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1.
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.
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.

5.
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
6.
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
7.
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.

8.
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
9.
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.

10.
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
11.
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.

12.
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
13.
Elife ; 102021 06 29.
Article in English | MEDLINE | ID: covidwho-1287004

ABSTRACT

Background: Rapid identification and investigation of healthcare-associated infections (HCAIs) is important for suppression of SARS-CoV-2, but the infection source for hospital onset COVID-19 infections (HOCIs) cannot always be readily identified based only on epidemiological data. Viral sequencing data provides additional information regarding potential transmission clusters, but the low mutation rate of SARS-CoV-2 can make interpretation using standard phylogenetic methods difficult. Methods: We developed a novel statistical method and sequence reporting tool (SRT) that combines epidemiological and sequence data in order to provide a rapid assessment of the probability of HCAI among HOCI cases (defined as first positive test >48 hr following admission) and to identify infections that could plausibly constitute outbreak events. The method is designed for prospective use, but was validated using retrospective datasets from hospitals in Glasgow and Sheffield collected February-May 2020. Results: We analysed data from 326 HOCIs. Among HOCIs with time from admission ≥8 days, the SRT algorithm identified close sequence matches from the same ward for 160/244 (65.6%) and in the remainder 68/84 (81.0%) had at least one similar sequence elsewhere in the hospital, resulting in high estimated probabilities of within-ward and within-hospital transmission. For HOCIs with time from admission 3-7 days, the SRT probability of healthcare acquisition was >0.5 in 33/82 (40.2%). Conclusions: The methodology developed can provide rapid feedback on HOCIs that could be useful for infection prevention and control teams, and warrants further prospective evaluation. The integration of epidemiological and sequence data is important given the low mutation rate of SARS-CoV-2 and its variable incubation period. Funding: COG-UK HOCI funded by COG-UK consortium, supported by funding from UK Research and Innovation, National Institute of Health Research and Wellcome Sanger Institute.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , Cross Infection/diagnosis , Cross Infection/epidemiology , Disease Outbreaks/statistics & numerical data , Population Surveillance/methods , SARS-CoV-2/genetics , Genome, Viral , Hospitals/statistics & numerical data , Humans , Probability , Retrospective Studies , United Kingdom/epidemiology , Whole Genome Sequencing
14.
Lancet Microbe ; 2(8): e354-e365, 2021 08.
Article in English | MEDLINE | ID: covidwho-1253810

ABSTRACT

BACKGROUND: Microbiological characterisation of co-infections and secondary infections in patients with COVID-19 is lacking, and antimicrobial use is high. We aimed to describe microbiologically confirmed co-infections and secondary infections, and antimicrobial use, in patients admitted to hospital with COVID-19. METHODS: The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study is an ongoing, prospective cohort study recruiting inpatients from 260 hospitals in England, Scotland, and Wales, conducted by the ISARIC Coronavirus Clinical Characterisation Consortium. Patients with a confirmed or clinician-defined high likelihood of SARS-CoV-2 infection were eligible for inclusion in the ISARIC WHO CCP-UK study. For this specific study, we excluded patients with a recorded negative SARS-CoV-2 test result and those without a recorded outcome at 28 days after admission. Demographic, clinical, laboratory, therapeutic, and outcome data were collected using a prespecified case report form. Organisms considered clinically insignificant were excluded. FINDINGS: We analysed data from 48 902 patients admitted to hospital between Feb 6 and June 8, 2020. The median patient age was 74 years (IQR 59-84) and 20 786 (42·6%) of 48 765 patients were female. Microbiological investigations were recorded for 8649 (17·7%) of 48 902 patients, with clinically significant COVID-19-related respiratory or bloodstream culture results recorded for 1107 patients. 762 (70·6%) of 1080 infections were secondary, occurring more than 2 days after hospital admission. Staphylococcus aureus and Haemophilus influenzae were the most common pathogens causing respiratory co-infections (diagnosed ≤2 days after admission), with Enterobacteriaceae and S aureus most common in secondary respiratory infections. Bloodstream infections were most frequently caused by Escherichia coli and S aureus. Among patients with available data, 13 390 (37·0%) of 36 145 had received antimicrobials in the community for this illness episode before hospital admission and 39 258 (85·2%) of 46 061 patients with inpatient antimicrobial data received one or more antimicrobials at some point during their admission (highest for patients in critical care). We identified frequent use of broad-spectrum agents and use of carbapenems rather than carbapenem-sparing alternatives. INTERPRETATION: In patients admitted to hospital with COVID-19, microbiologically confirmed bacterial infections are rare, and more likely to be secondary infections. Gram-negative organisms and S aureus are the predominant pathogens. The frequency and nature of antimicrobial use are concerning, but tractable targets for stewardship interventions exist. FUNDING: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, UK Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, and NIHR HPRU in Respiratory Infections at Imperial College London.


