179 results on '"Volz, E"'
Search Results
2. The use of representative community samples to assess SARS-CoV-2 lineage competition: Alpha outcompetes Beta and wild-type in England from January to March 2021
- Author
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Eales, O, Page, AJ, Tang, SN, Walters, CE, Wang, H, Haw, D, Trotter, AJ, Le Viet, T, Foster-Nyarko, E, Prosolek, S, Atchison, C, Ashby, D, Cooke, G, Barclay, W, Donnelly, CA, O'Grady, J, Volz, E, The Covid-Genomics Uk Cog-Uk Consortium, Darzi, A, Ward, H, Elliott, P, and Riley, S
- Abstract
Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy and will be a high priority for public health for the foreseeable future. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained using a variety of methods all of which are known to contain biases. As a case study, using an approach which is largely free of biases, we here describe lineage dynamics and phylogenetic relationships of the Alpha and Beta variant in England during the first 3 months of 2021 using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR 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 Alpha variant (first identified in Kent) becoming predominant, driven by a reproduction number 0.3 higher than for the prior wild-type. During January, positive samples were more likely to be Alpha in those aged 18 to 54 years old. Although individuals infected with the Alpha variant 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. Further, viral load was higher in those infected with the Alpha variant as measured by cycle threshold (Ct) values. The presence of infections with non-imported Beta variant (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. These results highlight how sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance during periods of lineage diversity.
- Published
- 2023
3. The origins and molecular evolution of SARS-CoV-2 lineage B.1.1.7 in the UK (vol 8, veac080, 2022)
- Author
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Hill, V, Plessis, LD, Peacock, TP, Aggarwal, D, Colquhoun, R, Carabelli, AM, Ellaby, N, Gallagher, E, Groves, N, Jackson, B, McCrone, JT, O'Toole, A, Price, A, Sanderson, T, Scher, E, Southgate, J, Volz, E, Barclay, WS, Barrett, JC, Chand, M, Connor, T, Goodfellow, I, Gupta, RK, Harrison, EM, Loman, N, Myers, R, Robertson, DL, Pybus, OG, and Rambaut, A
- Published
- 2022
4. SARS-CoV-2 evolution during treatment of chronic infection
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Kemp, S. A., Collier, D. A., Datir, R. P., Ferreira, I. A. T. M., Gayed, S., Jahun, A., Hosmillo, M., Rees-Spear, C., Mlcochova, P., Lumb, I. U., Roberts, D. J., Chandra, A., Temperton, N., Baker, S., Dougan, G., Hess, C., Kingston, N., Lehner, P. J., Lyons, P. A., Matheson, N. J., Owehand, W. H., Saunders, C., Summers, C., Thaventhiran, J. E. D., Toshner, M., Weekes, M. P., Bucke, A., Calder, J., Canna, L., Domingo, J., Elmer, A., Fuller, S., Harris, J., Hewitt, S., Kennet, J., Jose, S., Kourampa, J., Meadows, A., O'Brien, C., Price, J., Publico, C., Rastall, R., Ribeiro, C., Rowlands, J., Ruffolo, V., Tordesillas, H., Bullman, B., Dunmore, B. J., Fawke, S., Graf, S., Hodgson, J., Huang, C., Hunter, K., Jones, E., Legchenko, E., Matara, C., Martin, J., Mescia, F., O'Donnell, C., Pointon, L., Pond, N., Shih, J., Sutcliffe, R., Tilly, T., Treacy, C., Tong, Z., Wood, J., Wylot, M., Bergamaschi, L., Betancourt, A., Bower, G., Cossetti, C., De Sa, A., Epping, M., Gleadall, N., Grenfell, R., Hinch, A., Huhn, O., Jackson, S., Jarvis, I., Lewis, D., Marsden, J., Nice, F., Okecha, G., Omarjee, O., Perera, M., Richoz, N., Romashova, V., Yarkoni, N. S., Sharma, R., Stefanucci, L., Stephens, J., Strezlecki, M., Turner, L., De Bie, E. M. D. D., Bunclark, K., Josipovic, M., Mackay, M., Rossi, S., Selvan, M., Spencer, S., Yong, C., Ansaripour, A., Michael, A., Mwaura, L., Patterson, C., Polwarth, G., Polgarova, P., di Stefano, G., Fahey, C., Michel, R., Bong, S. -H., Coudert, J. D., Holmes, E., Allison, J., Butcher, H., Caputo, D., Clapham-Riley, D., Dewhurst, E., Furlong, A., Graves, B., Gray, J., Ivers, T., Kasanicki, M., Le Gresley, E., Linger, R., Meloy, S., Muldoon, F., Ovington, N., Papadia, S., Phelan, I., Stark, H., Stirrups, K. E., Townsend, P., Walker, N., Webster, J., Robson, S. C., Loman, N. J., Connor, T. R., Golubchik, T., Martinez Nunez, R. T., Ludden, C., Corden, S., Johnston, I., Bonsall, D., Smith, C. P., Awan, A. R., Bucca, G., Estee Torok, M., Saeed, K., Prieto, J. A., Jackson, D. K., Hamilton, W. L., Snell, L. B., Moore, C., Harrison, E. M., Goncalves, S., Fairley, D. J., Loose, M. W., Watkins, J., Livett, R., Moses, S., Amato, R., Nicholls, S., Bull, M., Smith, D. L., Barrett, J., Aanensen, D. M., Curran, M. D., Parmar, S., Aggarwal, D., Shepherd, J. G., Parker, M. D., Glaysher, S., Bashton, M., Underwood, A. P., Pacchiarini, N., Loveson, K. F., Carabelli, A. M., Templeton, K. E., Langford, C. F., Sillitoe, J., de Silva, T. I., Wang, D., Kwiatkowski, D., Rambaut, A., O'Grady, J., Cottrell, S., Holden, M. T. G., Thomson, E. C., Osman, H., Andersson, M., Chauhan, A. J., Hassan-Ibrahim, M. O., Lawniczak, M., Alderton, A., Chand, M., Constantinidou, C., Unnikrishnan, M., Darby, A. C., Hiscox, J. A., Paterson, S., Martincorena, I., Robertson, D. L., Volz, E. M., Page, A. J., Pybus, O. G., Bassett, A. R., Ariani, C. V., Spencer Chapman, M. H., K. K., Li, Shah, R. N., Jesudason, N. G., Taha, Y., Mchugh, M. P., Dewar, R., Jahun, A. S., Mcmurray, C., Pandey, S., Mckenna, J. P., Nelson, A., Young, G. R., Mccann, C. M., Elliott, S., Lowe, H., Temperton, B., Roy, S., Price, A., Rey, S., Wyles, M., Rooke, S., Shaaban, S., de Cesare, M., Letchford, L., Silveira, S., Pelosi, E., Wilson-Davies, E., O'Toole, A., Hesketh, A. R., Stark, R., du Plessis, L., Ruis, C., Adams, H., Bourgeois, Y., Michell, S. L., Gramatopoulos, D., Edgeworth, J., Breuer, J., Todd, J. A., Fraser, C., Buck, D., John, M., Kay, G. L., Palmer, S., Peacock, S. J., Heyburn, D., Weldon, D., Robinson, E., Mcnally, A., Muir, P., Vipond, I. B., Boyes, J., Sivaprakasam, V., Salluja, T., Dervisevic, S., Meader, E. J., Park, N. R., Oliver, K., Jeffries, A. R., Ott, S., da Silva Filipe, A., Simpson, D. A., Williams, C., Masoli, J. A. H., Knight, B. A., Jones, C. R., Koshy, C., Ash, A., Casey, A., Bosworth, A., Ratcliffe, L., Xu-McCrae, L., Pymont, H. M., Hutchings, S., Berry, L., Jones, K., Halstead, F., Davis, T., Holmes, C., Iturriza-Gomara, M., Lucaci, A. O., Randell, P. A., Cox, A., Madona, P., Harris, K. A., Brown, J. R., Mahungu, T. W., Irish-Tavares, D., Haque, T., Hart, J., Witele, E., Fenton, M. L., Liggett, S., Graham, C., Swindells, E., Collins, J., Eltringham, G., Campbell, S., Mcclure, P. C., Clark, G., Sloan, T. J., Jones, C., Lynch, J., Warne, B., Leonard, S., Durham, J., Williams, T., Haldenby, S. T., Storey, N., Alikhan, N. -F., Holmes, N., Carlile, M., Perry, M., Craine, N., Lyons, R. A., Beckett, A. H., Goudarzi, S., Fearn, C., Cook, K., Dent, H., Paul, H., Davies, R., Blane, B., Girgis, S. T., Beale, M. A., Bellis, K. L., Dorman, M. J., Drury, E., Kane, L., Kay, S., Mcguigan, S., Nelson, R., Prestwood, L., Rajatileka, S., Batra, R., Williams, R. J., Kristiansen, M., Green, A., Justice, A., Mahanama, A. I. K., Samaraweera, B., Hadjirin, N. F., Quick, J., Poplawski, R., Kermack, L. M., Reynolds, N., Hall, G., Chaudhry, Y., Pinckert, M. L., Georgana, I., Moll, R. J., Thornton, A., Myers, R., Stockton, J., Williams, C. A., Yew, W. C., Trotter, A. J., Trebes, A., MacIntyre-Cockett, G., Birchley, A., Adams, A., Plimmer, A., Gatica-Wilcox, B., Mckerr, C., Hilvers, E., Jones, H., Asad, H., Coombes, J., Evans, J. M., Fina, L., Gilbert, L., Graham, L., Cronin, M., Kumziene-Summerhayes, S., Taylor, S., Jones, S., Groves, D. C., Zhang, P., Gallis, M., Louka, S. F., Starinskij, I., Jackson, C., Gourtovaia, M., Tonkin-Hill, G., Lewis, K., Tovar-Corona, J. M., James, K., Baxter, L., Alam, M. T., Orton, R. J., Hughes, J., Vattipally, S., Ragonnet-Cronin, M., Nascimento, F. F., Jorgensen, D., Boyd, O., Geidelberg, L., Zarebski, A. E., Raghwani, J., Kraemer, M. U. G., Southgate, J., Lindsey, B. B., Freeman, T. M., Keatley, J. -P., Singer, J. B., de Oliveira Martins, L., Yeats, C. A., Abudahab, K., Taylor, B. E. W., Menegazzo, M., Danesh, J., Hogsden, W., Eldirdiri, S., Kenyon, A., Mason, J., Robinson, T. I., Holmes, A., Hartley, J. A., Curran, T., Mather, A. E., Shankar, G., Jones, R., Howe, R., Morgan, S., Wastenge, E., Chapman, M. R., Mookerjee, S., Stanley, R., Smith, W., Peto, T., Eyre, D., Crook, D., Vernet, G., Kitchen, C., Gulliver, H., Merrick, I., Guest, M., Munn, R., Bradley, D. T., Wyatt, T., Beaver, C., Foulser, L., Churcher, C. M., Brooks, E., Smith, K. S., Galai, K., Mcmanus, G. M., Bolt, F., Coll, F., Meadows, L., Attwood, S. W., Davies, A., De Lacy, E., Downing, F., Edwards, S., Scarlett, G. P., Jeremiah, S., Smith, N., Leek, D., Sridhar, S., Forrest, S., Cormie, C., Gill, H. K., Dias, J., Higginson, E. E., Maes, M., Young, J., Wantoch, M., Jamrozy, D., Lo, S., Patel, M., Hill, V., Bewshea, C. M., Ellard, S., Auckland, C., Harrison, I., Bishop, C., Chalker, V., Richter, A., Beggs, A., Best, A., Percival, B., Mirza, J., Megram, O., Mayhew, M., Crawford, L., Ashcroft, F., Moles-Garcia, E., Cumley, N., Hopes, R., Asamaphan, P., Niebel, M. O., Gunson, R. N., Bradley, A., Maclean, A., Mollett, G., Blacow, R., Bird, P., Helmer, T., Fallon, K., Tang, J., Hale, A. D., Macfarlane-Smith, L. R., Harper, K. L., Carden, H., Machin, N. W., Jackson, K. A., Ahmad, S. S. Y., George, R. P., Turtle, L., O'Toole, E., Watts, J., Breen, C., Cowell, A., Alcolea-Medina, A., Charalampous, T., Patel, A., Levett, L. J., Heaney, J., Rowan, A., Taylor, G. P., Shah, D., Atkinson, L., Lee, J. C. D., Westhorpe, A. P., Jannoo, R., Lowe, H. L., Karamani, A., Ensell, L., Chatterton, W., Pusok, M., Dadrah, A., Symmonds, A., Sluga, G., Molnar, Z., Baker, P., Bonner, S., Essex, S., Barton, E., Padgett, D., Scott, G., Greenaway, J., Payne, B. A. I., Burton-Fanning, S., Waugh, S., Raviprakash, V., Sheriff, N., Blakey, V., Williams, L. -A., Moore, J., Stonehouse, S., Smith, L., Davidson, R. K., Bedford, L., Coupland, L., Wright, V., Chappell, J. G., Tsoleridis, T., Ball, J., Khakh, M., Fleming, V. M., Lister, M. M., Howson-Wells, H. C., Boswell, T., Joseph, A., Willingham, I., Duckworth, N., Walsh, S., Wise, E., Moore, N., Mori, M., Cortes, N., Kidd, S., Williams, R., Gifford, L., Bicknell, K., Wyllie, S., Lloyd, A., Impey, R., Malone, C. S., Cogger, B. J., Levene, N., Monaghan, L., Keeley, A. J., Partridge, D. G., Raza, M., Evans, C., Johnson, K., Abnizova, I., Aigrain, L., Ali, M., Allen, L., Anderson, R., Ariani, C., Austin-Guest, S., Bala, S., Bassett, A., Battleday, K., Beal, J., Beale, M., Bellany, S., Bellerby, T., Bellis, K., Berger, D., Berriman, M., Betteridge, E., Bevan, P., Binley, S., Bishop, J., Blackburn, K., Bonfield, J., Boughton, N., Bowker, S., Brendler-Spaeth, T., Bronner, I., Brooklyn, T., Buddenborg, S. K., Bush, R., Caetano, C., Cagan, A., Carter, N., Cartwright, J., Monteiro, T. C., Chapman, L., Chillingworth, T. -J., Clapham, P., Clark, R., Clarke, A., Clarke, C., Cole, D., Cook, E., Coppola, M., Cornell, L., Cornwell, C., Corton, C., Crackett, A., Cranage, A., Craven, H., Craw, S., Crawford, M., Cutts, T., Dabrowska, M., Davies, M., Dawson, J., Day, C., Densem, A., Dibling, T., Dockree, C., Dodd, D., Dogga, S., Dougherty, M., Dove, A., Drummond, L., Dudek, M., Durrant, L., Easthope, E., Eckert, S., Ellis, P., Farr, B., Fenton, M., Ferrero, M., Flack, N., Fordham, H., Forsythe, G., Francis, M., Fraser, A., Freeman, A., Galvin, A., Garcia-Casado, M., Gedny, A., Girgis, S., Glover, J., Goodwin, S., Gould, O., Gray, A., Gray, E., Griffiths, C., Gu, Y., Guerin, F., Hamilton, W., Hanks, H., Harrison, E., Harrott, A., Harry, E., Harvison, J., Heath, P., Hernandez-Koutoucheva, A., Hobbs, R., Holland, D., Holmes, S., Hornett, G., Hough, N., Huckle, L., Hughes-Hallet, L., Hunter, A., Inglis, S., Iqbal, S., Jackson, A., Jackson, D., Verdejo, C. J., Jones, M., Kallepally, K., Kay, K., Keatley, J., Keith, A., King, A., Kitchin, L., Kleanthous, M., Klimekova, M., Korlevic, P., Krasheninnkova, K., Lane, G., Langford, C., Laverack, A., Law, K., Lensing, S., Lewis-Wade, A., Liddle, J., Lin, Q., Lindsay, S., Linsdell, S., Long, R., Lovell, J., Mack, J., Maddison, M., Makunin, A., Mamun, I., Mansfield, J., Marriott, N., Martin, M., Mayho, M., Mccarthy, S., Mcclintock, J., Mchugh, S., Mcminn, L., Meadows, C., Mobley, E., Moll, R., Morra, M., Morrow, L., Murie, K., Nash, S., Nathwani, C., Naydenova, P., Neaverson, A., Nerou, E., Nicholson, J., Nimz, T., Noell, G. G., O'Meara, S., Ohan, V., Olney, C., Ormond, D., Oszlanczi, A., Pang, Y. F., Pardubska, B., Park, N., Parmar, A., Patel, G., Payne, M., Peacock, S., Petersen, A., Plowman, D., Preston, T., Puethe, C., Quail, M., Rajan, D., Rance, R., Rawlings, S., Redshaw, N., Reynolds, J., Reynolds, M., Rice, S., Richardson, M., Roberts, C., Robinson, K., Robinson, M., Robinson, D., Rogers, H., Rojo, E. M., Roopra, D., Rose, M., Rudd, L., Sadri, R., Salmon, N., Saul, D., Schwach, F., Scott, C., Seekings, P., Shirley, L., Simms, A., Sinnott, M., Sivadasan, S., Siwek, B., Sizer, D., Skeldon, K., Skelton, J., Slater-Tunstill, J., Sloper, L., Smerdon, N., Smith, C., Smith, J., Smith, K., Smith, M., Smith, S., Smith, T., Sneade, L., Soria, C. D., Sousa, C., Souster, E., Sparkes, A., Spencer-Chapman, M., Squares, J., Steed, C., Stickland, T., Still, I., Stratton, M., Strickland, M., Swann, A., Swiatkowska, A., Sycamore, N., Swift, E., Symons, E., Szluha, S., Taluy, E., Tao, N., Taylor, K., Thompson, S., Thompson, M., Thomson, M., Thomson, N., Thurston, S., Toombs, D., Topping, B., Tovar-Corona, J., Ungureanu, D., Uphill, J., Urbanova, J., Jansen