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Relph, Katharine A.; Russell, Clark D.; Fairfield, Cameron J.; Turtle, Lance, de Silva, Thushan I.; Siggins, Matthew K.; Drake, Thomas M.; Thwaites, Ryan S.; Abrams, Simon, Moore, Shona C.; Hardwick, Hayley E.; Oosthuyzen, Wilna, Harrison, Ewen M.; Docherty, Annemarie B.; Openshaw, Peter J. M.; Baillie, J. Kenneth, Semple, Malcolm G.; Ho, Antonia, Baillie, J. Kenneth, Semple, Malcolm G.; Openshaw, Peter J. M.; Carson, Gail, Alex, Beatrice, Bach, Benjamin, Barclay, Wendy S.; Bogaert, Debby, Chand, Meera, Cooke, Graham S.; Docherty, Annemarie B.; Dunning, Jake, Filipe, Ana da Silva, Fletcher, Tom, Green, Christopher A.; Harrison, Ewen M.; Hiscox, Julian A.; Ho, Antonia Ying Wai, Horby, Peter W.; Ijaz, Samreen, Khoo, Saye, Klenerman, Paul, Law, Andrew, Lim, Wei Shen, Mentzer, Alexander J.; Merson, Laura, Meynert, Alison M.; Noursadeghi, Mahdad, Moore, Shona C.; Palmarini, Massimo, Paxton, William A.; Pollakis, Georgios, Price, Nicholas, Rambaut, Andrew, Robertson, David L.; Russell, Clark D.; Sancho-Shimizu, Vanessa, Scott, Janet T.; de Silva, Thushan, Sigfrid, Louise, Solomon, Tom, Sriskandan, Shiranee, Stuart, David, Summers, Charlotte, Tedder, Richard S.; Thomson, Emma C.; Roger Thompson, A. A.; Thwaites, Ryan S.; Turtle, Lance C. W.; Gupta, Rishi K.; Zambon, Maria, Hardwick, Hayley, Donohue, Chloe, Lyons, Ruth, Griffiths, Fiona, Oosthuyzen, Wilna, Norman, Lisa, Pius, Riinu, Drake, Thomas M.; Fairfield, Cameron J.; Knight, Stephen R.; McLean, Kenneth A.; Murphy, Derek, Shaw, Catherine A.; Dalton, Jo, Girvan, Michelle, Saviciute, Egle, Roberts, Stephanie, Harrison, Janet, Marsh, Laura, Connor, Marie, Halpin, Sophie, Jackson, Clare, Gamble, Carrol, Leeming, Gary, Law, Andrew, Wham, Murray, Clohisey, Sara, Hendry, Ross, Scott-Brown, James, Greenhalf, William, Shaw, Victoria, McDonald, Sara, Keating, Seán, Ahmed, Katie A.; Armstrong, Jane A.; Ashworth, Milton, Asiimwe, Innocent G.; Bakshi, Siddharth, Barlow, Samantha L.; Booth, Laura, Brennan, Benjamin, Bullock, Katie, Catterall, Benjamin W. A.; Clark, Jordan J.; Clarke, Emily A.; Cole, Sarah, Cooper, Louise, Cox, Helen, Davis, Christopher, Dincarslan, Oslem, Dunn, Chris, Dyer, Philip, Elliott, Angela, Evans, Anthony, Finch, Lorna, Fisher, Lewis W. S.; Foster, Terry, Garcia-Dorival, Isabel, Greenhalf, William, Gunning, Philip, Hartley, Catherine, Jensen, Rebecca L.; Jones, Christopher B.; Jones, Trevor R.; Khandaker, Shadia, King, Katharine, Kiy, Robyn T.; Koukorava, Chrysa, Lake, Annette, Lant, Suzannah, Latawiec, Diane, Lavelle-Langham, Lara, Lefteri, Daniella, Lett, Lauren, Livoti, Lucia A.; Mancini, Maria, McDonald, Sarah, McEvoy, Laurence, McLauchlan, John, Metelmann, Soeren, Miah, Nahida S.; Middleton, Joanna, Mitchell, Joyce, Moore, Shona C.; Murphy, Ellen G.; Penrice-Randal, Rebekah, Pilgrim, Jack, Prince, Tessa, Reynolds, Will, Matthew Ridley, P.; Sales, Debby, Shaw, Victoria E.; Shears, Rebecca K.; Small, Benjamin, Subramaniam, Krishanthi S.; Szemiel, Agnieska, Taggart, Aislynn, Tanianis-Hughes, Jolanta, Thomas, Jordan, Trochu, Erwan, van Tonder, Libby, Wilcock, Eve, Eunice Zhang, J.; Flaherty, Lisa, Maziere, Nicole, Cass, Emily, Doce