Subject(s)
Anti-Infective Agents , COVID-19 , Coinfection , Respiratory Tract Infections , Aged , Aged, 80 and over , COVID-19/epidemiology , Coinfection/drug therapy , Female , Humans , Male , Middle Aged , Pandemics , Prospective Studies , Respiratory Tract Infections/epidemiology , SARS-CoV-2 , United Kingdom/epidemiology , World Health Organization
16.
J Clin Microbiol ; 59(6)2021 05 19.
Article in English | MEDLINE | ID: covidwho-1158099

ABSTRACT

LamPORE is a novel diagnostic platform for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA combining loop-mediated isothermal amplification with nanopore sequencing, which could potentially be used to analyze thousands of samples per day on a single instrument. We evaluated the performance of LamPORE against reverse transcriptase PCR (RT-PCR) using RNA extracted from spiked respiratory samples and stored nose and throat swabs collected at two UK hospitals. The limit of detection of LamPORE was 10 genome copies/µl of extracted RNA, which is above the limit achievable by RT-PCR, but was not associated with a significant reduction of sensitivity in clinical samples. Positive clinical specimens came mostly from patients with acute symptomatic infection, and among them, LamPORE had a diagnostic sensitivity of 99.1% (226/228; 95% confidence interval [CI], 96.9% to 99.9%). Among negative clinical specimens, including 153 with other respiratory pathogens detected, LamPORE had a diagnostic specificity of 99.6% (278/279; 98.0% to 100.0%). Overall, 1.4% (7/514; 0.5% to 2.9%) of samples produced an indeterminate result on first testing, and repeat LamPORE testing on the same RNA extract had a reproducibility of 96.8% (478/494; 94.8% to 98.1%). LamPORE has a similar performance as RT-PCR for the diagnosis of SARS-CoV-2 infection in symptomatic patients and offers a promising approach to high-throughput testing.


Subject(s)
COVID-19 , Nanopore Sequencing , Humans , Molecular Diagnostic Techniques , Nucleic Acid Amplification Techniques , RNA, Viral/genetics , Reproducibility of Results , SARS-CoV-2 , Sensitivity and Specificity
17.
Genome Res ; 31(4): 645-658, 2021 04.
Article in English | MEDLINE | ID: covidwho-1135943

ABSTRACT

We have developed periscope, a tool for the detection and quantification of subgenomic RNA (sgRNA) in SARS-CoV-2 genomic sequence data. The translation of the SARS-CoV-2 RNA genome for most open reading frames (ORFs) occurs via RNA intermediates termed "subgenomic RNAs." sgRNAs are produced through discontinuous transcription, which relies on homology between transcription regulatory sequences (TRS-B) upstream of the ORF start codons and that of the TRS-L, which is located in the 5' UTR. TRS-L is immediately preceded by a leader sequence. This leader sequence is therefore found at the 5' end of all sgRNA. We applied periscope to 1155 SARS-CoV-2 genomes from Sheffield, United Kingdom, and validated our findings using orthogonal data sets and in vitro cell systems. By using a simple local alignment to detect reads that contain the leader sequence, we were able to identify and quantify reads arising from canonical and noncanonical sgRNA. We were able to detect all canonical sgRNAs at the expected abundances, with the exception of ORF10. A number of recurrent noncanonical sgRNAs are detected. We show that the results are reproducible using technical replicates and determine the optimum number of reads for sgRNA analysis. In VeroE6 ACE2+/- cell lines, periscope can detect the changes in the kinetics of sgRNA in orthogonal sequencing data sets. Finally, variants found in genomic RNA are transmitted to sgRNAs with high fidelity in most cases. This tool can be applied to all sequenced COVID-19 samples worldwide to provide comprehensive analysis of SARS-CoV-2 sgRNA.