Van, P., Vancollie, V., Voak, P., Walker, D., Walker, M., Waller, M., Ward, G., Weatherhogg, C., Webb, N., Wells, A., Wells, E., Westwood, L., Whipp, T., Whiteley, T., Whitton, G., Whitwham, A., Widaa, S., Williams, M., Wilson, M., Wright, S., Farr, B. W., Quail, M. A., Thurston, S. A. J., Bronner, I. F., Redshaw, N. M., Lensing, S. V., Balcazar, C. E., Gallagher, M. D., Williamson, K. A., Stanton, T. D., Michelsen, M. L., Warwick-Dugdale, J., Manley, R., Farbos, A., Harrison, J. W., Sambles, C. M., Studholme, D. J., Lackenby, A., Mbisa, T., Platt, S., Miah, S., Bibby, D., Manso, C., Hubb, J., Dabrera, G., Ramsay, M., Bradshaw, D., Schaefer, U., Groves, N., Gallagher, E., Lee, D., Williams, D., Ellaby, N., Hartman, H., Manesis, N., Patel, V., Ledesma, J., Twohig, K. A., Allara, E., Pearson, C., Cheng, J. K. J., Bridgewater, H. E., Frost, L. R., Taylor-Joyce, G., Brown, P. E., Tong, L., Broos, A., Mair, D., Nichols, J., Carmichael, S. N., Smollett, K. L., Nomikou, K., Aranday-Cortes, E., Johnson, N., Nickbakhsh, S., Vamos, E. E., Hughes, M., Rainbow, L., Eccles, R., Nelson, C., Whitehead, M., Gregory, R., Gemmell, M., Wierzbicki, C., Webster, H. J., Fisher, C. L., Signell, A. W., Betancor, G., Wilson, H. D., Nebbia, G., Flaviani, F., Cerda, A. C., Merrill, T. V., Wilson, R. E., Cotic, M., Bayzid, N., Thompson, T., Acheson, E., Rushton, S., O'Brien, S., Baker, D. J., Rudder, S., Aydin, A., Sang, F., Debebe, J., Francois, S., Vasylyeva, T. I., Zamudio, M. E., Gutierrez, B., Marchbank, A., Maksimovic, J., Spellman, K., Mccluggage, K., Morgan, M., Beer, R., Afifi, S., Workman, T., Fuller, W., Bresner, C., Angyal, A., Green, L. R., Parsons, P. J., Tucker, R. M., Brown, R., Whiteley, M., Rowe, W., Siveroni, I., Le-Viet, T., Gaskin, A., Johnson, R., Sharrocks, K., Blane, E., Modis, Y., Leigh, K. E., Briggs, J. A. G., van Gils, M. J., Smith, K. G. C., Bradley, J. R., Doffinger, R., Ceron-Gutierrez, L., Barcenas-Morales, G., Pollock, D. D., Goldstein, R. A., Smielewska, A., Skittrall, J. P., Gouliouris, T., Goodfellow, I. G., Gkrania-Klotsas, E., Illingworth, C. J. R., Mccoy, L. E., Gupta, R. K., Medical Microbiology and Infection Prevention, AII - Infectious diseases, Collier, Dami A [0000-0001-5446-4423], Jahun, Aminu [0000-0002-4585-1701], Temperton, Nigel [0000-0002-7978-3815], Modis, Yorgo [0000-0002-6084-0429], Briggs, John AG [0000-0003-3990-6910], Goldstein, Richard A [0000-0001-5148-4672], Skittrall, Jordan P [0000-0002-8228-3758], Gkrania-Klotsas, Effrossyni [0000-0002-0930-8330], McCoy, Laura E [0000-0001-9503-7946], Gupta, Ravindra K [0000-0001-9751-1808], and Apollo - University of Cambridge Repository
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0301 basic medicine ,Male ,Time Factors ,viruses ,Passive ,Antibodies, Viral ,CITIID-NIHR BioResource COVID-19 Collaboration ,2.1 Biological and endogenous factors ,Viral ,Aetiology ,Neutralizing ,Lung ,Phylogeny ,neutralising antibodies ,Infectivity ,education.field_of_study ,Genome ,Multidisciplinary ,Alanine ,biology ,High-Throughput Nucleotide Sequencing ,Viral Load ,Spike Glycoprotein ,Virus Shedding ,Adenosine Monophosphate ,Aged ,Antibodies, Neutralizing ,COVID-19 ,Chronic Disease ,Genome, Viral ,Humans ,Immune Evasion ,Immune Tolerance ,Immunization, Passive ,Immunosuppression Therapy ,Mutagenesis ,Mutant Proteins ,Mutation ,SARS-CoV-2 ,Spike Glycoprotein, Coronavirus ,Evolution, Molecular ,Infectious Diseases ,Pneumonia & Influenza ,Antibody ,Infection ,Viral load ,Biotechnology ,Evolution ,General Science & Technology ,antibody escape, Convalescent plasma ,030106 microbiology ,Population ,evasion ,Antibodies ,Virus ,Article ,Vaccine Related ,resistance ,03 medical and health sciences ,Immune system ,COVID-19 Genomics UK (COG-UK) Consortium ,Biodefense ,Genetics ,Viral shedding ,education ,COVID-19 Serotherapy ,QR355 ,Prevention ,Wild type ,Molecular ,Pneumonia ,Virology ,COVID-19 Drug Treatment ,Coronavirus ,Emerging Infectious Diseases ,Good Health and Well Being ,030104 developmental biology ,biology.protein ,Immunization ,immune suppression ,mutation - Abstract
The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical for virus infection through the engagement of the human ACE2 protein1 and is a major antibody target. Here we show that chronic infection with SARS-CoV-2 leads to viral evolution and reduced sensitivity to neutralizing antibodies in an immunosuppressed individual treated with convalescent plasma, by generating whole-genome ultra-deep sequences for 23 time points that span 101 days and using in vitro techniques to characterize the mutations revealed by sequencing. There was little change in the overall structure of the viral population after two courses of remdesivir during the first 57 days. However, after convalescent plasma therapy, we observed large, dynamic shifts in the viral population, with the emergence of a dominant viral strain that contained a substitution (D796H) in the S2 subunit and a deletion (ΔH69/ΔV70) in the S1 N-terminal domain of the spike protein. As passively transferred serum antibodies diminished, viruses with the escape genotype were reduced in frequency, before returning during a final, unsuccessful course of convalescent plasma treatment. In vitro, the spike double mutant bearing both ΔH69/ΔV70 and D796H conferred modestly decreased sensitivity to convalescent plasma, while maintaining infectivity levels that were similar to the wild-type virus.The spike substitution mutant D796H appeared to be the main contributor to the decreased susceptibility to neutralizing antibodies, but this mutation resulted in an infectivity defect. The spike deletion mutant ΔH69/ΔV70 had a twofold higher level of infectivity than wild-type SARS-CoV-2, possibly compensating for the reduced infectivity of the D796H mutation. These data reveal strong selection on SARS-CoV-2 during convalescent plasma therapy, which is associated with the emergence of viral variants that show evidence of reduced susceptibility to neutralizing antibodies in immunosuppressed individuals.
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- 2021
5. Report 51: Evidence for age dependence in the severity of the Omicron SARS-CoV variant of concern relative to the Delta variant
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Ferguson, N, Ghani, A, Hinsley, W, and Volz, E
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Coronavirus ,COVID19 ,Omicron ,SARS-CoV-2 ,COVID-19 - Published
- 2022
- Full Text
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6. Genomic reconstruction of the SARS-CoV-2 epidemic in England
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Vöhringer, HS, Sanderson, T, Sinnott, M, De Maio, N, Nguyen, T, Goater, R, Schwach, F, Harrison, I, Hellewell, J, Ariani, CV, Gonçalves, S, Jackson, DK, Johnston, I, Jung, AW, Saint, C, Sillitoe, J, Suciu, M, Goldman, N, Panovska-Griffiths, J, Abnizova, I, Aigrain, L, Alderton, A, Ali, M, Allen, L, Amato, R, Anderson, R, Ariani, C, Austin-Guest, S, Bala, S, Barrett, J, Bassett, A, Battleday, K, Beal, J, Beale, M, Beaver, C, Bellany, S, Bellerby, T, Bellis, K, Berger, D, Berriman, M, Betteridge, E, Bevan, P, Binley, S, Bishop, J, Blackburn, K, Bonfield, J, Boughton, N, Bowker, S, Brendler-Spaeth, T, Bronner, I, Brooklyn, T, Buddenborg, SK, Bush, R, Caetano, C, Cagan, A, Carter, N, Cartwright, J, Monteiro, TC, Chapman, L, Chillingworth, T-J, Clapham, P, Clark, R, Clarke, A, Clarke, C, Cole, D, Cook, E, Coppola, M, Cornell, L, Cornwell, C, Corton, C, Crackett, A, Cranage, A, Craven, H, Craw, S, Crawford, M, Cutts, T, Dabrowska, M, Davies, M, Davies, R, Dawson, J, Day, C, Densem, A, Dibling, T, Dockree, C, Dodd, D, Dogga, S, Dorman, M, Dougan, G, Dougherty, M, Dove, A, Drummond, L, Drury, E, Dudek, M, Durham, J, Durrant, L, Easthope, E, Eckert, S, Ellis, P, Farr, B, Fenton, M, Ferrero, M, Flack, N, Fordham, H, Forsythe, G, Foulser, L, Francis, M, Fraser, A, Freeman, A, Galvin, A, Garcia-Casado, M, Gedny, A, Girgis, S, Glover, J, Goncalves, S, Goodwin, S, Gould, O, Gourtovaia, M, Gray, A, Gray, E, Griffiths, C, Gu, Y, Guerin, F, Hamilton, W, Hanks, H, Harrison, E, Harrott, A, Harry, E, Harvison, J, Heath, P, Hernandez-Koutoucheva, A, Hobbs, R, Holland, D, Holmes, S, Hornett, G, Hough, N, Huckle, L, Hughes-Hallet, L, Hunter, A, Inglis, S, Iqbal, S, Jackson, A, Jackson, D, James, K, Jamrozy, D, Verdejo, CJ, Jones, M, Kallepally, K, Kane, L, Kay, K, Kay, S, Keatley, J, Keith, A, King, A, Kitchin, L, Kleanthous, M, Klimekova, M, Korlevic, P, Krasheninnkova, K, Lane, G, Langford, C, Laverack, A, Law, K, Lawniczak, M, Lensing, S, Leonard, S, Letchford, L, Lewis, K, Lewis-Wade, A, Liddle, J, Lin, Q, Lindsay, S, Linsdell, S, Livett, R, Lo, S, Long, R, Lovell, J, Ludden, C, Mack, J, Maddison, M, Makunin, A, Mamun, I, Mansfield, J, Marriott, N, Martin, M, Mayho, M, McCarthy, S, McClintock, J, McGuigan, S, McHugh, S, McMinn, L, Meadows, C, Mobley, E, Moll, R, Morra, M, Morrow, L, Murie, K, Nash, S, Nathwani, C, Naydenova, P, Neaverson, A, Nelson, R, Nerou, E, Nicholson, J, Nimz, T, Noell, GG, O’Meara, S, Ohan, V, Oliver, K, Olney, C, Ormond, D, Oszlanczi, A, Palmer, S, Pang, YF, Pardubska, B, Park, N, Parmar, A, Patel, G, Patel, M, Payne, M, Peacock, S, Petersen, A, Plowman, D, Preston, T, Prestwood, L, Puethe, C, Quail, M, Rajan, D, Rajatileka, S, Rance, R, Rawlings, S, Redshaw, N, Reynolds, J, Reynolds, M, Rice, S, Richardson, M, Roberts, C, Robinson, K, Robinson, M, Robinson, D, Rogers, H, Rojo, EM, Roopra, D, Rose, M, Rudd, L, Sadri, R, Salmon, N, Saul, D, Scott, C, Seekings, P, Shirley, L, Simms, A, Sivadasan, S, Siwek, B, Sizer, D, Skeldon, K, Skelton, J, Slater-Tunstill, J, Sloper, L, Smerdon, N, Smith, C, Smith, J, Smith, K, Smith, M, Smith, S, Smith, T, Sneade, L, Soria, CD, Sousa, C, Souster, E, Sparkes, A, Spencer-Chapman, M, Squares, J, Stanley, R, Steed, C, Stickland, T, Still, I, Stratton, MR, Strickland, M, Swann, A, Swiatkowska, A, Sycamore, N, Swift, E, Symons, E, Szluha, S, Taluy, E, Tao, N, Taylor, K, Taylor, S, Thompson, S, Thompson, M, Thomson, M, Thomson, N, Thurston, S, Tonkin-Hill, G, Toombs, D, Topping, B, Tovar-Corona, J, Ungureanu, D, Uphill, J, Urbanova, J, Van Vuuren, PJ, Vancollie, V, Voak, P, Walker, D, Walker, M, Waller, M, Ward, G, Weatherhogg, C, Webb, N, Weldon, D, Wells, A, Wells, E, Westwood, L, Whipp, T, Whiteley, T, Whitton, G, Whitwham, A, Widaa, S, Williams, M, Wilson, M, Wright, S, Robson, SC, Connor, TR, Loman, NJ, Golubchik, T, Martinez Nunez, RT, Bonsall, D, Rambaut, A, Snell, LB, Corden, S, Nastouli, E, Nebbia, G, Lythgoe, K, Torok, ME, Goodfellow, IG, Prieto, JA, Saeed, K, Houlihan, C, Frampton, D, Hamilton, WL, Witney, AA, Bucca, G, Pope, CF, Moore, C, Thomson, EC, Harrison, EM, Smith, CP, Rogan, F, Beckwith, SM, Murray, A, Singleton, D, Eastick, K, Sheridan, LA, Randell, P, Jackson, LM, Fairley, DJ, Loose, MW, Watkins, J, Moses, S, Nicholls, S, Bull, M, Smith, DL, Aanensen, DM, Aggarwal, D, Shepherd, JG, Curran, MD, Parmar, S, Parker, MD, Williams, C, Glaysher, S, Underwood, AP, Bashton, M, Pacchiarini, N, Loveson, KF, Byott, M, Carabelli, AM, Templeton, KE, de Silva, TI, Wang, D, Langford, CF, Gunson, RN, Cottrell, S, O’Grady, J, Kwiatkowski, D, Lillie, PJ, Cortes, N, Moore, N, Thomas, C, Burns, PJ, Mahungu, TW, Liggett, S, Beckett, AH, Holden, MTG, Levett, LJ, Osman, H, Hassan-Ibrahim, MO, Simpson, DA, Chand, M, Gupta, RK, Darby, AC, Paterson, S, Pybus, OG, Volz, EM, de Angelis, D, Robertson, DL, Page, AJ, Bassett, AR, Wong, N, Taha, Y, Erkiert, MJ, Spencer Chapman, MH, Dewar, R, McHugh, MP, Mookerjee, S, Aplin, S, Harvey, M, Sass, T, Umpleby, H, Wheeler, H, McKenna, JP, Warne, B, Taylor, JF, Chaudhry, Y, Izuagbe, R, Jahun, AS, Young, GR, McMurray, C, McCann, CM, Nelson, A, Elliott, S, Lowe, H, Price, A, Crown, MR, Rey, S, Roy, S, Temperton, B, Shaaban, S, Hesketh, AR, Laing, KG, Monahan, IM, Heaney, J, Pelosi, E, Silviera, S, Wilson-Davies, E, Fryer, H, Adams, H, du Plessis, L, Johnson, R, Harvey, WT, Hughes, J, Orton, RJ, Spurgin, LG, Bourgeois, Y, Ruis, C, O’Toole, Á, Fraser, C, Edgeworth, J, Breuer, J, Michell, SL, Todd, JA, John, M, Buck, D, Gajee, K, Kay, GL, Peacock, SJ, Heyburn, D, Kitchman, K, McNally, A, Pritchard, DT, Dervisevic, S, Muir, P, Robinson, E, Vipond, BB, Ramadan, NA, Jeanes, C, Catalan, J, Jones, N, da Silva