Carracedo, Alejandra, Carlucci, Nicola, Holmes, Anthony, Massey, Hannah, Murphy, Lee, Wrobel, Nicola, McCafferty, Sarah, Morrice, Kirstie, MacLean, Alan, Adeniji, Kayode, Agranoff, Daniel, Agwuh, Ken, Ail, Dhiraj, Aldera, Erin L.; Alegria, Ana, Angus, Brian, Ashish, Abdul, Atkinson, Dougal, Bari, Shahedal, Barlow, Gavin, Barnass, Stella, Barrett, Nicholas, Bassford, Christopher, Basude, Sneha, Baxter, David, Beadsworth, Michael, Bernatoniene, Jolanta, Berridge, John, Best, Nicola, Bothma, Pieter, Chadwick, David, Brittain-Long, Robin, Bulteel, Naomi, Burden, Tom, Burtenshaw, Andrew, Caruth, Vikki, Chadwick, David, Chambler, Duncan, Chee, Nigel, Child, Jenny, Chukkambotla, Srikanth, Clark, Tom, Collini, Paul, Cosgrove, Catherine, Cupitt, Jason, Cutino-Moguel, Maria-Teresa, Dark, Paul, Dawson, Chris, Dervisevic, Samir, Donnison, Phil, Douthwaite, Sam, DuRand, Ingrid, Dushianthan, Ahilanadan, Dyer, Tristan, Evans, Cariad, Eziefula, Chi, Fegan, Christopher, Finn, Adam, Fullerton, Duncan, Garg, Sanjeev, Garg, Sanjeev, Garg, Atul, Gkrania-Klotsas, Effrossyni, Godden, Jo, Goldsmith, Arthur, Graham, Clive, Hardy, Elaine, Hartshorn, Stuart, Harvey, Daniel, Havalda, Peter, Hawcutt, Daniel B.; Hobrok, Maria, Hodgson, Luke, Hormis, Anil, Jacobs, Michael, Jain, Susan, Jennings, Paul, Kaliappan, Agilan, Kasipandian, Vidya, Kegg, Stephen, Kelsey, Michael, Kendall, Jason, Kerrison, Caroline, Kerslake, Ian, Koch, Oliver, Koduri, Gouri, Koshy, George, Laha, Shondipon, Laird, Steven, Larkin, Susan, Leiner, Tamas, Lillie, Patrick, Limb, James, Linnett, Vanessa, Little, Jeff, Lyttle, Mark, MacMahon, Michael, MacNaughton, Emily, Mankregod, Ravish, Masson, Huw, Matovu, Elijah, McCullough, Katherine, McEwen, Ruth, Meda, Manjula, Mills, Gary, Minton, Jane, Mirfenderesky, Mariyam, Mohandas, Kavya, Mok, Quen, Moon, James, Moore, Elinoor, Morgan, Patrick, Morris, Craig, Mortimore, Katherine, Moses, Samuel, Mpenge, Mbiye, Mulla, Rohinton, Murphy, Michael, Nagel, Megan, Nagarajan, Thapas, Nelson, Mark, O’Shea, Matthew K.; Otahal, Igor, Ostermann, Marlies, Pais, Mark, Panchatsharam, Selva, Papakonstantinou, Danai, Paraiso, Hassan, Patel, Brij, Pattison, Natalie, Pepperell, Justin, Peters, Mark, Phull, Mandeep, Pintus, Stefania, Pooni, Jagtur Singh, Post, Frank, Price, David, Prout, Rachel, Rae, Nikolas, Reschreiter, Henrik, Reynolds, Tim, Richardson, Neil, Roberts, Mark, Roberts, Devender, Rose, Alistair, Rousseau, Guy, Ryan, Brendan, Saluja, Taranprit, Shah, Aarti, Shanmuga, Prad, Sharma, Anil, Shawcross, Anna, Sizer, Jeremy, Shankar-Hari, Manu, Smith, Richard, Snelson, Catherine, Spittle, Nick, Staines, Nikki, Stambach, Tom, Stewart, Richard, Subudhi, Pradeep, Szakmany, Tamas, Tatham, Kate, Thomas, Jo, Thompson, Chris, Thompson, Robert, Tridente, Ascanio, Tupper-Carey, Darell, Twagira, Mary, Ustianowski, Andrew, Vallotton, Nick, Vincent-Smith, Lisa, Visuvanathan, Shico, Vuylsteke, Alan, Waddy, Sam, Wake, Rachel, Walden, Andrew, Welters, Ingeborg, Whitehouse, Tony, Whittaker, Paul, Whittington, Ashley, Papineni, Padmasayee, Wijesinghe, Meme, Williams, Martin, Wilson, Lawrence, Cole, Sarah, Winchester, Stephen, Wiselka, Martin, Wolverson, Adam, Wootton, Daniel G.; Workman, Andrew, Yates, Bryan, Young, Peter.
Open Forum Infectious Diseases ; 9(5), 2022.
Article in English | PMC | ID: covidwho-1821760

