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1.
Emergency Medicine Journal ; 39(3):263, 2022.
Article in English | EMBASE | ID: covidwho-1759397

ABSTRACT

Aims/Objectives/Background Patients admitted to hospital via the emergency department (ED) need to be separated by SARS-CoV-2 infection status to prevent transmission. Using clinical criteria alone is not feasible due to the range of symptoms and asymptomatic spread. Turnaround time of laboratory PCR assays (~6-24 hrs) hinders patient movement through the hospital with pressure on side-rooms pending results and exposure risk if unsuspected cases are moved into bays. Lateral flow devices (LFD) can provide a rapid diagnosis and aid patient movement. This implementation study aimed to assess the accuracy and safety of LFDs within an ED during a highprevalence period. Methods/Design Two rapid point-of-care tests (POCT) were introduced during December 2020: Cobas®-Liat® system (Roche Diagnostics) is a 20-minute assay comparable to laboratory PCR (in-house validation), and LFDs. Symptomatic patients with a positive LFD were cohorted on a 'red' ward. Asymptomatic patients with a negative result were allocated an 'amber' ward, pending lab PCR. Where there were discrepancies between results and symptoms;a Liat® was performed. The LFDs were validated by PCR swabs to determine true positive and false negative (FN) rates and to minimise fallout via contact tracing. The PCR cycle threshold (CT) values were recorded to evaluate the LFD sensitivity and specificity. Results were collected between December 2020-March 2021. Results/Conclusions Comparing LFD with PCR results, the sensitivity and specificity were 70.7% and 99.1%. LFD FNs had higher CT values (25), indicating the beginning or end of infection - unlikely infectious. One period of false positives during lower prevalence revealed a faulty batch. During the study period 90% of patients left the ED with a virological diagnosis. We conclude that POCT can aid the diagnosis of COVID- 19 in the ED when combined with existing laboratory-based PCR algorithms. We demonstrate a safe and effective use of POCT in the ED which could be replicated across other centres.

2.
McCrone, J. T.; Hill, V.; Bajaj, S.; Pena, R. E.; Lambert, B. C.; Inward, R.; Bhatt, S.; Volz, E.; Ruis, C.; Dellicour, S.; Baele, G.; Zarebski, A. E.; Sadilek, A.; Wu, N.; Schneider, A.; Ji, X.; Raghwani, J.; Jackson, B.; Colquhoun, R.; O'Toole, Á, Peacock, T. P.; Twohig, K.; Thelwall, S.; Dabrera, G.; Myers, R.; Faria, N. R.; Huber, C.; Bogoch, I. I.; Khan, K.; du Plessis, L.; Barrett, J. C.; Aanensen, D. M.; Barclay, W. S.; Chand, M.; Connor, T.; Loman, N. J.; Suchard, M. A.; Pybus, O. G.; Rambaut, A.; Kraemer, M. U. G.; Robson, S. C.; Connor, T. R.; Loman, N. J.; Golubchik, T.; Martinez Nunez, R. T.; Bonsall, D.; Rambaut, A.; Snell, L. B.; Livett, R.; Ludden, C.; Corden, S.; Nastouli, E.; Nebbia, G.; Johnston, I.; Lythgoe, K.; Estee Torok, M.; Goodfellow, I. G.; Prieto, J. A.; Saeed, K.; Jackson, D. K.; Houlihan, C.; Frampton, D.; Hamilton, W. L.; Witney, A. A.; Bucca, G.; Pope, C. F.; Moore, C.; Thomson, E. C.; Harrison, E. M.; Smith, C. P.; Rogan, F.; Beckwith, S. M.; Murray, A.; Singleton, D.; Eastick, K.; Sheridan, L. A.; Randell, P.; Jackson, L. M.; Ariani, C. V.; Gonçalves, S.; Fairley, D. J.; Loose, M. W.; Watkins, J.; Moses, S.; Nicholls, S.; Bull, M.; Amato, R.; Smith, D. L.; Aanensen, D. M.; Barrett, J. C.; Aggarwal, D.; Shepherd, J. G.; Curran, M. D.; Parmar, S.; Parker, M. D.; Williams, C.; Glaysher, S.; Underwood, A. P.; Bashton, M.; Pacchiarini, N.; Loveson, K. F.; Byott, M.; Carabelli, A. M.; Templeton, K. E.; de