Filipe, A, Fuchs, M, Miskelly, J, Jeffries, AR, Park, NR, Ash, A, Koshy, C, Barrow, M, Buchan, SL, Mantzouratou, A, Clark, G, Holmes, CW, Campbell, S, Davis, T, Tan, NK, Brown, JR, Harris, KA, Kidd, SP, Grant, PR, Xu-McCrae, L, Cox, A, Madona, P, Pond, M, Randell, PA, Withell, KT, Graham, C, Denton-Smith, R, Swindells, E, Turnbull, R, Sloan, TJ, Bosworth, A, Hutchings, S, Pymont, HM, Casey, A, Ratcliffe, L, Jones, CR, Knight, BA, Haque, T, Hart, J, Irish-Tavares, D, Witele, E, Mower, C, Watson, LK, Collins, J, Eltringham, G, Crudgington, D, Macklin, B, Iturriza-Gomara, M, Lucaci, AO, McClure, PC, Carlile, M, Holmes, N, Storey, N, Rooke, S, Yebra, G, Craine, N, Perry, M, Alikhan, N-F, Bridgett, S, Cook, KF, Fearn, C, Goudarzi, S, Lyons, RA, Williams, T, Haldenby, ST, Davies, RM, Batra, R, Blane, B, Spyer, MJ, Smith, P, Yavus, M, Williams, RJ, Mahanama, AIK, Samaraweera, B, Girgis, ST, Hansford, SE, Green, A, Bellis, KL, Dorman, MJ, Quick, J, Poplawski, R, Reynolds, N, Mack, A, Morriss, A, Whalley, T, Patel, B, Georgana, I, Hosmillo, M, Pinckert, ML, Stockton, J, Henderson, JH, Hollis, A, Stanley, W, Yew, WC, Myers, R, Thornton, A, Adams, A, Annett, T, Asad, H, Birchley, A, Coombes, J, Evans, JM, Fina, L, Gatica-Wilcox, B, Gilbert, L, Graham, L, Hey, J, Hilvers, E, Jones, S, Jones, H, Kumziene-Summerhayes, S, McKerr, C, Powell, J, Pugh, G, Trotter, AJ, Williams, CA, Kermack, LM, Foulkes, BH, Gallis, M, Hornsby, HR, Louka, SF, Pohare, M, Wolverson, P, Zhang, P, MacIntyre-Cockett, G, Trebes, A, Moll, RJ, Ferguson, L, Goldstein, EJ, Maclean, A, Tomb, R, Starinskij, I, Thomson, L, Southgate, J, Kraemer, MUG, Raghwani, J, Zarebski, AE, Boyd, O, Geidelberg, L, Illingworth, CJ, Jackson, C, Pascall, D, Vattipally, S, Freeman, TM, Hsu, SN, Lindsey, BB, Tovar-Corona, JM, Cox, M, Abudahab, K, Menegazzo, M, Taylor, BEW, Yeats, CA, Mukaddas, A, Wright, DW, de Oliveira Martins, L, Colquhoun, R, Hill, V, Jackson, B, McCrone, JT, Medd, N, Scher, E, Keatley, J-P, Curran, T, Morgan, S, Maxwell, P, Eldirdiri, S, Kenyon, A, Holmes, AH, Price, JR, Wyatt, T, Mather, AE, Skvortsov, T, Hartley, JA, Guest, M, Kitchen, C, Merrick, I, Munn, R, Bertolusso, B, Lynch, J, Vernet, G, Kirk, S, Wastnedge, E, Idle, G, Bradley, DT, Poyner, J, Mori, M, Jones, O, Wright, V, Brooks, E, Churcher, CM, Fragakis, M, Galai, K, Jermy, A, Judges, S, McManus, GM, Smith, KS, Westwick, E, Attwood, SW, Bolt, F, Davies, A, De Lacy, E, Downing, F, Edwards, S, Meadows, L, Jeremiah, S, Smith, N, Charalampous, T, Patel, A, Berry, L, Boswell, T, Fleming, VM, Howson-Wells, HC, Joseph, A, Khakh, M, Lister, MM, Bird, PW, Fallon, K, Helmer, T, McMurray, CL, Odedra, M, Shaw, J, Tang, JW, Willford, NJ, Blakey, V, Raviprakash, V, Sheriff, N, Williams, L-A, Feltwell, T, Bedford, L, Cargill, JS, Hughes, W, Moore, J, Stonehouse, S, Atkinson, L, Lee, JCD, Shah, D, Alcolea, A, Ohemeng-Kumi, N, Ramble, J, Sehmi, J, Williams, R, Chatterton, W, Pusok, M, Everson, W, Castigador, A, Macnaughton, E, El Bouzidi, K, Lampejo, T, Sudhanva, M, Breen, C, Sluga, G, Ahmad, SSY, George, RP, Machin, NW, Binns, D, James, V, Blacow, R, Coupland, L, Smith, L, Barton, E, Padgett, D, Scott, G, Cross, A, Mirfenderesky, M, Greenaway, J, Cole, K, Clarke, P, Duckworth, N, Walsh, S, Bicknell, K, Impey, R, Wyllie, S, Hopes, R, Bishop, C, Chalker, V, Gifford, L, Molnar, Z, Auckland, C, Evans, C, Johnson, K, Partridge, DG, Raza, M, Baker, P, Bonner, S, Essex, S, Murray, LJ, Lawton, AI, Burton-Fanning, S, Payne, BAI, Waugh, S, Gomes, AN, Kimuli, M, Murray, DR, Ashfield, P, Dobie, D, Ashford, F, Best, A, Crawford, L, Cumley, N, Mayhew, M, Megram, O, Mirza, J, Moles-Garcia, E, Percival, B, Ensell, L, Lowe, HL, Maftei, L, Mondani, M, Chaloner, NJ, Cogger, BJ, Easton, LJ, Huckson, H, Lewis, J, Lowdon, S, Malone, CS, Munemo, F, Mutingwende, M, Nicodemi, R, Podplomyk, O, Somassa, T, Beggs, A, Richter, A, Cormie, C, Dias, J, Forrest, S, Higginson, EE, Maes, M, Young, J, Davidson, RK, Jackson, KA, Turtle, L, Keeley, AJ, Ball, J, Byaruhanga, T, Chappell, JG, Dey, J, Hill, JD, Park, EJ, Fanaie, A, Hilson, RA, Yaze, G, Afifi, S, Beer, R, Maksimovic, J, Masters, KM, Spellman, K, Bresner, C, Fuller, W, Marchbank, A, Workman, T, Shelest, E, Debebe, J, Sang, F, Zamudio, ME, Francois, S, Gutierrez, B, Vasylyeva, TI, Flaviani, F, Ragonnet-Cronin, M, Smollett, KL, Broos, A, Mair, D, Nichols, J, Nomikou, K, Tong, L, Tsatsani, I, O’Brien, S, Rushton, S, Sanderson, R, Perkins, J, Cotton, S, Gallagher, A, Allara, E, Pearson, C, Bibby, D, Dabrera, G, Ellaby, N, Gallagher, E, Hubb, J, Lackenby, A, Lee, D, Manesis, N, Mbisa, T, Platt, S, Twohig, KA, Morgan, M, Aydin, A, Baker, DJ, Foster-Nyarko, E, Prosolek, SJ, Rudder, S, Baxter, C, Carvalho, SF, Lavin, D, Mariappan, A, Radulescu, C, Singh, A, Tang, M, Morcrette, H, Bayzid, N, Cotic, M, Balcazar, CE, Gallagher, MD, Maloney, D, Stanton, TD, Williamson, KA, Manley, R, Michelsen, ML, Sambles, CM, Studholme, DJ, Warwick-Dugdale, J, Eccles, R, Gemmell, M, Gregory, R, Hughes, M, Nelson, C, Rainbow, L, Vamos, EE, Webster, HJ, Whitehead, M, Wierzbicki, C, Angyal, A, Green, LR, Whiteley, M, Bronner, IF, Farr, BW, Lensing, SV, McCarthy, SA, Quail, MA, Redshaw, NM, Thurston, SAJ, Rowe, W, Gaskin, A, Le-Viet, T, Birney, E, Volz, E, Funk, S, Martincorena, I, Barrett, JC, and Gerstung, M
- Abstract
The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021.
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- 2021
7. Report 49: Growth, population distribution and immune escape of Omicron in England
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Ferguson, N, Ghani, A, Cori, A, Hogan, A, Hinsley, W, Volz, E, and Medical Research Council (MRC)
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Coronavirus ,COVID-19 - Abstract
To estimate the growth of the Omicron variant of concern (1) and its immune escape (2–9) characteristics, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England excluding those with a history of recent international travel. We undertook separate analyses according to two case definitions. For the first definition, we included all cases with a definitive negative S-gene Target Failure (SGTF) result and specimen dates between 29/11/2021 and 11/12/2021 inclusive. For the second definition, we included cases with a positive genotype result and specimen date between 23/11/2021 and 11/12/2021 inclusive. We chose a later start date for the SGTF definition to ensure greater specificity of SGTF for Omicron. We used logistic and Poisson regression to identify factors associated with testing positive for Omicron compared to non-Omicron (mostly Delta) cases. We explored the following predictors: day, region, symptomatic status, sex, ethnicity, age band and vaccination status. Our results suggest rapid growth of the frequency of the Omicron variant relative to Delta, with the exponential growth rate of its frequency estimated to be 0.34/day (95% CI: 0.33-0.35) [2.0 day doubling time] over the study period from both SGTF and genotype data. The distribution of Omicron by age, region and ethnicity currently differs markedly from Delta, with 18–29-year-olds, residents in the London region, and those of African ethnicity having significantly higher rates of infection with Omicron relative to Delta. Hospitalisation and asymptomatic infection indicators were not significantly associated with Omicron infection, suggesting at most limited changes in severity compared with Delta. To estimate the impact of Omicron on vaccine effectiveness (VE) for symptomatic infection we used conditional Poisson regression to estimate the hazard ratio of being an Omicron case (using SGTF definition) compared with Delta, restricting our analysis to symptomatic cases and matching by day, region, 10-year age band, sex and ethnicity. We found a significant increased risk of an Omicron case compared to Delta for those with vaccine status AZ 2+weeks post-dose 2 (PD2) , Pfizer 2+w PD2, AZ 2+w post-dose 3 (PD3) and PF 2+w PD3 vaccine states with hazard ratios of 1.86 (95%CI: 1.67-2.08), 2.68 (95%CI: 2.54-2.83), 4.32 (95%CI: 3.84-4.85) and 4.07 (95%CI: 3.66-4.51), respectively, where PD3 states are categorised by the dose 1/2 vaccine used. Depending on the Delta VE estimates used (10), these estimates translate into Omicron VE estimates of between 0% and 20% PD2 and between 55% and 80% PD3 against Omicron, consistent with other estimates (11). Similar estimates were obtained using genotype data, albeit with greater uncertainty. To assess the impact of Omicron on reinfection rates we relied on genotype data, since SGTF is associated with a higher observed rate of reinfection, likely due to reinfections typically having higher Ct values than primary infections and therefore being subject to a higher rate of random PCR target failure. Controlling for vaccine status, age, sex, ethnicity, asymptomatic status, region and specimen date and using conditional Poisson regression to predict reinfection status, Omicron was associated with a 5.41 (95% CI: 4.87-6.00) fold higher risk of reinfection compared with Delta. This suggests relatively low remaining levels of immunity from prior infection.
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- 2021
8. Report 50: Hospitalisation risk for Omicron cases in England
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Ferguson, N, Ghani, A, Hinsley, W, Volz, E, On behalf of the Imperial College COVID-19 Response Team, and Medical Research Council (MRC)
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Coronavirus ,COVID-19 - Abstract
To assess differences in the risk of hospitalisation between the Omicron variant of concern (1) and the Delta variant, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England with last test specimen dates between 1st and 14th December inclusive. Variant was defined using a combination of S-gene Target Failure (SGTF) and genetic data. Case data were linked by National Health service (NHS) number to the National Immunisation Management System (NIMS) database, the NHS Emergency Care (ECDS) and Secondary Use Services (SUS) hospital episode datasets. Hospital attendance was defined as any record of attendance at a hospital by a case in the 14 days following their last positive PCR test, up to and including the day of attendance. A secondary analysis examined the subset of attendances with a length of stay of one or more days. We used stratified conditional Poisson regression to predict hospitalisation status, with demographic strata defined by age, sex, ethnicity, region, specimen date, index of multiple deprivation and in some analyses, vaccination status. Predictor variables were variant (Omicron or Delta), reinfection status and vaccination status. Overall, we find evidence of a reduction in the risk of hospitalisation for Omicron relative to Delta infections, averaging over all cases in the study period. The extent of reduction is sensitive to the inclusion criteria used for cases and hospitalisation, being in the range 20-25% when using any attendance at hospital as the endpoint, and 40-45% when using hospitalisation lasting 1 day or longer or hospitalisations with the ECDS discharge field recorded as “admitted” as the endpoint (Table 1). These reductions must be balanced against the larger risk of infection with Omicron, due to the reduction in protection provided by both vaccination and natural infection. A previous infection reduces the risk of any hospitalisation by approximately 50% (Table 2) and the risk of a hospital stay of 1+ days by 61% (95%CI:55-65%) (before adjustments for under ascertainment of reinfections). High historical infection attack rates and observed reinfection rates with Omicron mean it is necessary to correct hazard ratio estimates to accurately quantify intrinsic differences in severity between Omicron and Delta and to assess the protection afforded by past infection. The resulting adjustments are moderate (typically less than an increase of 0.2 in the hazard ratio for Omicron vs Delta and a reduction of approximately 0.1 in the hazard ratio for reinfections vs primary infections) but significant for evaluating severity overall. Using a hospital stay of 1+ days as the endpoint, the adjusted estimate of the relative risk of reinfections versus primary cases is 0.31, a 69% reduction in hospitalisation risk (Table 2). Stratifying hospitalisation risk by vaccination state reveals a more complex overall picture, albeit consistent with the unstratified analysis. This showed an apparent difference between those who received AstraZenca (AZ) vaccine versus Pfizer or Moderna (PF/MD) for their primary series (doses 1 and 2). Hazard ratios for hospital attendance with Omicron for PF/MD are similar to those seen for Delta in those vaccination categories, while Omicron hazard ratios are generally lower than for Delta for the AZ vaccination categories. Given the limited samples sizes to date, we caution about over-interpreting these trends, but they are compatible with previous findings that while protection afforded against mild infection from AZ was substantially reduced with the emergency of Delta, protection against more severe outcomes was sustained (2,3). We emphasise that these are estimates which condition upon infection; net vaccine effectiveness against hospital attendance may not vary between the vaccines, given that PF/MD maintain higher effectiveness against symptomatic infection with Omicron than AZ (4). Our estimates will assist in refining mathematical models of potential healthcare demand associated with the unfolding European Omicron wave. The hazard ratios provided in Table 3 can be translated into estimates of vaccine effectiveness (VE) against hospitalisation, given estimates of VE against infection (4). In broad terms, our estimates suggest that individuals who have received at least 2 vaccine doses remain substantially protected against hospitalisation, even if protection against infection has been largely lost against the Omicron variant (4,5).