ABSTRACT

Admission procalcitonin measurements and microbiology results were available for 1040 hospitalized adults with coronavirus disease 2019 (from 48 902 included in the International Severe Acute Respiratory and Emerging Infections Consortium World Health Organization Clinical Characterisation Protocol UK study). Although procalcitonin was higher in bacterial coinfection, this was neither clinically significant (median [IQR], 0.33 [0.11–1.70] ng/mL vs 0.24 [0.10–0.90] ng/mL) nor diagnostically useful (area under the receiver operating characteristic curve, 0.56 [95% confidence interval, .51–.60]).

4.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-330044

ABSTRACT

Background: We aimed to measure SARS-CoV-2 seroprevalence in a cohort of healthcare workers (HCWs) during the first UK wave of the COVID-19 pandemic, explore risk factors associated with infection, and investigate the impact of antibody titres on assay sensitivity. Methods: :  HCWs at Sheffield Teaching Hospitals NHS Foundation Trust were prospectively enrolled and sampled at two time points. We developed an in-house ELISA for testing participant serum for SARS-CoV-2 IgG and IgA reactivity against Spike and Nucleoprotein. Data were analysed using three statistical models: a seroprevalence model, an antibody kinetics model, and a heterogeneous sensitivity model. Results: :  Our in-house assay had a sensitivity of 99·47% and specificity of 99·56%. We found that 24·4% (n=311/1275) of HCWs were seropositive as of 12th June 2020. Of these, 39·2% (n=122/311) were asymptomatic. The highest adjusted seroprevalence was measured in HCWs on the Acute Medical Unit (41·1%, 95% CrI 30·0–52·9) and in Physiotherapists and Occupational Therapists (39·2%, 95% CrI 24·4–56·5). Older age groups showed overall higher median antibody titres. Further modelling suggests that, for a serological assay with an overall sensitivity of 80%, antibody titres may be markedly affected by differences in age, with sensitivity estimates of 89% in those over 60 years but 61% in those ≤30 years. Conclusions: :   HCWs in acute medical units and those working closely with COVID-19 patients were at highest risk of infection, though whether these are infections acquired from patients or other staff is unknown. Current serological assays may underestimate seroprevalence in younger age groups if validated using sera from older and/or more severe COVID-19 cases.

5.
Nat Commun ; 13(1): 1251, 2022 03 10.
Article in English | MEDLINE | ID: covidwho-1740439

ABSTRACT

The trajectories of acquired immunity to severe acute respiratory syndrome coronavirus 2 infection are not fully understood. We present a detailed longitudinal cohort study of UK healthcare workers prior to vaccination, presenting April-June 2020 with asymptomatic or symptomatic infection. Here we show a highly variable range of responses, some of which (T cell interferon-gamma ELISpot, N-specific antibody) wane over time, while others (spike-specific antibody, B cell memory ELISpot) are stable. We use integrative analysis and a machine-learning approach (SIMON - Sequential Iterative Modeling OverNight) to explore this heterogeneity. We identify a subgroup of participants with higher antibody responses and interferon-gamma ELISpot T cell responses, and a robust trajectory for longer term immunity associates with higher levels of neutralising antibodies against the infecting (Victoria) strain and also against variants B.1.1.7 (alpha) and B.1.351 (beta). These variable trajectories following early priming may define subsequent protection from severe disease from novel variants.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Viral , Antiviral Agents , Humans , Longitudinal Studies , Spike Glycoprotein, Coronavirus
7.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327612