Silva, T. I.; Wang, D.; Langford, C. F.; Sillitoe, J.; Gunson, R. N.; Cottrell, S.; O'Grady, J.; Kwiatkowski, D.; Lillie, P. J.; Cortes, N.; Moore, N.; Thomas, C.; Burns, P. J.; Mahungu, T. W.; Liggett, S.; Beckett, A. H.; Holden, M. T. G.; Levett, L. J.; Osman, H.; Hassan-Ibrahim, M. O.; Simpson, D. A.; Chand, M.; Gupta, R. K.; Darby, A. C.; Paterson, S.; Pybus, O. G.; Volz, E. M.; de Angelis, D.; Robertson, D. L.; Page, A. J.; Martincorena, I.; Aigrain, L.; Bassett, A. R.; Wong, N.; Taha, Y.; Erkiert, M. J.; Spencer Chapman, M. H.; Dewar, R.; McHugh, M. P.; Mookerjee, S.; Aplin, S.; Harvey, M.; Sass, T.; Umpleby, H.; Wheeler, H.; McKenna, J. P.; Warne, B.; Taylor, J. F.; Chaudhry, Y.; Izuagbe, R.; Jahun, A. S.; Young, G. R.; McMurray, C.; McCann, C. M.; Nelson, A.; Elliott, S.; Lowe, H.; Price, A.; Crown, M. R.; Rey, S.; Roy, S.; Temperton, B.; Shaaban, S.; Hesketh, A. R.; Laing, K. G.; Monahan, I. M.; Heaney, J.; Pelosi, E.; Silviera, S.; Wilson-Davies, E.; Fryer, H.; Adams, H.; du Plessis, L.; Johnson, R.; Harvey, W. T.; Hughes, J.; Orton, R. J.; Spurgin, L. G.; Bourgeois, Y.; Ruis, C.; O'Toole, Á, Gourtovaia, M.; Sanderson, T.; Fraser, C.; Edgeworth, J.; Breuer, J.; Michell, S. L.; Todd, J. A.; John, M.; Buck, D.; Gajee, K.; Kay, G. L.; Peacock, S. J.; Heyburn, D.; Kitchman, K.; McNally, A.; Pritchard, D. T.; Dervisevic, S.; Muir, P.; Robinson, E.; Vipond, B. B.; Ramadan, N. A.; Jeanes, C.; Weldon, D.; Catalan, J.; Jones, N.; da Silva Filipe, A.; Williams, C.; Fuchs, M.; Miskelly, J.; Jeffries, A. R.; Oliver, K.; Park, N. R.; Ash, A.; Koshy, C.; Barrow, M.; Buchan, S. L.; Mantzouratou, A.; Clark, G.; Holmes, C. W.; Campbell, S.; Davis, T.; Tan, N. K.; Brown, J. R.; Harris, K. A.; Kidd, S. P.; Grant, P. R.; Xu-McCrae, L.; Cox, A.; Madona, P.; Pond, M.; Randell, P. A.; Withell, K. T.; Williams, C.; Graham, C.; Denton-Smith, R.; Swindells, E.; Turnbull, R.; Sloan, T. J.; Bosworth, A.; Hutchings, S.; Pymont, H. M.; Casey, A.; Ratcliffe, L.; Jones, C. R.; Knight, B. A.; Haque, T.; Hart, J.; Irish-Tavares, D.; Witele, E.; Mower, C.; Watson, L. K.; Collins, J.; Eltringham, G.; Crudgington, D.; Macklin, B.; Iturriza-Gomara, M.; Lucaci, A. O.; McClure, P. C.; Carlile, M.; Holmes, N.; Moore, C.; Storey, N.; Rooke, S.; Yebra, G.; Craine, N.; Perry, M.; Alikhan, N. F.; Bridgett, S.; Cook, K. F.; Fearn, C.; Goudarzi, S.; Lyons, R. A.; Williams, T.; Haldenby, S. T.; Durham, J.; Leonard, S.; Davies, R. M.; Batra, R.; Blane, B.; Spyer, M. J.; Smith, P.; Yavus, M.; Williams, R. J.; Mahanama, A. I. K.; Samaraweera, B.; Girgis, S. T.; Hansford, S. E.; Green, A.; Beaver, C.; Bellis, K. L.; Dorman, M. J.; Kay, S.; Prestwood, L.; Rajatileka, S.; Quick, J.; Poplawski, R.; Reynolds, N.; Mack, A.; Morriss, A.; Whalley, T.; Patel, B.; Georgana, I.; Hosmillo, M.; Pinckert, M. L.; Stockton, J.; Henderson, J. H.; Hollis, A.; Stanley, W.; Yew, W. C.; Myers, R.; Thornton, A.; Adams, A.; Annett, T.; Asad, H.; Birchley, A.; Coombes, J.; Evans, J. M.; 