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- 2021
9. HIV genetic diversity informs stage of HIV-1 infection among patients receiving antiretroviral therapy in Botswana
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Ragonnet-Cronin, M, Golubchik, T, Moyo, S, Fraser, C, Essex, M, Novitsky, V, Volz, E, Medical Research Council (MRC), and Medical Research Council
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DYNAMICS ,Science & Technology ,Botswana ,Immunology ,HIV ,Genetic Variation ,HIV Infections ,GENERALIZED EPIDEMICS ,Viral Load ,06 Biological Sciences ,Microbiology ,PHYLOGENETICS ,Infectious Diseases ,early HIV infection ,Anti-Retroviral Agents ,NGS ,MARKER ,HIV-1 ,HIV treatment ,Humans ,TRANSMISSION EVENTS ,Life Sciences & Biomedicine ,ART ,11 Medical and Health Sciences - Abstract
Background HIV-1 genetic diversity increases during infection and can help infer the time elapsed since infection. However the effect of antiretroviral treatment (ART) on the inference remains unknown. Methods Participants with estimated duration of HIV-1 infection based on repeated testing were sourced from cohorts in Botswana (n=1944). Full-length HIV genome sequencing was performed from proviral DNA. We optimized a machine learning model to classify infections as < or >1 year based on viral genetic diversity, demographic and clinical data. Results The best predictive model included variables for genetic diversity of HIV-1 gag, pol and env, viral load, age, sex and ART status. Most participants were on ART. Balanced accuracy was 90.6% (95%CI:86.7%-94.1%). We tested the algorithm among newly diagnosed participants with or without documented negative HIV tests. Among those without records, those who self-reported a negative HIV test within 1 year previously. There was no difference in classification between those self-reporting a negative HIV test
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- 2021
10. Dynamic Variation in Sexual Contact Rates in a Cohort of HIV-Negative Gay Men
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Romero-Severson, E. O., Volz, E., Koopman, J. S., Leitner, T., and Ionides, E. L.
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- 2015
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11. Report 44: Recent trends in SARS-CoV-2 variants of concern in England
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Mishra, S, Mindermann, S, Sharma, M, Whittaker, C, Mellan, T, Wilton, T, Klapsa, D, Mate, R, Fritzsche, M, Zambon, M, Ahuja, J, Howes, A, Miscouridou, X, Nason, G, Ratmann, O, Leech, G, Fabienne Sandkühler, J, Rogers-Smith, C, Vollmer, M, Unwin, H, Gal, Y, Chand, M, Gandy, A, Martin, J, Volz, E, Ferguson, N, Bhatt, S, Brauner, J, Flaxman, S, and Medical Research Council (MRC)
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coronavirus ,COVID-19 - Abstract
Since its emergence in Autumn 2020, the SARS-CoV-2 Variant of Concern (VOC) B.1.1.7 rapidly became the dominant lineage across much of Europe. Simultaneously, several other VOCs were identified globally. Unlike B.1.1.7, some of these VOCs possess mutations thought to confer partial immune escape. Understanding when, whether, and how these additional VOCs pose a threat in settings where B.1.1.7 is currently dominant is vital. This is particularly true for England, which has high coverage from vaccines that are likely more protective against B.1.1.7 than some other VOCs. We examine trends in B.1.1.7’s prevalence in London and other English regions using passive-case detection PCR data, cross-sectional community infection surveys, genomic surveillance, and wastewater monitoring. Our results suggest shifts in the composition of SARS-CoV-2 lineages driving transmission in England between March and April 2021. Local transmission of non-B.1.1.7 VOCs may be increasing; this warrants urgent further investigation.
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- 2021
12. Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England
- Author
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Volz, E, Mishra, S, Chand, M, Barrett, JC, Johnson, R, Geidelberg, L, Hinsley, WR, Laydon, DJ, Dabrera, G, O’Toole, Á, Amato, R, Ragonnet-Cronin, M, Harrison, I, Jackson, B, Ariani, CV, Boyd, O, Loman, NJ, McCrone, JT, Gonçalves, S, Jorgensen, D, Myers, R, Hill, V, Jackson, DK, Gaythorpe, K, Groves, N, Sillitoe, J, Kwiatkowski, DP, Koshy, C, Ash, A, Wise, E, Moore, N, Mori, M, Cortes, N, Lynch, J, Kidd, S, Fairley, DJ, Curran, T, McKenna, JP, Adams, H, Fraser, C, Golubchik, T, Bonsall, D, Hassan-Ibrahim, MO, Malone, CS, Cogger, BJ, Wantoch, M, Reynolds, N, Warne, B, Maksimovic, J, Spellman, K, McCluggage, K, John, M, Beer, R, Afifi, S, Morgan, S, Marchbank, A, Price, A, Kitchen, C, Gulliver, H, Merrick, I, Southgate, J, Guest, M, Munn, R, Workman, T, Connor, TR, Fuller, W, Bresner, C, Snell, LB, Patel, A, Charalampous, T, Nebbia, G, Batra, R, Edgeworth, J, Robson, SC, Beckett, AH, Aanensen, DM, Underwood, AP, Yeats, CA, Abudahab, K, Taylor, BEW, Menegazzo, M, Clark, G, Smith, W, Khakh, M, Fleming, VM, Lister, MM, Howson-Wells, HC, Berry, L, Boswell, T, Joseph, A, Willingham, I, Jones, C, Holmes, C, Bird, P, Helmer, T, Fallon, K, Tang, J, Raviprakash, V, Campbell, S, and Sheriff, N
- Abstract
The SARS-CoV-2 lineage B.1.1.7, designated variant of concern (VOC) 202012/01 by Public Health England1, was first identified in the UK in late summer to early autumn 20202. Whole-genome SARS-CoV-2 sequence data collected from community-based diagnostic testing for COVID-19 show an extremely rapid expansion of the B.1.1.7 lineage during autumn 2020, suggesting that it has a selective advantage. Here we show that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S gene target failures (SGTF) in community-based diagnostic PCR testing. Analysis of trends in SGTF and non-SGTF case numbers in local areas across England shows that B.1.1.7 has higher transmissibility than non-VOC lineages, even if it has a different latent period or generation time. The SGTF data indicate a transient shift in the age composition of reported cases, with cases of B.1.1.7 including a larger share of under 20-year-olds than non-VOC cases. We estimated time-varying reproduction numbers for B.1.1.7 and co-circulating lineages using SGTF and genomic data. The best-supported models did not indicate a substantial difference in VOC transmissibility among different age groups, but all analyses agreed that B.1.1.7 has a substantial transmission advantage over other lineages, with a 50% to 100% higher reproduction number.
- Published
- 2021
13. Sensitivity of SARS-CoV-2 B.1.1.7 to mRNA vaccine-elicited antibodies
- Author
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Collier, D. A., De Marco, A., Ferreira, I. A. T. M., Meng, B., Datir, R. P., Walls, A. C., Kemp, S. A., Bassi, J., Pinto, D., Silacci-Fregni, C., Bianchi, S., Tortorici, M. A., Bowen, J., Culap, K., Jaconi, S., Cameroni, E., Snell, G., Pizzuto, M. S., Pellanda, A. F., Garzoni, C., Riva, A., Baker, S., Dougan, G., Hess, C., Kingston, N., Lehner, P. J., Lyons, P. A., Matheson, N. J., Owehand, W. H., Saunders, C., Summers, C., Thaventhiran, J. E. D., Toshner, M., Weekes, M. P., Bucke, A., Calder, J., Canna, L., Domingo, J., Elmer, A., Fuller, S., Harris, J., Hewitt, S., Kennet, J., Jose, S., Kourampa, J., Meadows, A., O'Brien, C., Price, J., Publico, C., Rastall, R., Ribeiro, C., Rowlands, J., Ruffolo, V., Tordesillas, H., Bullman, B., Dunmore, B. J., Fawke, S., Graf, S., Hodgson, J., Huang, C., Hunter, K., Jones, E., Legchenko, E., Matara, C., Martin, J., Mescia, F., O'Donnell, C., Pointon, L., Pond, N., Shih, J., Sutcliffe, R., Tilly, T., Treacy, C., Tong, Z., Wood, J., Wylot, M., Bergamaschi, L., Betancourt, A., Bower, G., Cossetti, C., De Sa, A., Epping, M., Grenfell, R., Hinch, A., Huhn, O., Jackson, S., Jarvis, I., Lewis, D., Marsden, J., Nice, F., Okecha, G., Omarjee, O., Perera, M., Richoz, N., Romashova, V., Yarkoni, N. S., Sharma, R., Stefanucci, L., Stephens, J., Strezlecki, M., Turner, L., De Bie, E. M. D. D., Bunclark, K., Josipovic, M., Mackay, M., Rossi, S., Selvan, M., Spencer, S., Yong, C., Ansaripour, A., Michael, A., Mwaura, L., Patterson, C., Polwarth, G., Polgarova, P., di Stefano, G., Fahey, C., Michel, R., Bong, S. -H., Coudert, J. D., Holmes, E., Allison, J., Butcher, H., Caputo, D., Clapham-Riley, D., Dewhurst, E., Furlong, A., Graves, B., Gray, J., Ivers, T., Kasanicki, M., Le Gresley, E., Linger, R., Meloy, S., Muldoon, F., Ovington, N., Papadia, S., Phelan, I., Stark, H., Stirrups, K. E., Townsend, P., Walker, N., Webster, J., Mccoy, L. E., Smith, K. G. C., Bradley, J. R., Temperton, N., Ceron-Gutierrez, L., Barcenas-Morales, G., Robson, S. C., Loman, N. J., Connor, T. R., Golubchik, T., Martinez Nunez, R. T., Ludden, C., Corden, S., Johnston, I., Bonsall, D., Smith, C. P., Awan, A. R., Bucca, G., Torok, M. E., Saeed, K., Prieto, J. A., Jackson, D. K., Hamilton, W. L., Snell, L. B., Moore, C., Harrison, E. M., Goncalves, S., Fairley, D. J., Loose, M. W., Watkins, J., Livett, R., Moses, S., Amato, R., Nicholls, S., Bull, M., Smith, D. L., Barrett, J., Aanensen, D. M., Curran, M. D., Parmar, S., Aggarwal, D., Shepherd, J. G., Parker, M. D., Glaysher, S., Bashton, M., Underwood, A. P., Pacchiarini, N., Loveson, K. F., Carabelli, A. M., Templeton, K. E., Langford, C. F., Sillitoe, J., de Silva, T. I., Wang, D., Kwiatkowski, D., Rambaut, A., O'Grady, J., Cottrell, S., Holden, M. T. G., Thomson, E. C., Osman, H., Andersson, M., Chauhan, A. J., Hassan-Ibrahim, M. O., Lawniczak, M., Alderton, A., Chand, M., Constantinidou, C., Unnikrishnan, M., Darby, A. C., Hiscox, J. A., Paterson, S., Martincorena, I., Robertson, D. L., Volz, E. M., Page, A. J., Pybus, O. G., Bassett, A. R., Ariani, C. V., Spencer Chapman, M. H., K. K., Li, Shah, R. N., Jesudason, N. G., Taha, Y., Mchugh, M. P., Dewar, R., Jahun, A. S., Mcmurray, C., Pandey, S., Mckenna, J. P., Nelson, A., Young, G. R., Mccann, C. M., Elliott, S., Lowe, H., Temperton, B., Roy, S., Price, A., Rey, S., Wyles, M., Rooke, S., Shaaban, S., de Cesare, M., Letchford, L., Silveira, S., Pelosi, E., Wilson-Davies, E., Hosmillo, M., O'Toole, A., Hesketh, A. R., Stark, R., du Plessis, L., Ruis, C., Adams, H., Bourgeois, Y., Michell, S. L., Gramatopoulos, D., Edgeworth, J., Breuer, J., Todd, J. A., Fraser, C., Buck, D., John, M., Kay, G. L., Palmer, S., Peacock, S. J., Heyburn, D., Weldon, D., Robinson, E., Mcnally, A., Muir, P., Vipond, I. B., Boyes, J., Sivaprakasam, V., Salluja, T., Dervisevic, S., Meader, E. J., Park, N. R., Oliver, K., Jeffries, A. R., Ott, S., da Silva Filipe, A., Simpson, D. A., Williams, C., Masoli, J. A. H., Knight, B. A., Jones, C. R., Koshy, C., Ash, A., Casey, A., Bosworth, A., Ratcliffe, L., Xu-McCrae, L., Pymont, H. M., Hutchings, S., Berry, L., Jones, K., Halstead, F., Davis, T., Holmes, C., Iturriza-Gomara, M., Lucaci, A. O., Randell, P. A., Cox, A., Madona, P., Harris, K. A., Brown, J. R., Mahungu, T. W., Irish-Tavares, D., Haque, T., Hart, J., Witele, E., Fenton, M. L., Liggett, S., Graham, C., Swindells, E., Collins, J., Eltringham, G., Campbell, S., Mcclure, P. C., Clark, G., Sloan, T. J., Jones, C., Lynch, J., Warne, B., Leonard, S., Durham, J., Williams, T., Haldenby, S. T., Storey, N., Alikhan, N. -F., Holmes, N., Carlile, M., Perry, M., Craine, N., Lyons, R. A., Beckett, A. H., Goudarzi, S., Fearn, C., Cook, K., Dent, H., Paul, H., Davies, R., Blane, B., Girgis, S. T., Beale, M. A., Bellis, K. L., Dorman, M. J., Drury, E., Kane, L., Kay, S., Mcguigan, S., Nelson, R., Prestwood, L., Rajatileka, S., Batra, R., Williams, R. J., Kristiansen, M., Green, A., Justice, A., Mahanama, A. I. K., Samaraweera, B., Hadjirin, N. F., Quick, J., Poplawski, R., Kermack, L. M., Reynolds, N., Hall, G., Chaudhry, Y., Pinckert, M. L., Georgana, I., Moll, R. J., Thornton, A., Myers, R., Stockton, J., Williams, C. A., Yew, W. C., Trotter, A. J., Trebes, A., MacIntyre-Cockett, G., Birchley, A., Adams, A., Plimmer, A., Gatica-Wilcox, B., Mckerr, C., Hilvers, E., Jones, H., Asad, H., Coombes, J., Evans, J. M., Fina, L., Gilbert, L., Graham, L., Cronin, M., Kumziene-Summerhayes, S., Taylor, S., Jones, S., Groves, D. C., Zhang, P., Gallis, M., Louka, S. F., Starinskij, I., Jackson, C., Gourtovaia, M., Tonkin-Hill, G., Lewis, K., Tovar-Corona, J. M., James, K., Baxter, L., Alam, M. T., Orton, R. J., Hughes, J., Vattipally, S., Ragonnet-Cronin, M., Nascimento, F. F., Jorgensen, D., Boyd, O., Geidelberg, L., Zarebski, A. E., Raghwani, J., Kraemer, M. U. G., Southgate, J., Lindsey, B. B., Freeman, T. M., Keatley, J. -P., Singer, J. B., de Oliveira Martins, L., Yeats, C. A., Abudahab, K., Taylor, B. E. W., Menegazzo, M., Danesh, J., Hogsden, W., Eldirdiri, S., Kenyon, A., Mason, J., Robinson, T. I., Holmes, A., Hartley, J. A., Curran, T., Mather, A. E., Shankar, G., Jones, R., Howe, R., Morgan, S., Wastenge, E., Chapman, M. R., Mookerjee, S., Stanley, R., Smith, W., Peto, T., Eyre, D., Crook, D., Vernet, G., Kitchen, C., Gulliver, H., Merrick, I., Guest, M., Munn, R., Bradley, D. T., Wyatt, T., Beaver, C., Foulser, L., Churcher, C. M., Brooks, E., Smith, K. S., Galai, K., Mcmanus, G. M., Bolt, F., Coll, F., Meadows, L., Attwood, S. W., Davies, A., De