ABSTRACT

Introduction: Viral sequencing of SARS-CoV-2 has been used for outbreak investigation, but there is limited evidence supporting routine use for infection prevention and control (IPC) within hospital settings. Methods We conducted a prospective non-randomised trial of sequencing at 14 acute UK hospital trusts. Sites each had a 4-week baseline data-collection period, followed by intervention periods comprising 8 weeks of 'rapid' (<48h) and 4 weeks of 'longer-turnaround' (5-10 day) sequencing using a sequence reporting tool (SRT). Data were collected on all hospital onset COVID-19 infections (HOCIs;detected ≥48h from admission). The impact of the sequencing intervention on IPC knowledge and actions, and on incidence of probable/definite hospital-acquired infections (HAIs) was evaluated. Results A total of 2170 HOCI cases were recorded from October 2020-April 2021, with sequence reports returned for 650/1320 (49.2%) during intervention phases. We did not detect a statistically significant change in weekly incidence of HAIs in longer-turnaround (IRR 1.60, 95%CI 0.85-3.01;P=0.14) or rapid (0.85, 0.48-1.50;P=0.54) intervention phases compared to baseline phase. However, IPC practice was changed in 7.8% and 7.4% of all HOCI cases in rapid and longer-turnaround phases, respectively, and 17.2% and 11.6% of cases where the report was returned. In a per-protocol sensitivity analysis there was an impact on IPC actions in 20.7% of HOCI cases when the SRT report was returned within 5 days. Conclusion While we did not demonstrate a direct impact of sequencing on the incidence of nosocomial transmission, our results suggest that sequencing can inform IPC response to HOCIs, particularly when returned within 5 days.

8.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-322827

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is normally controlled by effective host immunity including innate, humoral and cellular responses. However, the trajectories and correlates of acquired immunity, and the capacity of memory responses months after infection to neutralise variants of concern - which has important public health implications - is not fully understood. To address this, we studied a cohort of 78 UK healthcare workers who presented in April to June 2020 with symptomatic PCR-confirmed infection or who tested positive during an asymptomatic screening programme and tracked virus-specific B and T cell responses longitudinally at 5-6 time points each over 6 months, prior to vaccination. We observed a highly variable range of responses, some of which - T cell interferon-gamma (IFN-γ) ELISpot, N-specific antibody waned over time across the cohort, while others (spike-specific antibody, B cell memory ELISpot) were stable. In such cohorts, antiviral antibody has been linked to protection against re-infection. We used integrative analysis and a machine-learning approach (SIMON - Sequential Iterative Modeling Over Night) to explore this heterogeneity and to identify predictors of sustained immune responses. Hierarchical clustering defined a group of high and low antibody responders, which showed stability over time regardless of clinical presentation. These antibody responses correlated with IFN-γ ELISpot measures of T cell immunity and represent a subgroup of patients with a robust trajectory for longer term immunity. Importantly, this immune-phenotype associates with higher levels of neutralising antibodies not only against the infecting (Victoria) strain but also against variants B.1.1.7 (alpha) and B.1.351 (beta). Overall memory responses to SARS-CoV-2 show distinct trajectories following early priming, that may define subsequent protection against infection and severe disease from novel variants.

9.
Frontiers in immunology ; 12, 2021.
Article in English | EuropePMC | ID: covidwho-1688458

ABSTRACT

Multiple sclerosis (MS) is a central nervous system (CNS) disorder, which is mediated by an abnormal immune response coordinated by T and B cells resulting in areas of inflammation, demyelination, and axonal loss. Disease-modifying treatments (DMTs) are available to dampen the inflammatory aggression but are ineffective in many patients. Autologous hematopoietic stem cell transplantation (HSCT) has been used as treatment in patients with a highly active disease, achieving a long-term clinical remission in most. The rationale of the intervention is to eradicate inflammatory autoreactive cells with lympho-ablative regimens and restore immune tolerance. Immunological studies have demonstrated that autologous HSCT induces a renewal of TCR repertoires, resurgence of immune regulatory cells, and depletion of proinflammatory T cell subsets, suggesting a “resetting” of immunological memory. Although our understanding of the clinical and immunological effects of autologous HSCT has progressed, further work is required to characterize the mechanisms that underlie treatment efficacy. Considering that memory B cells are disease-promoting and stem-like T cells are multipotent progenitors involved in self-regeneration of central and effector memory cells, investigating the reconstitution of B cell compartment and stem and effector subsets of immunological memory following autologous HSCT could elucidate those mechanisms. Since all subjects need to be optimally protected from vaccine-preventable diseases (including COVID-19), there is a need to ensure that vaccination in subjects undergoing HSCT is effective and safe. Additionally, the study of vaccination in HSCT-treated subjects as a means of evaluating immune responses could further distinguish broad immunosuppression from immune resetting.

