a high quality. C_LIO_LIOnly 5 countries, out of 103, have sequenced more SARS-CoV-2 genomes than have been sequenced in Norfolk for this paper. C_LIO_LISamples covered the entire first wave, March to August 2020. C_LIO_LIStable evolutionary rate of 2 SNPs per month. C_LIO_LID614G mutation is the dominant genotype and associated with increased transmission. C_LIO_LINo evidence of reinfection in 42 cases with longitudinal samples. C_LIO_LIWGS identified a sublineage associated with care facilities. C_LIO_LIWGS ruled out nosocomial outbreaks. C_LIO_LIRapid WGS confirmed the relatedness of cases from an outbreak at a food processing facility. C_LI

11.
Preprint in English | medRxiv | ID: ppmedrxiv-20131573

ABSTRACT

IntroductionSeveral viral respiratory infections - notably influenza - are associated with secondary bacterial infection and additional pathology. The extent to which this applies for COVID-19 is unknown. Accordingly, we aimed to define the bacteria causing secondary pneumonias in COVID-19 ICU patients using the FilmArray Pneumonia Panel, and to determine this tests potential in COVID-19 management. MethodsCOVID-19 ICU patients with clinically-suspected secondary infection at 5 UK hospitals were tested with the FilmArray at point of care. We collected patient demographic data and compared FilmArray results with routine culture. ResultsWe report results of 110 FilmArray tests on 94 patients (16 had 2 tests): 69 patients (73%) were male, the median age was 59 yrs; 92 were ventilated. Median hospital stay before testing was 14 days (range 1-38). Fifty-nine (54%) tests were positive, with 141 bacteria detected. Most were Enterobacterales (n=55, including Klebsiella spp. [n= 35]) or Staphylococcus aureus (n=13), as is typical of hospital and ventilator pneumonia. Community pathogens, including Haemophilus influenzae (n=8) and Streptococcus pneumoniae (n=1), were rarer. FilmArray detected one additional virus (Rhinovirus/Enterovirus) and no atypical bacteria. Fewer samples (28 % vs. 54%) were positive by routine culture, and fewer species were reported per sample; Klebsiella species remained the most prevalent pathogens. ConclusionFilmArray had a higher diagnostic yield than culture for ICU COVID-19 patients with suspected secondary pneumonias. The bacteria found mostly were Enterobacterales, S. aureus and P. aeruginosa, as in typical HAP/VAP, but with Klebsiella spp. more prominent. We found almost no viral co-infection. Turnaround from sample to results is around 1h 15 min compared with the usual 72h for culture, giving prescribers earlier data to inform antimicrobial decisions.

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