Subject(s)
Genome, Viral , RNA, Viral/genetics , SARS-CoV-2/genetics , Sequence Analysis, RNA/methods , Animals , Base Sequence , Chlorocebus aethiops , Humans , Limit of Detection , Vero Cells
18.
Int J Infect Dis ; 105: 579-587, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1126872

ABSTRACT

BACKGROUND: The progression and severity of COVID-19 vary significantly in the population. While the hallmarks of SARS-CoV-2 and severe COVID-19 within routine laboratory parameters are emerging, the impact of sex and age on these profiles is still unknown. METHODS: A multidimensional analysis was performed involving millions of records of laboratory parameters and diagnostic tests for 178 887 individuals from Brazil, of whom 33 266 tested positive for SARS-CoV-2. Analyzed data included those relating to complete blood cell count, electrolytes, metabolites, arterial blood gases, enzymes, hormones, cancer biomarkers, and others. FINDINGS: COVID-19 induced similar alterations in laboratory parameters in males and females. CRP and ferritin were increased, especially in older men with COVID-19, whereas abnormal liver function tests were common across several age groups, except for young women. Low peripheral blood basophils and eosinophils were more common in the elderly with COVID-19. Both male and female COVID-19 patients admitted to intensive care units displayed alterations in the coagulation system, and higher values for neutrophils, CRP, and lactate dehydrogenase. CONCLUSIONS: Our study uncovered the laboratory profiles of a large cohort of COVID-19 patients, which formed the basis of discrepancies influenced by aging and biological sex. These profiles directly linked COVID-19 disease presentation to an intricate interplay between sex, age, and immune activation.


Subject(s)
COVID-19/blood , Inflammation/etiology , SARS-CoV-2 , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , C-Reactive Protein/analysis , Female , Humans , Intensive Care Units , Male , Middle Aged , Sex Characteristics , Young Adult
19.
Cell ; 182(4): 812-827.e19, 2020 08 20.
Article in English | MEDLINE | ID: covidwho-628613

ABSTRACT

A SARS-CoV-2 variant carrying the Spike protein amino acid change D614G has become the most prevalent form in the global pandemic. Dynamic tracking of variant frequencies revealed a recurrent pattern of G614 increase at multiple geographic levels: national, regional, and municipal. The shift occurred even in local epidemics where the original D614 form was well established prior to introduction of the G614 variant. The consistency of this pattern was highly statistically significant, suggesting that the G614 variant may have a fitness advantage. We found that the G614 variant grows to a higher titer as pseudotyped virions. In infected individuals, G614 is associated with lower RT-PCR cycle thresholds, suggestive of higher upper respiratory tract viral loads, but not with increased disease severity. These findings illuminate changes important for a mechanistic understanding of the virus and support continuing surveillance of Spike mutations to aid with development of immunological interventions.


Subject(s)
Betacoronavirus/genetics , Betacoronavirus/pathogenicity , Coronavirus Infections/virology , Pneumonia, Viral/virology , Spike Glycoprotein, Coronavirus/genetics , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Epidemiological Monitoring , Genetic Fitness , Genetic Variation , Geographic Information Systems , Hospitalization , Humans , Pandemics , Phylogeny , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , Respiratory System/virology , SARS-CoV-2 , Severity of Illness Index , Viral Load
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