10.
Nat Commun ; 13(1): 671, 2022 02 03.
Article in English | MEDLINE | ID: covidwho-1671559

ABSTRACT

Hospital outbreaks of COVID19 result in considerable mortality and disruption to healthcare services and yet little is known about transmission within this setting. We characterise within hospital transmission by combining viral genomic and epidemiological data using Bayesian modelling amongst 2181 patients and healthcare workers from a large UK NHS Trust. Transmission events were compared between Wave 1 (1st March to 25th J'uly 2020) and Wave 2 (30th November 2020 to 24th January 2021). We show that staff-to-staff transmissions reduced from 31.6% to 12.9% of all infections. Patient-to-patient transmissions increased from 27.1% to 52.1%. 40%-50% of hospital-onset patient cases resulted in onward transmission compared to 4% of community-acquired cases. Control measures introduced during the pandemic likely reduced transmissions between healthcare workers but were insufficient to prevent increasing numbers of patient-to-patient transmissions. As hospital-acquired cases drive most onward transmission, earlier identification of nosocomial cases will be required to break hospital transmission chains.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Genome, Viral , Molecular Epidemiology , Pandemics , SARS-CoV-2/genetics , Bayes Theorem , Cohort Studies , Cross Infection/epidemiology , Cross Infection/transmission , Disease Outbreaks , Genomics , Health Personnel , Hospitals , Humans , United Kingdom/epidemiology
11.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-295696

ABSTRACT

SARS-CoV-2 lineage B.1.1.7 viruses are more transmissible, may lead to greater clinical severity, and result in modest reductions in antibody neutralization. subgenomic RNA (sgRNA) is produced by discontinuous transcription of the SARS-CoV-2 genome and is a crucial step in the SARS-CoV-2 life cycle. Applying our tool (periscope) to ARTIC Network Oxford Nanopore genomic sequencing data from 4400 SARS-CoV-2 positive clinical samples, we show that normalised sgRNA expression profiles are significantly increased in B.1.1.7 infections (n=879). This increase is seen over the previous dominant circulating lineage in the UK, B.1.177 (n=943), which is independent of genomic reads, E gene cycle threshold and days since symptom onset at sampling. A noncanonical sgRNA which could represent ORF9b is found in 98.4% of B.1.1.7 SARS-CoV-2 infections compared with only 13.8% of other lineages, with a 16-fold increase in median expression. We hypothesise that this is a direct consequence of a triple nucleotide mutation in nucleocapsid (28280:GAT>CAT, D3L) creating a transcription regulatory-like sequence complementary to a region 3’ of the genomic leader. These findings provide a unique insight into the biology of B.1.1.7 and support monitoring of sgRNA profiles in sequence data to evaluate emerging potential variants of concern. One Sentence Summary The recently emerged and more transmissible SARS-CoV-2 lineage B.1.1.7 shows greater subgenomic RNA expression in clinical infections and enhanced expression of a noncanonical subgenomic RNA near ORF9b.

12.
J Med Virol ; 94(1): 161-172, 2022 01.
Article in English | MEDLINE | ID: covidwho-1544335

ABSTRACT

Detailed information on intrahost viral evolution in SARS-CoV-2 with and without treatment is limited. Sequential viral loads and deep sequencing of SARS-CoV-2 from the upper respiratory tract of nine hospitalized children, three of whom were treated with remdesivir, revealed that remdesivir treatment suppressed viral load in one patient but not in a second infected with an identical strain without any evidence of drug resistance found. Reduced levels of subgenomic RNA during treatment of the second patient, suggest an additional effect of remdesivir on viral replication. Haplotype reconstruction uncovered persistent SARS-CoV-2 variant genotypes in four patients. These likely arose from within-host evolution, although superinfection cannot be excluded in one case. Although our dataset is small, observed sample-to-sample heterogeneity in variant frequencies across four of nine patients suggests the presence of discrete viral populations in the lung with incomplete population sampling in diagnostic swabs. Such compartmentalization could compromise the penetration of remdesivir into the lung, limiting the drugs in vivo efficacy, as has been observed in other lung infections.


Subject(s)
Adenosine Monophosphate/analogs & derivatives , Alanine/analogs & derivatives , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/virology , Evolution, Molecular , SARS-CoV-2/genetics , Adenosine Monophosphate/therapeutic use , Adolescent , Alanine/therapeutic use , Child , Child, Preschool , Drug Resistance, Viral , Female , Haplotypes , Humans , Infant , Lung/virology , Male , Phylogeny , RNA, Viral/analysis , RNA, Viral/genetics , SARS-CoV-2/isolation & purification , SARS-CoV-2/physiology , Viral Load , Virus Replication/drug effects
13.
Lancet Microbe ; 3(1): e21-e31, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1510521