Lacy, E., Downing, F., Edwards, S., Scarlett, G. P., Jeremiah, S., Smith, N., Leek, D., Sridhar, S., Forrest, S., Cormie, C., Gill, H. K., Dias, J., Higginson, E. E., Maes, M., Young, J., Wantoch, M., Jamrozy, D., Lo, S., Patel, M., Hill, V., Bewshea, C. M., Ellard, S., Auckland, C., Harrison, I., Bishop, C., Chalker, V., Richter, A., Beggs, A., Best, A., Percival, B., Mirza, J., Megram, O., Mayhew, M., Crawford, L., Ashcroft, F., Moles-Garcia, E., Cumley, N., Hopes, R., Asamaphan, P., Niebel, M. O., Gunson, R. N., Bradley, A., Maclean, A., Mollett, G., Blacow, R., Bird, P., Helmer, T., Fallon, K., Tang, J., Hale, A. D., Macfarlane-Smith, L. R., Harper, K. L., Carden, H., Machin, N. W., Jackson, K. A., Ahmad, S. S. Y., George, R. P., Turtle, L., O'Toole, E., Watts, J., Breen, C., Cowell, A., Alcolea-Medina, A., Charalampous, T., Patel, A., Levett, L. J., Heaney, J., Rowan, A., Taylor, G. P., Shah, D., Atkinson, L., Lee, J. C. D., Westhorpe, A. P., Jannoo, R., Lowe, H. L., Karamani, A., Ensell, L., Chatterton, W., Pusok, M., Dadrah, A., Symmonds, A., Sluga, G., Molnar, Z., Baker, P., Bonner, S., Essex, S., Barton, E., Padgett, D., Scott, G., Greenaway, J., Payne, B. A. I., Burton-Fanning, S., Waugh, S., Raviprakash, V., Sheriff, N., Blakey, V., Williams, L. -A., Moore, J., Stonehouse, S., Smith, L., Davidson, R. K., Bedford, L., Coupland, L., Wright, V., Chappell, J. G., Tsoleridis, T., Ball, J., Khakh, M., Fleming, V. M., Lister, M. M., Howson-Wells, H. C., Boswell, T., Joseph, A., Willingham, I., Duckworth, N., Walsh, S., Wise, E., Moore, N., Mori, M., Cortes, N., Kidd, S., Williams, R., Gifford, L., Bicknell, K., Wyllie, S., Lloyd, A., Impey, R., Malone, C. S., Cogger, B. J., Levene, N., Monaghan, L., Keeley, A. J., Partridge, D. G., Raza, M., Evans, C., Johnson, K., Betteridge, E., Farr, B. W., Goodwin, S., Quail, M. A., Scott, C., Shirley, L., Thurston, S. A. J., Rajan, D., Bronner, I. F., Aigrain, L., Redshaw, N. M., Lensing, S. V., Mccarthy, S., Makunin, A., Balcazar, C. E., Gallagher, M. D., Williamson, K. A., Stanton, T. D., Michelsen, M. L., Warwick-Dugdale, J., Manley, R., Farbos, A., Harrison, J. W., Sambles, C. M., Studholme, D. J., Lackenby, A., Mbisa, T., Platt, S., Miah, S., Bibby, D., Manso, C., Hubb, J., Dabrera, G., Ramsay, M., Bradshaw, D., Schaefer, U., Groves, N., Gallagher, E., Lee, D., Williams, D., Ellaby, N., Hartman, H., Manesis, N., Patel, V., Ledesma, J., Twohig, K. A., Allara, E., Pearson, C., Cheng, J. K. J., Bridgewater, H. E., Frost, L. R., Taylor-Joyce, G., Brown, P. E., Tong, L., Broos, A., Mair, D., Nichols, J., Carmichael, S. N., Smollett, K. L., Nomikou, K., Aranday-Cortes, E., Johnson, N., Nickbakhsh, S., Vamos, E. E., Hughes, M., Rainbow, L., Eccles, R., Nelson, C., Whitehead, M., Gregory, R., Gemmell, M., Wierzbicki, C., Webster, H. J., Fisher, C. L., Signell, A. W., Betancor, G., Wilson, H. D., Nebbia, G., Flaviani, F., Cerda, A. C., Merrill, T. V., Wilson, R. E., Cotic, M., Bayzid, N., Thompson, T., Acheson, E., Rushton, S., O'Brien, S., Baker, D. J., Rudder, S., Aydin, A., Sang, F., Debebe, J., Francois, S., Vasylyeva, T. I., Zamudio, M. E., Gutierrez, B., Marchbank, A., Maksimovic, J., Spellman, K., Mccluggage, K., Morgan, M., Beer, R., Afifi, S., Workman, T., Fuller, W., Bresner, C., Angyal, A., Green, L. R., Parsons, P. J., Tucker, R. M., Brown, R., Whiteley, M., Bonfield, J., Puethe, C., Whitwham, A., Liddle, J., Rowe, W., Siveroni, I., Le-Viet, T., Gaskin, A., Johnson, R., Abnizova, I., Ali, M., Allen, L., Anderson, R., Ariani, C., Austin-Guest, S., Bala, S., Bassett, A., Battleday, K., Beal, J., Beale, M., Bellany, S., Bellerby, T., Bellis, K., Berger, D., Berriman, M., Bevan, P., Binley, S., Bishop, J., Blackburn, K., Boughton, N., Bowker, S., Brendler-Spaeth, T., Bronner, I., Brooklyn, T., Buddenborg, S. K., Bush, R., Caetano, C., Cagan, A., Carter, N., Cartwright, J., Monteiro, T. C., Chapman, L., Chillingworth, T. -J., Clapham, P., Clark, R., Clarke, A., Clarke, C., Cole, D., Cook, E., Coppola, M., Cornell, L., Cornwell, C., Corton, C., Crackett, A., Cranage, A., Craven, H., Craw, S., Crawford, M., Cutts, T., Dabrowska, M., Davies, M., Dawson, J., Day, C., Densem, A., Dibling, T., Dockree, C., Dodd, D., Dogga, S., Dougherty, M., Dove, A., Drummond, L., Dudek, M., Durrant, L., Easthope, E., Eckert, S., Ellis, P., Farr, B., Fenton, M., Ferrero, M., Flack, N., Fordham, H., Forsythe, G., Francis, M., Fraser, A., Freeman, A., Galvin, A., Garcia-Casado, M., Gedny, A., Girgis, S., Glover, J., Gould, O., Gray, A., Gray, E., Griffiths, C., Gu, Y., Guerin, F., Hamilton, W., Hanks, H., Harrison, E., Harrott, A., Harry, E., Harvison, J., Heath, P., Hernandez-Koutoucheva, A., Hobbs, R., Holland, D., Holmes, S., Hornett, G., Hough, N., Huckle, L., Hughes-Hallet, L., Hunter, A., Inglis, S., Iqbal, S., Jackson, A., Jackson, D., Verdejo, C. J., Jones, M., Kallepally, K., Kay, K., Keatley, J., Keith, A., King, A., Kitchin, L., Kleanthous, M., Klimekova, M., Korlevic, P., Krasheninnkova, K., Lane, G., Langford, C., Laverack, A., Law, K., Lensing, S., Lewis-Wade, A., Lin, Q., Lindsay, S., Linsdell, S., Long, R., Lovell, J., Mack, J., Maddison, M., Mamun, I., Mansfield, J., Marriott, N., Martin, M., Mayho, M., Mcclintock, J., Mchugh, S., Mcminn, L., Meadows, C., Mobley, E., Moll, R., Morra, M., Morrow, L., Murie, K., Nash, S., Nathwani, C., Naydenova, P., Neaverson, A., Nerou, E., Nicholson, J., Nimz, T., Noell, G. G., O'Meara, S., Ohan, V., Olney, C., Ormond, D., Oszlanczi, A., Pang, Y. F., Pardubska, B., Park, N., Parmar, A., Patel, G., Payne, M., Peacock, S., Petersen, A., Plowman, D., Preston, T., Quail, M., Rance, R., Rawlings, S., Redshaw, N., Reynolds, J., Reynolds, M., Rice, S., Richardson, M., Roberts, C., Robinson, K., Robinson, M., Robinson, D., Rogers, H., Rojo, E. M., Roopra, D., Rose, M., Rudd, L., Sadri, R., Salmon, N., Saul, D., Schwach, F., Seekings, P., Simms, A., Sinnott, M., Sivadasan, S., Siwek, B., Sizer, D., Skeldon, K., Skelton, J., Slater-Tunstill, J., Sloper, L., Smerdon, N., Smith, C., Smith, J., Smith, K., Smith, M., Smith, S., Smith, T., Sneade, L., Soria, C. D., Sousa, C., Souster, E., Sparkes, A., Spencer-Chapman, M., Squares, J., Steed, C., Stickland, T., Still, I., Stratton, M., Strickland, M., Swann, A., Swiatkowska, A., Sycamore, N., Swift, E., Symons, E., Szluha, S., Taluy, E., Tao, N., Taylor, K., Thompson, S., Thompson, M., Thomson, M., Thomson, N., Thurston, S., Toombs, D., Topping, B., Tovar-Corona, J., Ungureanu, D., Uphill, J., Urbanova, J., Van, P. J., Vancollie, V., Voak, P., Walker, D., Walker, M., Waller, M., Ward, G., Weatherhogg, C., Webb, N., Wells, A., Wells, E., Westwood, L., Whipp, T., Whiteley, T., Whitton, G., Widaa, S., Williams, M., Wilson, M., Wright, S., Harvey, W., Virgin, H. W., Lanzavecchia, A., Piccoli, L., Doffinger, R., Wills, M., Veesler, D., Corti, D., and Gupta, R. K.
- Subjects
0301 basic medicine ,Male ,Models, Molecular ,Passive ,Antibodies, Viral ,Neutralization ,0302 clinical medicine ,Models ,Monoclonal ,80 and over ,Viral ,Neutralizing antibody ,Neutralizing ,Aged, 80 and over ,Vaccines ,Vaccines, Synthetic ,Multidisciplinary ,biology ,Antibodies, Monoclonal ,C500 ,Middle Aged ,C700 ,Spike Glycoprotein ,Vaccination ,Spike Glycoprotein, Coronavirus ,Female ,Angiotensin-Converting Enzyme 2 ,Antibody ,Aged ,Antibodies, Neutralizing ,COVID-19 ,COVID-19 Vaccines ,HEK293 Cells ,Humans ,Immune Evasion ,Immunization, Passive ,Mutation ,Neutralization Tests ,SARS-CoV-2 ,medicine.drug_class ,B100 ,Monoclonal antibody ,Antibodies ,Virus ,03 medical and health sciences ,Immune system ,medicine ,COVID-19 Serotherapy ,QR355 ,Synthetic ,Molecular ,Virology ,Coronavirus ,030104 developmental biology ,Immunization ,biology.protein ,030217 neurology & neurosurgery - Abstract
Transmission of SARS-CoV-2 is uncontrolled in many parts of the world; control is compounded in some areas by the higher transmission potential of the B.1.1.7 variant1, which has now been reported in 94 countries. It is unclear whether the response of the virus to vaccines against SARS-CoV-2 on the basis of the prototypic strain will be affected by the mutations found in B.1.1.7. Here we assess the immune responses of individuals after vaccination with the mRNA-based vaccine BNT162b22. We measured neutralizing antibody responses after the first and second immunizations using pseudoviruses that expressed the wild-type spike protein or a mutated spike protein that contained the eight amino acid changes found in the B.1.1.7 variant. The sera from individuals who received the vaccine exhibited a broad range of neutralizing titres against the wild-type pseudoviruses that were modestly reduced against the B.1.1.7 variant. This reduction was also evident in sera from some patients who had recovered from COVID-19. Decreased neutralization of the B.1.1.7 variant was also observed for monoclonal antibodies that target the N-terminal domain (9 out of 10) and the receptor-binding motif (5 out of 31), but not for monoclonal antibodies that recognize the receptor-binding domain that bind outside the receptor-binding motif. Introduction of the mutation that encodes the E484K substitution in the B.1.1.7 background to reflect a newly emerged variant of concern (VOC 202102/02) led to a more-substantial loss of neutralizing activity by vaccine-elicited antibodies and monoclonal antibodies (19 out of 31) compared with the loss of neutralizing activity conferred by the mutations in B.1.1.7 alone. The emergence of the E484K substitution in a B.1.1.7 background represents a threat to the efficacy of the BNT162b2 vaccine.
- Published
- 2021
14. Transmission of SARS-CoV-2 Lineage B.1.1.7 in England: Insights from linking epidemiological and genetic data
- Author
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Volz, E, Mishra, S, Chand, M, Barrett, JC, Johnson, R, Geidelberg, L, Hinsley, WR, Laydon, DJ, Dabrera, G, O’Toole, Á, Amato, R, Ragonnet-Cronin, M, Harrison, I, Jackson, B, Ariani, CV, Boyd, O, Loman, N, McCrone, JT, Gon\c calves, S, Jorgensen, D, Myers, R, Hill, V, Jackson, DK, Gaythorpe, K, Groves, N, Sillitoe, J, Kwiatkowski, DP, Flaxman, S, Ratman, O, Bhatt, S, Hopkins, S, Gandy, A, Rambaut, A, and Ferguson, NM
- Abstract
The SARS-CoV-2 lineage B.1.1.7, now designated Variant of Concern 202012/01 (VOC) by Public Health England, originated in the UK in late Summer to early Autumn 2020. We examine epidemiological evidence for this VOC having a transmission advantage from several perspectives. First, whole genome sequence data collected from community-based diagnostic testing provides an indication of changing prevalence of different genetic variants through time. Phylodynamic modelling additionally indicates that genetic diversity of this lineage has changed in a manner consistent with exponential growth. Second, we find that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S-gene target failures (SGTF) in community-based diagnostic PCR testing. Third, we examine growth trends in SGTF and non-SGTF case numbers at local area level across England, and show that the VOC has higher transmissibility than non-VOC lineages, even if the VOC has a different latent period or generation time. Available SGTF data indicate a shift in the age composition of reported cases, with a larger share of under 20 year olds among reported VOC than non-VOC cases. Fourth, we assess the association of VOC frequency with independent estimates of the overall SARS-CoV-2 reproduction number through time. Finally, we fit a semi-mechanistic model directly to local VOC and non-VOC case incidence to estimate the reproduction numbers over time for each. There is a consensus among all analyses that the VOC has a substantial transmission advantage, with the estimated difference in reproduction numbers between VOC and non-VOC ranging between 0.4 and 0.7, and the ratio of reproduction numbers varying between 1.4 and 1.8. We note that these estimates of transmission advantage apply to a period where high levels of social distancing were in place in England; extrapolation to other transmission contexts therefore requires caution.Competing Interest StatementThe authors have declared no competing interest.Funding StatementCOG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute. The Imperial College COVID-19 Research Fund, UKRI (MR/V038109/1), The Academy of Medical Sciences (SBF004/1080), Bill & Melinda Gates Foundation (OPP1197730, OPP1175094), the European Commission (CoroNAb 101003653), the NIHR BRC Imperial College NHS Trust Infection and COVID themes (RDA02), Amazon AWS and Microsoft AI for Health, the EPSRC, The Medical Research Council (MR/R015600/1), the NIHR Health Protection Research Unit for Modelling and Health Economics, NIHR VEEPD project funding. Wellcome core funding to the Wellcome Sanger Institute (206194).Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:NAAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll aggregated data to reproduce analysis will be provided in the url below.https://github.com/mrc-ide/covid19-variant-N501Y
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- 2021
15. Susceptible-infected-recovered epidemics in populations with heterogeneous contact rates
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Volz, E.