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.; Taylor, S.; Trotter, A. J.; Williams, C. A.; Kermack, L. M.; Foulkes, B. H.; Gallis, M.; Hornsby, H. R.; Louka, S. F.; Pohare, M.; Wolverson, P.; Zhang, P.; MacIntyre-Cockett, G.; Trebes, A.; Moll, R. J.; Ferguson, L.; Goldstein, E. J.; Maclean, A.; Tomb, R.; Starinskij, I.; Thomson, L.; Southgate, J.; Kraemer, M. U. G.; Raghwani, J.; Zarebski, A. E.; Boyd, O.; Geidelberg, L.; Illingworth, C. J.; Jackson, C.; Pascall, D.; Vattipally, S.; Freeman, T. M.; Hsu, S. N.; Lindsey, B. B.; James, K.; Lewis, K.; Tonkin-Hill, G.; Tovar-Corona, J. M.; Cox, M.; Abudahab, K.; Menegazzo, M.; Taylor, B. E. W.; Yeats, C. A.; Mukaddas, A.; Wright, D. W.; de Oliveira Martins, L.; Colquhoun, R.; Hill, V.; Jackson, B.; McCrone, J. T.; Medd, N.; Scher, E.; Keatley, J. P.; Curran, T.; Morgan, S.; Maxwell, P.; Smith, K.; Eldirdiri, S.; Kenyon, A.; Holmes, A. H.; Price, J. R.; Wyatt, T.; Mather, A. E.; Skvortsov, T.; Hartley, J. A.; Guest, M.; Kitchen, C.; Merrick, I.; Munn, R.; Bertolusso, B.; Lynch, J.; Vernet, G.; Kirk, S.; Wastnedge, E.; Stanley, R.; Idle, G.; Bradley, D. T.; Poyner, J.; Mori, M.; Jones, O.; Wright, V.; Brooks, E.; Churcher, C. M.; Fragakis, M.; Galai, K.; Jermy, A.; Judges, S.; McManus, G. M.; Smith, K. S.; Westwick, E.; Attwood, S. W.; Bolt, F.; Davies, A.; De Lacy, E.; Downing, F.; Edwards, S.; Meadows, L.; Jeremiah, S.; Smith, N.; Foulser, L.; Charalampous, T.; Patel, A.; Berry, L.; Boswell, T.; Fleming, V. M.; Howson-Wells, H. C.; Joseph, A.; Khakh, M.; Lister, M. M.; Bird, P. W.; Fallon, K.; Helmer, T.; McMurray, C. L.; Odedra, M.; Shaw, J.; Tang, J. W.; Willford, N. J.; Blakey, V.; Raviprakash, V.; Sheriff, N.; Williams, L. A.; Feltwell, T.; Bedford, L.; Cargill, J. S.; Hughes, W.; Moore, J.; Stonehouse, S.; Atkinson, L.; Lee, J. C. D.; Shah, D.; Alcolea-Medina, 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, S. S. Y.; George, R. P.; Machin, N. W.; 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.; et al..
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326827

ABSTRACT

The Delta variant of concern of SARS-CoV-2 has spread globally causing large outbreaks and resurgences of COVID-19 cases1-3. The emergence of Delta in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions4,5. Here we analyse 52,992 Delta genomes from England in combination with 93,649 global genomes to reconstruct the emergence of Delta, and quantify its introduction to and regional dissemination across England, in the context of changing travel and social restrictions. Through analysis of human movement, contact tracing, and virus genomic data, we find that the focus of geographic expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced >1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers from India reduced onward transmission from importations;however the transmission chains that later dominated the Delta wave in England had been already seeded before restrictions were introduced. In England, increasing inter-regional travel drove Delta's nationwide dissemination, with some cities receiving >2,000 observable lineage introductions from other regions. Subsequently, increased levels of local population mixing, not the number of importations, was associated with faster relative growth of Delta. Among US states, we find that regions that previously experienced large waves also had faster Delta growth rates, and a model including interactions between immunity and human behaviour could accurately predict the rise of Delta there. Delta's invasion dynamics depended on fine scale spatial heterogeneity in immunity and contact patterns and our findings will inform optimal spatial interventions to reduce transmission of current and future VOCs such as Omicron.