ABSTRACT

BACKGROUND: Previous infection with SARS-CoV-2 affects the immune response to the first dose of the SARS-CoV-2 vaccine. We aimed to compare SARS-CoV-2-specific T-cell and antibody responses in health-care workers with and without previous SARS-CoV-2 infection following a single dose of the BNT162b2 (tozinameran; Pfizer-BioNTech) mRNA vaccine. METHODS: We sampled health-care workers enrolled in the PITCH study across four hospital sites in the UK (Oxford, Liverpool, Newcastle, and Sheffield). All health-care workers aged 18 years or older consenting to participate in this prospective cohort study were included, with no exclusion criteria applied. Blood samples were collected where possible before vaccination and 28 (±7) days following one or two doses (given 3-4 weeks apart) of the BNT162b2 vaccine. Previous infection was determined by a documented SARS-CoV-2-positive RT-PCR result or the presence of positive anti-SARS-CoV-2 nucleocapsid antibodies. We measured spike-specific IgG antibodies and quantified T-cell responses by interferon-γ enzyme-linked immunospot assay in all participants where samples were available at the time of analysis, comparing SARS-CoV-2-naive individuals to those with previous infection. FINDINGS: Between Dec 9, 2020, and Feb 9, 2021, 119 SARS-CoV-2-naive and 145 previously infected health-care workers received one dose, and 25 SARS-CoV-2-naive health-care workers received two doses, of the BNT162b2 vaccine. In previously infected health-care workers, the median time from previous infection to vaccination was 268 days (IQR 232-285). At 28 days (IQR 27-33) after a single dose, the spike-specific T-cell response measured in fresh peripheral blood mononuclear cells (PBMCs) was higher in previously infected (n=76) than in infection-naive (n=45) health-care workers (median 284 [IQR 150-461] vs 55 [IQR 24-132] spot-forming units [SFUs] per 106 PBMCs; p<0·0001). With cryopreserved PBMCs, the T-cell response in previously infected individuals (n=52) after one vaccine dose was equivalent to that of infection-naive individuals (n=19) after receiving two vaccine doses (median 152 [IQR 119-275] vs 162 [104-258] SFUs/106 PBMCs; p=1·00). Anti-spike IgG antibody responses following a single dose in 142 previously infected health-care workers (median 270 373 [IQR 203 461-535 188] antibody units [AU] per mL) were higher than in 111 infection-naive health-care workers following one dose (35 001 [17 099-55 341] AU/mL; p<0·0001) and higher than in 25 infection-naive individuals given two doses (180 904 [108 221-242 467] AU/mL; p<0·0001). INTERPRETATION: A single dose of the BNT162b2 vaccine is likely to provide greater protection against SARS-CoV-2 infection in individuals with previous SARS-CoV-2 infection, than in SARS-CoV-2-naive individuals, including against variants of concern. Future studies should determine the additional benefit of a second dose on the magnitude and durability of immune responses in individuals vaccinated following infection, alongside evaluation of the impact of extending the interval between vaccine doses. FUNDING: UK Department of Health and Social Care, and UK Coronavirus Immunology Consortium.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Viral , Antibody Formation , COVID-19/prevention & control , COVID-19 Vaccines , Humans , Immunoglobulin G , Leukocytes, Mononuclear , Prospective Studies , T-Lymphocytes , United Kingdom/epidemiology , Vaccines, Synthetic
14.
iScience ; 24(11): 103353, 2021 Nov 19.
Article in English | MEDLINE | ID: covidwho-1509904

ABSTRACT

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.

15.
Front Microbiol ; 12: 722838, 2021.
Article in English | MEDLINE | ID: covidwho-1450821

ABSTRACT

Background: In order to understand the molecular epidemiology of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Sri Lanka, since March 2020, we carried out genomic sequencing overlaid on available epidemiological data until April 2021. Methods: Whole genome sequencing was carried out on diagnostic sputum or nasopharyngeal swabs from 373 patients with COVID-19. Molecular clock phylogenetic analysis was undertaken to further explore dominant lineages. Results: The B.1.411 lineage was most prevalent, which was established in Sri Lanka and caused outbreaks throughout the country until March 2021. The estimated time of the most recent common ancestor (tMRCA) of this lineage was June 1, 2020 (with 95% lower and upper bounds March 30 to July 27) suggesting cryptic transmission may have occurred, prior to a large epidemic starting in October 2020. Returning travellers were identified with infections caused by lineage B.1.258, as well as the more transmissible B.1.1.7 lineage, which has replaced B.1.411 to fuel the ongoing large outbreak in the country. Conclusions: The large outbreak that started in early October, is due to spread of a single virus lineage, B.1.411 until the end of March 2021, when B.1.1.7 emerged and became the dominant lineage.