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- 2008
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16. Report 33: Modelling the allocation and impact of a COVID-19 vaccine
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Hogan, A, Winskill, P, Watson, O, Walker, P, Whittaker, C, Baguelin, M, Haw, D, Lochen, A, Gaythorpe, K, Ainslie, K, Bhatt, S, Boonyasiri, A, Boyd, O, Brazeau, N, Cattarino, L, Charles, G, Cooper, L, Coupland, H, Cucunuba Perez, Z, Cuomo-Dannenburg, G, Donnelly, C, Dorigatti, I, Eales, O, Van Elsland, S, Ferreira Do Nascimento, F, Fitzjohn, R, Flaxman, S, Green, W, Hallett, T, Hamlet, A, Hinsley, W, Imai, N, Jauneikaite, E, Jeffrey, B, Knock, E, Laydon, D, Lees, J, Mellan, T, Mishra, S, Nedjati Gilani, G, Nouvellet, P, Ower, A, Parag, K, Ragonnet-Cronin, M, Siveroni, I, Skarp, J, Thompson, H, Unwin, H, Verity, R, Vollmer, M, Volz, E, Walters, C, Wang, H, Wang, Y, Whittles, L, Xi, X, Muhib, F, Smith, P, Hauck, K, Ferguson, N, Ghani, A, Medical Research Council (MRC), and Abdul Latif Jameel Foundation
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Coronavirus ,COVID19 ,COVID-19 ,Vaccine - Abstract
Several SARS-CoV-2 vaccine candidates are now in late-stage trials, with efficacy and safety results expected by the end of 2020. Even under optimistic scenarios for manufacture and delivery, the doses available in 2021 are likely to be limited. Here we identify optimal vaccine allocation strategies within and between countries to maximise health (avert deaths) under constraints on dose supply. We extended an existing mathematical model of SARS-CoV-2 transmission across different country settings to model the public health impact of potential vaccines, using a range of target product profiles developed by the World Health Organization. We show that as supply increases, vaccines that reduce or block infection – and thus transmission – in addition to preventing disease have a greater impact than those that prevent disease alone, due to the indirect protection provided to high-risk groups. We further demonstrate that the health impact of vaccination will depend on the cumulative infection incidence in the population when vaccination begins, the duration of any naturally acquired immunity, the likely trajectory of the epidemic in 2021 and the level of healthcare available to effectively treat those with disease. Within a country, we find that for a limited supply (doses for
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- 2020
17. Report 31: Estimating the burden of COVID-19 in Damascus, Syria: an analysis of novel data sources to infer mortality under-ascertainment
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Van Elsland, S, Watson, O, Alhaffar, M, Mehchy, Z, Whittaker, C, Akil, Z, Ainslie, K, Baguelin, M, Bhatt, S, Boonyasiri, A, Boyd, O, Brazeau, N, Cattarino, L, Charles, G, Ciavarella, C, Cooper, L, Coupland, H, Cucunuba Perez, Z, Cuomo-Dannenburg, G, Djaafara, A, Donnelly, C, Dorigatti, I, Eales, O, Nascimento, F, Fitzjohn, R, Flaxman, S, Forna, A, Fu, H, Gaythorpe, K, Green, W, Hamlet, A, Hauck, K, Haw, D, Hayes, S, Hinsley, W, Imai, N, Jeffrey, B, Johnson, R, Jorgensen, D, Knock, E, Laydon, D, Lees, J, Mellan, T, Mishra, S, Nedjati Gilani, G, Nouvellet, P, Okell, L, Olivera Mesa, D, Pons Salort, M, Ragonnet-Cronin, M, Siveroni, I, Stopard, I, Thompson, H, Unwin, H, Verity, R, Vollmer, M, Volz, E, Walters, C, Wang, H, Wang, Y, Whittles, L, Winskill, P, Xi, X, Ferguson, N, Beals, E, Walker, P, Anonymous Authors, Medical Research Council (MRC), and Abdul Latif Jameel Foundation
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Coronavirus ,Syria ,COVID19 ,COVID-19 - Abstract
The COVID-19 pandemic has resulted in substantial mortality worldwide. However, to date, countries in the Middle East and Africa have reported substantially lower mortality rates than in Europe and the Americas. One hypothesis is that these countries have been ‘spared’, but another is that deaths have been under-ascertained (deaths that have been unreported due to any number of reasons, for instance due to limited testing capacity). However, the scale of under-ascertainment is difficult to assess with currently available data. In this analysis, we estimate the potential under-ascertainment of COVID-19 mortality in Damascus, Syria, where all-cause mortality data has been reported between 25th July and 1st August. We fit a mathematical model of COVID-19 transmission to reported COVID-19 deaths in Damascus since the beginning of the pandemic and compare the model-predicted deaths to reported excess deaths. Exploring a range of different assumptions about under-ascertainment, we estimate that only 1.25% of deaths (sensitivity range 1% - 3%) due to COVID-19 are reported in Damascus. Accounting for under-ascertainment also corroborates local reports of exceeded hospital bed capacity. To validate the epidemic dynamics inferred, we leverage community-uploaded obituary certificates as an alternative data source, which confirms extensive mortality under-ascertainment in Damascus between July and August. This level of under-ascertainment suggests that Damascus is at a much later stage in its epidemic than suggested by surveillance reports, which have repo. We estimate that 4,340 (95% CI: 3,250 - 5,540) deaths due to COVID-19 in Damascus may have been missed as of 2nd September 2020. Given that Damascus is likely to have the most robust surveillance in Syria, these findings suggest that other regions of the country could have experienced similar or worse mortality rates due to COVID-19.
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- 2020
18. Report 30: The COVID-19 epidemic trends and control measures in mainland China
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Fu, H, Xi, X, Wang, H, Boonyasiri, A, Wang, Y, Hinsley, W, Fraser, K, McCabe, R, Olivera Mesa, D, Skarp, J, Ledda, A, Dewe, T, Dighe, A, Winskill, P, Van Elsland, S, Ainslie, K, Baguelin, M, Bhatt, S, Boyd, O, Brazeau, N, Cattarino, L, Charles, G, Coupland, H, Cucunuba Perez, Z, Cuomo-Dannenburg, G, Donnelly, C, Dorigatti, I, Green, W, Hamlet, A, Hauck, K, Haw, D, Jeffrey, B, Laydon, D, Lees, J, Mellan, T, Mishra, S, Nedjati Gilani, G, Nouvellet, P, Okell, L, Parag, K, Ragonnet-Cronin, M, Riley, S, Schmit, N, Thompson, H, Unwin, H, Verity, R, Vollmer, M, Volz, E, Walker, P, Walters, C, Watson, O, Whittaker, C, Whittles, L, Imai, N, Bhatia, S, Ferguson, N, and Medical Research Council (MRC)
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Coronavirus ,China ,COVID19 ,COVID-19 - Published
- 2020
19. Estimating the number of undetected COVID-19 cases among travellers from mainland China
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Bhatia, S, Imai, N, Cuomo-Dannenburg, G, Baguelin, M, Boonyasiri, A, Cori, A, Cucunuba Perez, Z, Dorigatti, I, Fitzjohn, R, Fu, H, Gaythorpe, K, Ghani, A, Hamlet, A, Hinsley, W, Laydon, D, Nedjati Gilani, G, Okell, L, Riley, S, Thompson, H, Van Elsland, S, Volz, E, Wang, H, Wang, Y, Whittaker, C, Xi, X, Donnelly, CA, Ferguson, NM, and Medical Research Council (MRC)
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Background: Since the start of the COVID-19 epidemic in late 2019, there have been more than 152 affected regions and countries with over 110,000 confirmed cases outside mainland China. Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries. Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that more than two thirds (70%, 95% CI: 54% - 80%, compared to Singapore; 75%, 95% CI: 66% - 82%, compared to multiple countries) of cases exported from mainland China have remained undetected. Conclusions: These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.
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- 2020
20. Report 26: Reduction in mobility and COVID-19 transmission
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Nouvellet, P, Bhatia, S, Cori, A, Ainslie, K, Baguelin, M, Bhatt, S, Boonyasiri, A, Brazeau, N, Cattarino, L, Cooper, L, Coupland, H, Cucunuba Perez, Z, Cuomo-Dannenburg, G, Dighe, A, Djaafara, A, Dorigatti, I, Eales, O, Van Elsland, S, Nscimento, F, Fitzjohn, R, Gaythorpe, K, Geidelberg, L, Grassly, N, Green, W, Hamlet, A, Hauck, K, Hinsley, W, Imai, N, Jeffrey, B, Knock, E, Laydon, D, Lees, J, Mangal, T, Mellan, T, Nedjati Gilani, G, Parag, K, Pons Salort, M, Ragonnet-Cronin, M, Riley, S, Unwin, H, Verity, R, Vollmer, M, Volz, E, Walker, P, Walters, C, Wang, H, Watson, O, Whittaker, C, Whittles, L, Xi, X, Ferguson, N, Donnelly, C, and Medical Research Council (MRC)
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Mobility ,COVID19 ,Transmissibility ,COVID-19 - Abstract
In response to the COVID-19 pandemic, countries have sought to control transmission of SARS-CoV-2 by restricting population movement through social distancing interventions, reducing the number of contacts. Mobility data represent an important proxy measure of social distancing. Here, we develop a framework to infer the relationship between mobility and the key measure of population-level disease transmission, the reproduction number (R). The framework is applied to 53 countries with sustained SARS-CoV-2 transmission based on two distinct country-specific automated measures of human mobility, Apple and Google mobility data. For both datasets, the relationship between mobility and transmission was consistent within and across countries and explained more than 85% of the variance in the observed variation in transmissibility. We quantified country-specific mobility thresholds defined as the reduction in mobility necessary to expect a decline in new infections (R
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- 2020
21. Report 16: Role of testing in COVID-19 control
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Grassly, N, Pons Salort, M, Parker, E, White, P, Ainslie, K, Baguelin, M, Bhatt, S, Boonyasiri, A, Boyd, O, Brazeau, N, Cattarino, L, Ciavarella, C, Cooper, L, Coupland, H, Cucunuba Perez, Z, Cuomo-Dannenburg, G, Dighe, A, Djaafara, A, Donnelly, C, Dorigatti, I, Van Elsland, S, Ferreira Do Nascimento, F, Fitzjohn, R, Fu, H, Gaythorpe, K, Geidelberg, L, Green, W, Hallett, T, Hamlet, A, Hayes, S, Hinsley, W, Imai, N, Jorgensen, D, Knock, E, Laydon, D, Lees, J, Mangal, T, Mellan, T, Mishra, S, Nedjati Gilani, G, Nouvellet, P, Okell, L, Ower, A, Parag, K, Pickles, M, Ragonnet-Cronin, M, Stopard, I, Thompson, H, Unwin, H, Verity, R, Vollmer, M, Volz, E, Walker, P, Walters, C, Wang, H, Wang, Y, Watson, O, Whittaker, C, Whittles, L, Winskill, P, Xi, X, Ferguson, N, and Medical Research Council (MRC)
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Coronavirus ,COVID19 ,Testing ,COVID-19 - Abstract
The World Health Organization has called for increased molecular testing in response to the COVID-19 pandemic, but different countries have taken very different approaches. We used a simple mathematical model to investigate the potential effectiveness of alternative testing strategies for COVID-19 control. Weekly screening of healthcare workers (HCWs) and other at-risk groups using PCR or point-of-care tests for infection irrespective of symptoms is estimated to reduce their contribution to transmission by 25-33%, on top of reductions achieved by self-isolation following symptoms. Widespread PCR testing in the general population is unlikely to limit transmission more than contact-tracing and quarantine based on symptoms alone, but could allow earlier release of contacts from quarantine. Immunity passports based on tests for antibody or infection could support return to work but face significant technical, legal and ethical challenges. Testing is essential for pandemic surveillance but its direct contribution to the prevention of transmission is likely to be limited to patients, HCWs and other high-risk groups.
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- 2020
22. Report 13: Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries
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Flaxman, S, Mishra, S, Gandy, A, Unwin, H, Coupland, H, Mellan, T, Zhu, H, Berah, T, Eaton, J, Perez Guzman, P, Schmit, N, Cilloni, L, Ainslie, K, Baguelin, M, Blake, I, Boonyasiri, A, Boyd, O, Cattarino, L, Ciavarella, C, Cooper, L, Cucunuba Perez, Z, Cuomo-Dannenburg, G, Dighe, A, Djaafara, A, Dorigatti, I, Van Elsland, S, Fitzjohn, R, Fu, H, Gaythorpe, K, Geidelberg, L, Grassly, N, Green, W, Hallett, T, Hamlet, A, Hinsley, W, Jeffrey, B, Jorgensen, D, Knock, E, Laydon, D, Nedjati Gilani, G, Nouvellet, P, Parag, K, Siveroni, I, Thompson, H, Verity, R, Volz, E, Walters, C, Wang, H, Wang, Y, Watson, O, Winskill, P, Xi, X, Whittaker, C, Walker, P, Ghani, A, Donnelly, C, Riley, S, Okell, L, Vollmer, M, Ferguson, N, Bhatt, S, Medical Research Council (MRC), and The Royal Society
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Europe ,COVID19 ,Non-pharmaceutical Interventions ,Pneumonia, Viral ,Coronavirus Infections ,CoronaVirus - Abstract
Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Europe is now experiencing large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and universities, banning of mass gatherings and/or public events, and most recently, widescale social distancing including local and national lockdowns. In this report, we use a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact of these interventions across 11 European countries. Our methods assume that changes in the reproductive number – a measure of transmission - are an immediate response to these interventions being implemented rather than broader gradual changes in behaviour. Our model estimates these changes by calculating backwards from the deaths observed over time to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. One of the key assumptions of the model is that each intervention has the same effect on the reproduction number across countries and over time. This allows us to leverage a greater amount of data across Europe to estimate these effects. It also means that our results are driven strongly by the data from countries with more advanced epidemics, and earlier interventions, such as Italy and Spain. We find that the slowing growth in daily reported deaths in Italy is consistent with a significant impact of interventions implemented several weeks earlier. In Italy, we estimate that the effective reproduction number, Rt, dropped to close to 1 around the time of lockdown (11th March), although with a high level of uncertainty. Overall, we estimate that countries have managed to reduce their reproduction number. Our estimates have wide credible intervals and contain 1 for countries that have implemented all interventions considered in our analysis. This means that the reproduction number may be above or below this value. With current interventions remaining in place to at least the end of March, we estimate that interventions across all 11 countries will have averted 59,000 deaths up to 31 March [95% credible interval 21,000-120,000]. Many more deaths will be averted through ensuring that interventions remain in place until transmission drops to low levels. We estimate that, across all 11 countries between 7 and 43 million individuals have been infected with SARS-CoV-2 up to 28th March, representing between 1.88% and 11.43% of the population. The proportion of the population infected to date – the attack rate - is estimated to be highest in Spain followed by Italy and lowest in Germany and Norway, reflecting the relative stages of the epidemics. Given the lag of 2-3 weeks between when transmission changes occur and when their impact can be observed in trends in mortality, for most of the countries considered here it remains too early to be certain that recent interventions have been effective. If interventions in countries at earlier stages of their epidemic, such as Germany or the UK, are more or less effective than they were in the countries with advanced epidemics, on which our estimates are largely based, or if interventions have improved or worsened over time, then our estimates of the reproduction number and deaths averted would change accordingly. It is therefore critical that the current interventions remain in place and trends in cases and deaths are closely monitored in the coming days and weeks to provide reassurance that transmission of SARS-Cov-2 is slowing.
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- 2020
23. Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand
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Ferguson, N, Laydon, D, Nedjati Gilani, G, Imai, N, Ainslie, K, Baguelin, M, Bhatia, S, Boonyasiri, A, Cucunuba Perez, Z, Cuomo-Dannenburg, G, Dighe, A, Dorigatti, I, Fu, H, Gaythorpe, K, Green, W, Hamlet, A, Hinsley, W, Okell, L, Van Elsland, S, Thompson, H, Verity, R, Volz, E, Wang, H, Wang, Y, Walker, P, Walters, C, Winskill, P, Whittaker, C, Donnelly, C, Riley, S, Ghani, A, Medical Research Council (MRC), and The Royal Society
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Coronavirus ,COVID19 ,Non-pharmaceutical interventions ,healthcare demand ,Mortality - Abstract
The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic. Here we present the results of epidemiological modelling which has informed policymaking in the UK and other countries in recent weeks. In the absence of a COVID-19 vaccine, we assess the potential role of a number of public health measures – so-called non-pharmaceutical interventions (NPIs) – aimed at reducing contact rates in the population and thereby reducing transmission of the virus. In the results presented here, we apply a previously published microsimulation model to two countries: the UK (Great Britain specifically) and the US. We conclude that the effectiveness of any one intervention in isolation is likely to be limited, requiring multiple interventions to be combined to have a substantial impact on transmission. Two fundamental strategies are possible: (a) mitigation, which focuses on slowing but not necessarily stopping epidemic spread – reducing peak healthcare demand while protecting those most at risk of severe disease from infection, and (b) suppression, which aims to reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely. Each policy has major challenges. We find that that optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over. For countries able to achieve it, this leaves suppression as the preferred policy option. We show that in the UK and US context, suppression will minimally require a combination of social distancing of the entire population, home isolation of cases and household quarantine of their family members. This may need to be supplemented by school and university closures, though it should be recognised that such closures may have negative impacts on health systems due to increased absenteeism. The major challenge of suppression is that this type of intensive intervention package – or something equivalently effective at reducing transmission – will need to be maintained until a vaccine becomes available (potentially 18 months or more) – given that we predict that transmission will quickly rebound if interventions are relaxed. We show that intermittent social distancing – triggered by trends in disease surveillance – may allow interventions to be relaxed temporarily in relative short time windows, but measures will need to be reintroduced if or when case numbers rebound. Last, while experience in China and now South Korea show that suppression is possible in the short term, it remains to be seen whether it is possible long-term, and whether the social and economic costs of the interventions adopted thus far can be reduced.