16.
J Infect ; 83(6): 693-700, 2021 12.
Article in English | MEDLINE | ID: covidwho-1446866

ABSTRACT

OBJECTIVES: Recently emerging SARS-CoV-2 variants have been associated with an increased rate of transmission within the community. We sought to determine whether this also resulted in increased transmission within hospitals. METHODS: We collected viral sequences and epidemiological data of patients with community and healthcare associated SARS-CoV-2 infections, sampled from 16th November 2020 to 10th January 2021, from nine hospitals participating in the COG-UK HOCI study. Outbreaks were identified using ward information, lineage and pairwise genetic differences between viral sequences. RESULTS: Mixed effects logistic regression analysis of 4184 sequences showed healthcare-acquired infections were no more likely to be identified as the Alpha variant than community acquired infections. Nosocomial outbreaks were investigated based on overlapping ward stay and SARS-CoV-2 genome sequence similarity. There was no significant difference in the number of patients involved in outbreaks caused by the Alpha variant compared to outbreaks caused by other lineages. CONCLUSIONS: We find no evidence to support it causing more nosocomial transmission than previous lineages. This suggests that the stringent infection prevention measures already in place in UK hospitals contained the spread of the Alpha variant as effectively as other less transmissible lineages, providing reassurance of their efficacy against emerging variants of concern.


Subject(s)
COVID-19 , Cross Infection , Cross Infection/epidemiology , Hospitals , Humans , SARS-CoV-2 , United Kingdom/epidemiology
17.
BMJ Open Respir Res ; 8(1)2021 09.
Article in English | MEDLINE | ID: covidwho-1430193

ABSTRACT

BACKGROUND: SARS-CoV-2 lineage B.1.1.7 has been associated with an increased rate of transmission and disease severity among subjects testing positive in the community. Its impact on hospitalised patients is less well documented. METHODS: We collected viral sequences and clinical data of patients admitted with SARS-CoV-2 and hospital-onset COVID-19 infections (HOCIs), sampled 16 November 2020 to 10 January 2021, from eight hospitals participating in the COG-UK-HOCI study. Associations between the variant and the outcomes of all-cause mortality and intensive therapy unit (ITU) admission were evaluated using mixed effects Cox models adjusted by age, sex, comorbidities, care home residence, pregnancy and ethnicity. FINDINGS: Sequences were obtained from 2341 inpatients (HOCI cases=786) and analysis of clinical outcomes was carried out in 2147 inpatients with all data available. The HR for mortality of B.1.1.7 compared with other lineages was 1.01 (95% CI 0.79 to 1.28, p=0.94) and for ITU admission was 1.01 (95% CI 0.75 to 1.37, p=0.96). Analysis of sex-specific effects of B.1.1.7 identified increased risk of mortality (HR 1.30, 95% CI 0.95 to 1.78, p=0.096) and ITU admission (HR 1.82, 95% CI 1.15 to 2.90, p=0.011) in females infected with the variant but not males (mortality HR 0.82, 95% CI 0.61 to 1.10, p=0.177; ITU HR 0.74, 95% CI 0.52 to 1.04, p=0.086). INTERPRETATION: In common with smaller studies of patients hospitalised with SARS-CoV-2, we did not find an overall increase in mortality or ITU admission associated with B.1.1.7 compared with other lineages. However, women with B.1.1.7 may be at an increased risk of admission to intensive care and at modestly increased risk of mortality.


Subject(s)
COVID-19 , SARS-CoV-2 , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/mortality , COVID-19/virology , COVID-19 Testing , Child , Child, Preschool , Cohort Studies , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Severity of Illness Index , United Kingdom , Young Adult
18.
Pathog Immun ; 6(2): 27-49, 2021.
Article in English | MEDLINE | ID: covidwho-1399715

ABSTRACT

BACKGROUND: Genetic variations across the SARS-CoV-2 genome may influence transmissibility of the virus and the host's anti-viral immune response, in turn affecting the frequency of variants over time. In this study, we examined the adjacent amino acid polymorphisms in the nucleocapsid (R203K/G204R) of SARS-CoV-2 that arose on the background of the spike D614G change and describe how strains harboring these changes became dominant circulating strains globally. METHODS: Deep-sequencing data of SARS-CoV-2 from public databases and from clinical samples were analyzed to identify and map genetic variants and sub-genomic RNA transcripts across the genome. Results: Sequence analysis suggests that the 3 adjacent nucleotide changes that result in the K203/R204 variant have arisen by homologous recombination from the core sequence of the leader transcription-regulating sequence (TRS) rather than by stepwise mutation. The resulting sequence changes generate a novel sub-genomic RNA transcript for the C-terminal dimerization domain of nucleocapsid. Deep-sequencing data from 981 clinical samples confirmed the presence of the novel TRS-CS-dimerization domain RNA in individuals with the K203/R204 variant. Quantification of sub-genomic RNA indicates that viruses with the K203/R204 variant may also have increased expression of sub-genomic RNA from other open reading frames. CONCLUSIONS: The finding that homologous recombination from the TRS may have occurred since the introduction of SARS-CoV-2 in humans, resulting in both coding changes and novel sub-genomic RNA transcripts, suggests this as a mechanism for diversification and adaptation within its new host.

19.
Emerg Infect Dis ; 27(8): 2064-2072, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1319582

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is evolving differently in Africa than in other regions. Africa has lower SARS-CoV-2 transmission rates and milder clinical manifestations. Detailed SARS-CoV-2 epidemiologic data are needed in Africa. We used publicly available data to calculate SARS-CoV-2 infections per 1,000 persons in The Gambia. We evaluated transmission rates among 1,366 employees of the Medical Research Council Unit The Gambia (MRCG), where systematic surveillance of symptomatic cases and contact tracing were implemented. By September 30, 2020, The Gambia had identified 3,579 SARS-CoV-2 cases, including 115 deaths; 67% of cases were identified in August. Among infections, MRCG staff accounted for 191 cases; all were asymptomatic or mild. The cumulative incidence rate among nonclinical MRCG staff was 124 infections/1,000 persons, which is >80-fold higher than estimates of diagnosed cases among the population. Systematic surveillance and seroepidemiologic surveys are needed to clarify the extent of SARS-CoV-2 transmission in Africa.


Subject(s)
COVID-19 , Africa , Gambia/epidemiology , Humans , Pandemics , SARS-CoV-2 , Seroepidemiologic Studies
20.
Lancet ; 398(10296): 223-237, 2021 07 17.
Article in English | MEDLINE | ID: covidwho-1313499

ABSTRACT

BACKGROUND: COVID-19 is a multisystem disease and patients who survive might have in-hospital complications. These complications are likely to have important short-term and long-term consequences for patients, health-care utilisation, health-care system preparedness, and society amidst the ongoing COVID-19 pandemic. Our aim was to characterise the extent and effect of COVID-19 complications, particularly in those who survive, using the International Severe Acute Respiratory and Emerging Infections Consortium WHO Clinical Characterisation Protocol UK. METHODS: We did a prospective, multicentre cohort study in 302 UK health-care facilities. Adult patients aged 19 years or older, with confirmed or highly suspected SARS-CoV-2 infection leading to COVID-19 were included in the study. The primary outcome of this study was the incidence of in-hospital complications, defined as organ-specific diagnoses occurring alone or in addition to any hallmarks of COVID-19 illness. We used multilevel logistic regression and survival models to explore associations between these outcomes and in-hospital complications, age, and pre-existing comorbidities. FINDINGS: Between Jan 17 and Aug 4, 2020, 80 388 patients were included in the study. Of the patients admitted to hospital for management of COVID-19, 49·7% (36 367 of 73 197) had at least one complication. The mean age of our cohort was 71·1 years (SD 18·7), with 56·0% (41 025 of 73 197) being male and 81·0% (59 289 of 73 197) having at least one comorbidity. Males and those aged older than 60 years were most likely to have a complication (aged ≥60 years: 54·5% [16 579 of 30 416] in males and 48·2% [11 707 of 24 288] in females; aged <60 years: 48·8% [5179 of 10 609] in males and 36·6% [2814 of 7689] in females). Renal (24·3%, 17 752 of 73 197), complex respiratory (18·4%, 13 486 of 73 197), and systemic (16·3%, 11 895 of 73 197) complications were the most frequent. Cardiovascular (12·3%, 8973 of 73 197), neurological (4·3%, 3115 of 73 197), and gastrointestinal or liver (0·8%, 7901 of 73 197) complications were also reported. INTERPRETATION: Complications and worse functional outcomes in patients admitted to hospital with COVID-19 are high, even in young, previously healthy individuals. Acute complications are associated with reduced ability to self-care at discharge, with neurological complications being associated with the worst functional outcomes. COVID-19 complications are likely to cause a substantial strain on health and social care in the coming years. These data will help in the design and provision of services aimed at the post-hospitalisation care of patients with COVID-19. FUNDING: National Institute for Health Research and the UK Medical Research Council.


Subject(s)
COVID-19/complications , Clinical Protocols/standards , Comorbidity , Hospital Mortality , Hospitalization , Age Factors , Aged , COVID-19/epidemiology , Cardiovascular Diseases , Female , Hospitals , Humans , Male , Nervous System Diseases , Prospective Studies , Respiratory Tract Diseases , SARS-CoV-2 , United Kingdom/epidemiology , World Health Organization
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