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- 2020
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24. Report 8: Symptom progression of COVID-19
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Gaythorpe, K, Imai, N, Cuomo-Dannenburg, G, Baguelin, M, Bhatia, S, Boonyasiri, A, Cori, A, Cucunuba Perez, Z, Dighe, A, Dorigatti, I, Fitzjohn, R, Fu, H, Green, W, Griffin, J, Hamlet, A, Hinsley, W, Hong, N, Kwun, M, Laydon, D, Nedjati Gilani, G, Okell, L, Riley, S, Thompson, H, Van Elsland, S, Verity, R, Volz, E, Walker, P, Wang, H, Wang, Y, Walters, C, Whittaker, C, Winskill, P, Xi, X, Donnelly, C, Ghani, A, Ferguson, N, Medical Research Council (MRC), and The Royal Society
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Coronavirus ,COVID19 ,Symptom - Abstract
The COVID-19 epidemic was declared a Public Health Emergency of International Concern (PHEIC) by WHO on 30th January 2020 [1]. As of 8 March 2020, over 107,000 cases had been reported. Here, we use published and preprint studies of clinical characteristics of cases in mainland China as well as case studies of individuals from Hong Kong, Japan, Singapore and South Korea to examine the proportional occurrence of symptoms and the progression of symptoms through time. We find that in mainland China, where specific symptoms or disease presentation are reported, pneumonia is the most frequently mentioned, see figure 1. We found a more varied spectrum of severity in cases outside mainland China. In Hong Kong, Japan, Singapore and South Korea, fever was the most frequently reported symptom. In this latter group, presentation with pneumonia is not reported as frequently although it is more common in individuals over 60 years old. The average time from reported onset of first symptoms to the occurrence of specific symptoms or disease presentation, such as pneumonia or the use of mechanical ventilation, varied substantially. The average time to presentation with pneumonia is 5.88 days, and may be linked to testing at hospitalisation; fever is often reported at onset (where the mean time to develop fever is 0.77 days).
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- 2020
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25. Report 7: Estimating infection prevalence in Wuhan City from repatriation flights
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Thompson, H, Imai, N, Dighe, A, Baguelin, M, Bhatia, S, Boonyasiri, A, Cori, A, Cucunuba Perez, Z, Cuomo-Dannenburg, G, Dorigatti, I, Fitzjohn, R, Fu, H, Gaythorpe, K, Ghani, A, Green, W, Hamlet, A, Hinsley, W, Laydon, D, Nedjati Gilani, G, Okell, L, Riley, S, Van Elsland, S, Volz, E, Wang, H, Yuanrong, W, Whittaker, C, Xi, X, Donnelly, C, Ferguson, N, and Medical Research Council (MRC)
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Coronavirus ,Prevalence ,COVID-19 ,Repatriation flights ,health care economics and organizations - Abstract
Since the end of January 2020, in response to the growing COVID-19 epidemic, 55 countries have repatriated over 8000 citizens from Wuhan City, China. In addition to quarantine measures for returning citizens, many countries implemented PCR screening to test for infection regardless of symptoms. These flights therefore give estimates of infection prevalence in Wuhan over time. Between 30th January and 1st February (close to the peak of the epidemic in Wuhan), infection prevalence was 0.87% (95% CI: 0.32% - 1.89%). As countries now start to repatriate citizens from Iran and northern Italy, information from repatriated citizens could help inform the level of response necessary to help control the outbreaks unfolding in newly affected areas.
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- 2020
26. Report 6: Relative sensitivity of international surveillance
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Bhatia, S, Imai, N, Cuomo-Dannenburg, G, Baguelin, M, Boonyasiri, A, Cori, A, Cucunuba Perez, Z, Dorigatti, I, Fitzjohn, R, Fu, H, Gaythorpe, K, Ghani, A, Hamlet, A, Hinsley, W, Laydon, D, Nedjati Gilani, G, Thompson, H, Okell, L, Riley, S, Van Elsland, S, Volz, E, Wang, H, Wang, Y, Whittaker, C, Xi, X, Donnelly, C, Ferguson, N, and Medical Research Council (MRC)
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Surveillance ,COVID-19 - Abstract
Since the start of the COVID-19 epidemic in late 2019, there are now 29 affected countries with over 1000 confirmed cases outside of mainland China. In previous reports, we estimated the likely epidemic size in Wuhan City based on air traffic volumes and the number of detected cases internationally. Here we analysed COVID-19 cases exported from mainland China to different regions and countries, comparing the country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different countries. Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that about two thirds of COVID-19 cases exported from mainland China have remained undetected worldwide, potentially resulting in multiple chains of as yet undetected human-to-human transmission outside mainland China.
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- 2020
27. Report 5: Phylogenetic analysis of SARS-CoV-2
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Volz, E, Baguelin, M, Bhatia, S, Boonyasiri, A, Cori, A, Cucunuba Perez, Z, Cuomo-Dannenburg, G, Donnelly, C, Dorigatti, I, Fitzjohn, R, Fu, H, Gaythorpe, K, Ghani, A, Hamlet, A, Hinsley, W, Imai, N, Laydon, D, Nedjati Gilani, G, Okell, L, Riley, S, Van Elsland, S, Wang, H, Wang, Y, Xi, X, Ferguson, N, Medical Research Council (MRC), and The Royal Society
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Phylogenetics ,COVID-19 - Abstract
Genetic diversity of SARS-CoV-2 (formerly 2019-nCoV), the virus which causes COVID-19, provides information about epidemic origins and the rate of epidemic growth. By analysing 53 SARS-CoV-2 whole genome sequences collected up to February 3, 2020, we find a strong association between the time of sample collection and accumulation of genetic diversity. Bayesian and maximum likelihood phylogenetic methods indicate that the virus was introduced into the human population in early December and has an epidemic doubling time of approximately seven days. Phylodynamic modelling provides an estimate of epidemic size through time. Precise estimates of epidemic size are not possible with current genetic data, but our analyses indicate evidence of substantial heterogeneity in the number of secondary infections caused by each case, as indicated by a high level of over-dispersion in the reproduction number. Larger numbers of more systematically sampled sequences – particularly from across China – will allow phylogenetic estimates of epidemic size and growth rate to be substantially refined.
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- 2020
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28. Report 4: Severity of 2019-novel coronavirus (nCoV)
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Dorigatti, I, Okell, L, Cori, A, Imai, N, Baguelin, M, Bhatia, S, Boonyasiri, A, Cucunuba Perez, Z, Cuomo-Dannenburg, G, Fitzjohn, R, Fu, H, Gaythorpe, K, Hamlet, A, Hinsley, W, Hong, N, Kwun, M, Laydon, D, Nedjati Gilani, G, Riley, S, Van Elsland, S, Volz, E, Wang, H, Walters, C, Xi, X, Donnelly, C, Ghani, A, Ferguson, N, Medical Research Council (MRC), and The Royal Society
- Subjects
CFR ,COVID-19 ,Severity - Abstract
We present case fatality ratio (CFR) estimates for three strata of 2019-nCoV infections. For cases detected in Hubei, we estimate the CFR to be 18% (95% credible interval: 11%-81%). For cases detected in travellers outside mainland China, we obtain central estimates of the CFR in the range 1.2-5.6% depending on the statistical methods, with substantial uncertainty around these central values. Using estimates of underlying infection prevalence in Wuhan at the end of January derived from testing of passengers on repatriation flights to Japan and Germany, we adjusted the estimates of CFR from either the early epidemic in Hubei Province, or from cases reported outside mainland China, to obtain estimates of the overall CFR in all infections (asymptomatic or symptomatic) of approximately 1% (95% confidence interval 0.5%-4%). It is important to note that the differences in these estimates does not reflect underlying differences in disease severity between countries. CFRs seen in individual countries will vary depending on the sensitivity of different surveillance systems to detect cases of differing levels of severity and the clinical care offered to severely ill cases. All CFR estimates should be viewed cautiously at the current time as the sensitivity of surveillance of both deaths and cases in mainland China is unclear. Furthermore, all estimates rely on limited data on the typical time intervals from symptom onset to death or recovery which influences the CFR estimates.
- Published
- 2020
29. Formation of intergranular amorphous films during the microstructural development of liquid phase sintered silicon carbide ceramics
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Volz, E., Roosen, A., Wang, S.-C., and Wei, W.-C. J.
- Published
- 2004
- Full Text
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30. Zinc oxide thin films prepared by means of Langmuir–Blodgett multilayers
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Seidl, M., Schurr, M., Brugger, A., Volz, E., and Voit, H.
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- 1999
- Full Text
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31. Structural and Electronic Properties of Self-Assembled Supramolecular Grid Structures: Doping of Supramolecular Thin Films
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Hassmann, J., Hahn, C. Y., Waldmann, O., Volz, E., Schleemilch, H-J., Hallschmid, N., Müller, P., Hanan, G. S., Volkmer, D., Schubert, U. S., Lehn, J-M., Mauser, H., Hirsch, A., and Clark, T.
- Published
- 1997
- Full Text
- View/download PDF
32. Associations between baseline characteristics, CD4 cell count response and virological failure on first-line efavirenz
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Stirrup, OT, Sabin, CA, Phillips, AN, Williams, I, Churchill, D, Tostevin, A, Hill, T, Dunn, DT, Asboe, D, Pozniak, A, Cane, P, Chadwick, D, Clark, D, Collins, S, Delpech, V, Douthwaite, S, Dunn, D, Fearnhill, E, Porter, K, Stirrup, O, Fraser, C, Geretti, AM, Gunson, R, Hale, A, Hue, S, Lazarus, L, Leigh-Brown, A, Mbisa, T, Mackie, N, Orkin, C, Nastouli, E, Pillay, D, Phillips, A, Sabin, C, Smit, E, Templeton, K, Tilston, P, Volz, E, Zhang, H, Fairbrother, K, Dawkins, J, O'Shea, S, Mullen, J, Cox, A, Tandy, R, Fawcett, T, Hopkins, M, Booth, C, Garcia-Diaz, A, Renwick, L, Schmid, ML, Payne, B, Hubb, J, Dustan, S, Kirk, S, Bradley-Stewart, A, Ainsworth, J, Allan, S, Anderson, J, Babiker, A, Gazzard, B, Gilson, R, Compels, M, Hay, P, Johnson, M, Jose, S, Kegg, S, Leen, C, Martin, F, Mital, D, Nelson, M, Palfreeman, A, Post, F, Pritchard, J, Schwenk, A, Tariq, A, Trevelion, R, Ustianowski, A, Walsh, J, Thornton, A, Huntington, S, Glabay, A, Shidfar, S, Lynch, J, Hand, J, De Souza, C, Perry, N, Tilbury, S, Youssef, E, Mabika, T, Mandalia, S, Munshi, S, Adefisan, A, Taylor, C, Gleisner, Z, Ibrahim, F, Campbell, L, Baillie, K, Brima, N, Miller, S, Wood, C, Youle, M, Lampe, F, Smith, C, Tsintas, R, Chaloner, C, Hutchinson, S, Winston, A, Weber, J, Ramzan, F, Carder, M, Wilson, A, Morris, S, Gompels, M, Lewszuk, A, Faleye, A, Ogunbiyi, V, Mitchell, S, Kemble, C, Russell-Sharpe, S, Gravely, J, Harte, A, Spencer, H, Jones, R, Cumming, S, Atkinson, C, Edgell, V, Allen, J, Murphy, C, and Gunder, I
- Subjects
NNRTI ,viral suppression ,Science & Technology ,drug resistance ,MUTATIONS ,Immunology ,antiretroviral therapy ,MODELS ,viral failure ,HIV ,HIV-1 DRUG-RESISTANCE ,TIME ,INDIVIDUALS ,Infectious Diseases ,ADHERENCE ,NRTI ,Virology ,INFECTION ,UK ,COMBINATION ANTIRETROVIRAL THERAPY ,UK HIV Drug Resistance Database and the UK Collaborative HIV Cohort ,Life Sciences & Biomedicine ,ART ,SUPPRESSION - Abstract
Objectives The aim of this study was to investigate associations between baseline characteristics and CD4 cell count response on first-line antiretroviral therapy and risk of virological failure (VF) with or without drug resistance. Methods We conducted an analysis of UK Collaborative HIV Cohort data linked to the UK HIV Drug Resistance Database. Inclusion criteria were viral sequence showing no resistance prior to initiation of first-line efavirenz + tenofovir disoproxil fumarate + emtricitabine and virological suppression within 6 months. Outcomes of VF (≥200 copies/mL) with or without drug resistance were assessed using a competing risks approach fitted jointly with a model for CD4 cell count recovery. Hazard ratios for each VF outcome were estimated for baseline CD4 cell count and viral load and characteristics of CD4 cell count response using latent variables on a standard normal scale. Results A total of 3640 people were included with 338 VF events; corresponding viral sequences were available in 134 with ≥1 resistance mutation in 36. VF with resistance was associated with lower baseline CD4 (0.30, 0.09–0.62), lower CD4 recovery (0.04, 0.00–0.17) and higher CD4 variability (4.40, 1.22–12.68). A different pattern of associations was observed for VF without resistance, but the strength of these results was less consistent across sensitivity analyses. Cumulative incidence of VF with resistance was estimated to be
- Published
- 2019
33. Genetic clustering analysis for HIV infection among MSM in Nigeria implications for intervention
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Li, Y, Liu, H, Ramadhani, HO, Ndembi, N, Crowell, TA, Kijak, G, Robb, ML, Ake, JA, Kokogho, A, Nowak, RG, Gaydos, C, Baral, SD, Volz, E, Tovanabutra, S, Charurat, M, TRUST/RV368 Study Group, and Medical Research Council (MRC)
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Adult ,Male ,0301 basic medicine ,Adolescent ,Immunology ,Human immunodeficiency virus (HIV) ,Nigeria ,HIV Infections ,medicine.disease_cause ,Logistic regression ,Article ,Odds ,Young Adult ,03 medical and health sciences ,0302 clinical medicine ,Intervention (counseling) ,Virology ,medicine ,TRUST/RV368 Study Group ,Cluster Analysis ,Humans ,Immunology and Allergy ,Genetic Predisposition to Disease ,Prospective Studies ,030212 general & internal medicine ,Homosexuality, Male ,11 Medical and Health Sciences ,business.industry ,virus diseases ,Odds ratio ,06 Biological Sciences ,Confidence interval ,17 Psychology and Cognitive Sciences ,Logistic Models ,030104 developmental biology ,Infectious Diseases ,Anti-Retroviral Agents ,Multivariate Analysis ,Cohort ,business ,Viral load ,Demography - Abstract
Background The HIV epidemic continues to grow among MSM in countries across sub-Saharan Africa including Nigeria. To inform prevention efforts, we used a phylogenetic cluster method to characterize HIV genetic clusters and factors associated with cluster formation among MSM living with HIV in Nigeria. Methods We analyzed HIV-1 pol sequences from 417 MSM living with HIV enrolled in the TRUST/RV368 cohort between 2013 and 2017 in Abuja and Lagos, Nigeria. A genetically linked cluster was defined among participants whose sequences had pairwise genetic distance of 1.5% or less. Binary and multinomial logistic regressions were used to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for factors associated with HIV genetic cluster membership and size. Results Among 417 MSM living with HIV, 153 (36.7%) were genetically linked. Participants with higher viral load (AOR = 1.72 95% CI: 1.04-2.86), no female partners (AOR = 3.66; 95% CI: 1.97-6.08), and self-identified as male sex (compared with self-identified as bigender) (AOR = 3.42; 95% CI: 1.08-10.78) had higher odds of being in a genetic cluster. Compared with unlinked participants, MSM who had high school education (AOR = 23.84; 95% CI: 2.66-213.49), were employed (AOR = 3.41; 95% CI: 1.89-10.70), had bacterial sexually transmitted infections (AOR = 3.98; 95% CI: 0.89-17.22) and were not taking antiretroviral therapy (AOR = 6.61; 95% CI: 2.25-19.37) had higher odds of being in a large cluster (size > 4). Conclusion Comprehensive HIV prevention packages should include behavioral and biological components, including early diagnosis and treatment of both HIV and bacterial sexually transmitted infections to optimally reduce the risk of HIV transmission and acquisition.
- Published
- 2019
34. Identification of hidden population structure in time-scaled phylogenies
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Volz, E, Wiuf, C, Grad, Y, Frost, SDW, Dennis, A, Didelot, X, and Medical Research Council (MRC)
- Abstract
Population structure influences genealogical patterns, however data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealised genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial pol sequences. This revealed the presence of clades which had grown rapidly in the recent past, and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome Neisseria gonorrhoeae sequences. We find that population structure detected using these methods closely overlaps with the appearance and expansion of mutations conferring antimicrobial resistance.
- Published
- 2019
35. Virological outcomes of boosted protease inhibitor-based first-line ART in subjects harbouring thymidine analogue-associated mutations as the sole form of transmitted drug resistance
- Author
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Geretti, AM, White, E, Orkin, C, Tostevin, A, Tilston, P, Chadwick, D, Leen, C, Sabin, C, Dunn, DT, Asboe, D, Pozniak, A, Cane, P, Churchill, D, Clark, D, Collins, S, Delpech, V, Douthwaite, S, Dunn, D, Fearnhill, E, Porter, K, Stirrup, O, Fraser, C, Gunson, R, Hale, A, Hue, S, Lazarus, L, Leigh-Brown, A, Mbisa, T, Mackie, N, Nastouli, E, Pillay, D, Phillips, A, Smit, E, Templeton, K, Volz, E, Williams, I, Zhang, H, Dawkins, J, O'Shea, S, Mullen, J, Cox, A, Tandy, R, Fawcett, T, Hopkins, M, Booth, C, Garcia-Diaz, A, Renwick, L, Schmid, ML, Payne, B, Hubb, J, Dustan, S, Kirk, S, Bradley-Stewart, A, Ainsworth, J, Allan, S, Anderson, J, Babiker, A, Gazzard, B, Gilson, R, Gompels, M, Hay, P, Hill, T, Johnson, M, Jose, S, Kegg, S, Martin, F, Mital, D, Nelson, M, Palfreeman, A, Post, F, Pritchard, J, Sabin, CA, Schwenk, A, Tariq, A, Trevelion, R, Ustianowski, A, Walsh, J, Thornton, A, Huntington, S, Glabay, A, Shidfar, S, Lynch, J, Hand, J, De Souza, C, Perry, N, Tilbury, S, Youssef, E, Mabika, T, Mandalia, S, Munshi, S, Adefisan, A, Taylor, C, Gleisner, Z, Ibrahim, F, Campbell, L, Baillie, K, Brima, N, Miller, S, Wood, C, Youle, M, Lampe, F, Smith, C, Tsintas, R, Chaloner, C, Hutchinson, S, Winston, A, Weber, J, Ramzan, F, Carder, M, Wilson, A, Morris, S, Lewszuk, A, Faleye, A, Ogunbiyi, V, Mitchell, S, Kemble, C, Russell-Sharpe, S, Gravely, J, Harte, A, Spencer, H, Jones, R, Cumming, S, Atkinson, C, Edgell, V, Allen, J, Murphy, C, and Gunder, I
- Subjects
0301 basic medicine ,Oncology ,Male ,HIV Infections ,Drug resistance ,Kaplan-Meier Estimate ,chemistry.chemical_compound ,0302 clinical medicine ,1108 Medical Microbiology ,Abacavir ,Antiretroviral Therapy, Highly Active ,INFECTION ,Pharmacology (medical) ,Pharmacology & Pharmacy ,030212 general & internal medicine ,Original Research ,Proteolytic enzymes ,Lamivudine ,virus diseases ,Viral Load ,Prognosis ,ANTIRETROVIRAL TREATMENT ,Infectious Diseases ,Treatment Outcome ,Cohort ,RNA, Viral ,Female ,1115 Pharmacology and Pharmaceutical Sciences ,UK HIV Drug Resistance Database and UK CHIC Study ,Life Sciences & Biomedicine ,Viral load ,0605 Microbiology ,medicine.drug ,Microbiology (medical) ,Adult ,medicine.medical_specialty ,Efavirenz ,Genotype ,TRANSMISSION ,Anti-HIV Agents ,030106 microbiology ,REGIMENS ,Emtricitabine ,Microbiology ,03 medical and health sciences ,Internal medicine ,Drug Resistance, Viral ,medicine ,Humans ,Protease Inhibitors ,Alleles ,Pharmacology ,Science & Technology ,TREATMENT-NAIVE PATIENTS ,business.industry ,HIV ,INDIVIDUALS ,chemistry ,Amino Acid Substitution ,Mutation ,HIV-1 ,business - Abstract
Objectives: In subjects with transmitted thymidine analogue mutations (TAMs), boosted PIs (PI/b) are often chosen to overcome possible resistance to the NRTI backbone. However, data to guide treatment selection are limited. Our aim was to obtain firmer guidance for clinical practice using real-world cohort data.Methods: We analysed 1710 subjects who started a PI/b in combination with tenofovir or abacavir plus emtricitabine or lamivudine, and compared their virological outcomes with those of 4889 patients who started an NNRTI (predominantly efavirenz), according to the presence of ≥1 TAM as the sole form of transmitted drug resistance.Results: Participants with ≥1 TAM comprised predominantly MSM (213 of 269, 79.2%), subjects of white ethnicity (206 of 269, 76.6%) and HIV-1 subtype B infections (234 of 269, 87.0%). Most (203 of 269, 75.5%) had singleton TAMs, commonly a revertant of T215Y or T215F (112 of 269, 41.6%). Over a median of 2.5 years of follow-up, 834 of 6599 (12.6%) subjects experienced viraemia (HIV-1 RNA >50 copies/mL). The adjusted HR for viraemia was 2.17 with PI/b versus NNRTI-based therapy (95% CI 1.88-2.51; P Conclusions: In this cohort, patients harbouring ≥1 TAM as the sole form of transmitted drug resistance gained no apparent virological advantage from starting first-line ART with a PI/b.
- Published
- 2018
36. Molecular epidemiology of HIV-1 subtype B reveals heterogeneous transmission risk: Implications for intervention and control
- Author
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Volz, E, Le Vu, S, Ratmann, O, Tostevin, A, Dunn, D, Orkin, C, O'Shea, S, Delpech, V, Brown, A, Gill, N, and Fraser, C
- Abstract
Background The impact of HIV pre-exposure prophylaxis (PrEP) depends on infections averted by protecting vulnerable individuals as well as infections averted by preventing transmission by those who would have been infected if not receiving PrEP. Analysis of HIV phylogenies reveals risk factors for transmission, which we examine as potential criteria for allocating PrEP. Methods We analyzed 6912 HIV-1 partial pol sequences from men who have sex with men (MSM) in the United Kingdom combined with global reference sequences and patient-level metadata. Population genetic models were developed that adjust for stage of infection, global migration of HIV lineages, and changing incidence of infection through time. Models were extended to simulate the effects of providing susceptible MSM with PrEP. Results We found that young age Conclusions Concentrating PrEP doses on young individuals can avert more infections than random allocation.
- Published
- 2018
37. Systematic Use of Lactic Acid Levels to Comply with Sepsis Guidelines May Result in Overtreatment of Non-Septic Patients
- Author
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Berlinger, M., primary, Hamer, D., additional, Musso, M., additional, Walker, M., additional, Bliss, K., additional, Volz, E., additional, Laurent, M.E., additional, Caffery, T., additional, Alwood, S., additional, Brierre, S.A., additional, Jagneaux, T., additional, Sanchez, M., additional, O'Neal, H.R., additional, and Thomas, C.B., additional
- Published
- 2019
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38. Phylodynamic inference across epidemic scales
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Volz, E, Romero-Severson, E, Leitner, TK, Medical Research Council (MRC), and National Institutes of Health
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Genetics & Heredity ,DYNAMICS ,Biochemistry & Molecular Biology ,Evolutionary Biology ,0604 Genetics ,Science & Technology ,DRUG-USERS ,EVOLUTIONARY RATES ,EFFECTIVE POPULATION-SIZE ,HIV ,0601 Biochemistry And Cell Biology ,SEQUENCE DATA ,coalescent ,phylodynamics ,COALESCENT INFERENCE ,0603 Evolutionary Biology ,RISK GROUPS ,Ebola ,HIV-1 ,TRANSMISSION HISTORY ,EFFECTIVE NUMBER ,Life Sciences & Biomedicine - Abstract
Within-host genetic diversity and large transmission bottlenecks confound phylodynamic inference of epidemiological dynamics. Conventional phylodynamic approaches assume that nodes in a time-scaled pathogen phylogeny correspond closely to the time of transmission between hosts that are ancestral to the sample. However, when hosts harbour diverse pathogen populations, node times can substantially pre-date infection times. Imperfect bottlenecks can cause lineages sampled in different individuals to coalesce in unexpected patterns. To address realistic violations of standard phylodynamic assumptions we developed a new inference approach based on a multi-scale coalescent model, accounting for nonlinear epidemiological dynamics, heterogeneous sampling through time, non-negligible genetic diversity of pathogens within hosts, and imperfect transmission bottlenecks. We apply this method to HIV-1 and Ebola virus outbreak sequence data, illustrating how and when conventional phylodynamic inference may give misleading results. Within-host diversity of HIV-1 causes substantial upwards bias in the number of infected hosts using conventional coalescent models, but estimates using the multi-scale model have greater consistency with reported number of diagnoses through time. In contrast, we find that within- host diversity of Ebola virus has little influence on estimated numbers of infected hosts or reproduction numbers, and estimates are highly consistent with the reported number of diagnoses through time. The multi-scale coalescent also enables estimation of within-host effective population size using single sequences from a random sample of patients. We find within-host population genetic diversity of HIV-1 p17 to be 2 Nμ = 0 . 012(95% CI:0 . 0066 − 0 . 023), which is lower than estimates based on HIV envelope serial sequencing of individual patients.
- Published
- 2017
39. Improving Timely Completion of Radiation Therapy End of Treatment Summaries in a Large Multi-Site Radiation Oncology Department
- Author
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Guttmann, D.M., primary, Volz, E., additional, Gabriel, P.E., additional, Lustig, R.A., additional, Patel, K., additional, Maity, A., additional, and Alonso-Basanta, M., additional
- Published
- 2018
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40. A6 Using phylodynamic modelling to estimate the population attributable fraction of HIV spread due to key populations in Dakar, Senegal
- Author
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Geidelberg, E, primary and Volz, E, additional
- Published
- 2018
- Full Text
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41. Scalable relaxed clock phylogenetic dating
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Volz, E. M., primary and Frost, S. D. W., additional
- Published
- 2017
- Full Text
- View/download PDF
42. CONTINUED GENETIC INVESTIGATION OF PATIENTS WITH PRESUMED DEFECTS IN THE GH-IGF-1 AXIS: GENOTYPE:PHENOTYPE CORRELATIONS
- Author
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Ahearn, M.E., Gayol, L., Estrella, E., Volz, E., Basterrichea, H., Silverman, M., Davis, A., and Baumbach, L.
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Human genetics -- Research ,Dwarfism -- Genetic aspects ,Gene mutations -- Physiological aspects ,Biological sciences - Published
- 2001
43. Ueber die Natur der Quellungsvorgänge: Siebente Mitteilung Ueber die molaren Vorgänge bei Quellungen und deren Quellungswärmen
- Author
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Knövenagel, E. and Volz, E.
- Published
- 1923
- Full Text
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44. Die pelviskopische Sakropexie zur Therapie des Vaginalprolapses
- Author
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Volz E, J. Volz, S. Köster, H.-J. Strittmatter, F. Melchert, and A. Wischnik
- Subjects
medicine.medical_specialty ,Benign condition ,medicine.diagnostic_test ,business.industry ,Obstetrics and Gynecology ,Uterine prolapse ,medicine.disease ,Surgery ,Endoscopy ,Vaginal disease ,medicine.anatomical_structure ,Surgical mesh ,Maternity and Midwifery ,medicine ,Vagina ,Laparoscopy ,business ,Invasive Procedure - Abstract
Although transabdominal sacropexy to correct vaginal prolapse is technically simple and yields good results, a minimal invasive procedure is desirable in the treatment of this benign condition. We therefore developed a laparoscopic sacropexy technique and were able to apply this operation successfully. Pelviscopic sacropexy does not differ greatly in principle from the intraabdominal approach; however, the techniques used in the individual steps must be adapted to pelviscopic methods.
- Published
- 1993
45. Examining Patient Perceptions of Quality and Safety in a Large Radiation Oncology Department
- Author
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DeCesaris, C.M., primary, Woodhouse, K.D., additional, Volz, E., additional, Gabriel, P.E., additional, Suneja, G., additional, Maity, A., additional, and Hahn, S.M., additional
- Published
- 2015
- Full Text
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46. The Implementation and Assessment of a Quality and Safety Culture Education Program in a Large Radiation Oncology Department
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Woodhouse, K.D., primary, Volz, E., additional, Bellerive, M.R., additional, Gabriel, P.E., additional, Maity, A., additional, Hahn, S.M., additional, and Vapiwala, N., additional
- Published
- 2015
- Full Text
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47. Hemodynamic and Ventilatory Changes in Patients with Obstructive Airway Disease Exposed to a Simulated Altitude of 2,500 m
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Matthys, H., primary, Ernst, H. H., additional, Volz, E., additional, and Konietzko, N., additional
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48. Factors Associated With Event Reporting in the Pediatric Radiation Oncology Population Using an Electronic Condition Reporting System
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Hill-Kayser, C.E., primary, Gabriel, P.E., additional, Volz, E., additional, Lustig, R.A., additional, Tochner, Z., additional, Hahn, S., additional, and Maity, A., additional
- Published
- 2014
- Full Text
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49. Pelviskopisches Operieren ohne Pneumoperitoneum? Eine neue Methode und ihre Auswirkungen auf die Narkose
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S. Köster, Weiss M, Melchert F, A Wischnik, J. Volz, and Volz E
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medicine.medical_specialty ,medicine.diagnostic_test ,business.industry ,Obstetrics and Gynecology ,Surgical procedures ,medicine.disease ,Pelvis minor ,Surgery ,Endoscopy ,Abdominal wall ,medicine.anatomical_structure ,Pneumoperitoneum ,Anesthesia ,Maternity and Midwifery ,medicine ,Intraabdominal pressure ,business - Abstract
New developments in the field of pelviscopic surgery enable us to perform more extensive, time-consuming and difficult operations. Prolonging the increased intraabdominal pressure carries the risk of dangerous complications, especially in high-risk patients. We introduce a new technique to perform prolonged pelviscopic operations without or with only slightly increased intraabdominal pressure. The abdominal wall is suspended from a fixation frame. Negative effects on anaesthesia caused by prolonged increased intraabdominal pressure can be compensated. Many different pelviscopic operations can be performed using this simple and inexpensive technique, particularly in surgical procedures of the adnexae. This new technique is advantageous especially in high-risk patients, who can no longer be excluded from extensive pelviscopic surgery.
- Published
- 1993
50. Pelviskopische Ovarchirurgie: Eine neue Methode zur gefahrlosen Organbergung
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A. Wischnik, S. Köster, Potempa D, F. Melchert, Volz E, and J. Volz
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Ovarian surgery ,medicine.medical_specialty ,medicine.diagnostic_test ,business.industry ,Obstetrics and Gynecology ,Ovary ,Pelvis minor ,Surgery ,Endoscopy ,Abdominal wall ,Peritoneal cavity ,medicine.anatomical_structure ,Maternity and Midwifery ,Medicine ,Ovarian tumours ,business - Abstract
For pelviscopic removal of ovarian tumours, a puncture or morcellation of the tumour used to be necessary, frequently causing the peritoneal cavity to be contaminated with contents of cysts or tumourous material. This contamination can be avoided safely by placing the intact tumour into a bag, provided that the tumour has been dissected completely. The intact tumour is put into a bag and both are completely removed at the same time through the abdominal wall. This method increases the safety of pelviscopic ovarian surgery, and its indication for use can be broadened.
- Published
- 1993
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