3.
Robson, S. C.; Connor, T. R.; Loman, N. J.; Golubchik, T.; Nunez, R. T. M.; Bonsall, D.; Rambaut, A.; Snell, L. B.; Livett, R.; Ludden, C.; Corden, S.; Nastouli, E.; Nebbia, G.; Johnston, I.; Lythgoe, K.; Torok, M. E.; Goodfellow, I. G.; Prieto, J. A.; Saeed, K.; Jackson, D. K.; Houlihan, C.; Frampton, D.; Hamilton, W. L.; Witney, A. A.; Bucca, G.; Pope, C. F.; Moore, C.; Thomson, E. C.; Harrison, E. M.; Smith, C. P.; Rogan, F.; Beckwith, S. M.; Murray, A.; Singleton, D.; Eastick, K.; Sheridan, L. A.; Randell, P.; Jackson, L. M.; Ariani, C. V.; Gonçalves, S.; Fairley, D. J.; Loose, M. W.; Watkins, J.; Moses, S.; Nicholls, S.; Bull, M.; Amato, R.; Smith, D. L.; Aanensen, D. M.; Barrett, J. C.; Aggarwal, D.; Shepherd, J. G.; Curran, M. D.; Parmar, S.; Parker, M. D.; Williams, C.; Glaysher, S.; Underwood, A. P.; Bashton, M.; Loveson, K. F.; Byott, M.; Pacchiarini, N.; Carabelli, A. M.; Templeton, K. E.; de Silva, T. I.; Wang, D.; Langford, C. F.; Sillitoe, J.; Gunson, R. N.; Cottrell, S.; O'Grady, J.; Kwiatkowski, D.; Lillie, P. J.; Cortes, N.; Moore, N.; Thomas, C.; Burns, P. J.; Mahungu, T. W.; Liggett, S.; Beckett, A. H.; Holden, M. T. G.; Levett, L. J.; Osman, H.; Hassan-Ibrahim, M. O.; Simpson, D. A.; Chand, M.; Gupta, R. K.; Darby, A. C.; Paterson, S.; Pybus, O. G.; Volz, E. M.; de Angelis, D.; Robertson, D. L.; Page, A. J.; Martincorena, I.; Aigrain, L.; Bassett, A. R.; Wong, N.; Taha, Y.; Erkiert, M. J.; Chapman, M. H. S.; Dewar, R.; McHugh, M. P.; Mookerjee, S.; Aplin, S.; Harvey, M.; Sass, T.; Umpleby, H.; Wheeler, H.; McKenna, J. P.; Warne, B.; Taylor, J. F.; Chaudhry, Y.; Izuagbe, R.; Jahun, A. S.; Young, G. R.; McMurray, C.; McCann, C. M.; Nelson, A.; Elliott, S.; Lowe, H.; Price, A.; Crown, M. R.; Rey, S.; Roy, S.; Temperton, B.; Shaaban, S.; Hesketh, A. R.; Laing, K. G.; Monahan, I. M.; Heaney, J.; Pelosi, E.; Silviera, S.; Wilson-Davies, E.; Adams, H.; du Plessis, L.; Johnson, R.; Harvey, W. T.; Hughes, J.; Orton, R. J.; Spurgin, L. G.; Bourgeois, Y.; Ruis, C.; O'Toole, Á, Gourtovaia, M.; Sanderson, T.; Fraser, C.; Edgeworth, J.; Breuer, J.; Michell, S. L.; Todd, J. A.; John, M.; Buck, D.; Gajee, K.; Kay, G. L.; Peacock, S. J.; Heyburn, D.; Kitchman, K.; McNally, A.; Pritchard, D. T.; Dervisevic, S.; Muir, P.; Robinson, E.; Vipond, B. B.; Ramadan, N. A.; Jeanes, C.; Weldon, D.; Catalan, J.; Jones, N.; da Silva Filipe, A.; Williams, C.; Fuchs, M.; Miskelly, J.; Jeffries, A. R.; Oliver, K.; Park, N. R.; Ash, A.; Koshy, C.; Barrow, M.; Buchan, S. L.; Mantzouratou, A.; Clark, G.; Holmes, C. W.; Campbell, S.; Davis, T.; Tan, N. K.; Brown, J. R.; Harris, K. A.; Kidd, S. P.; Grant, P. R.; Xu-McCrae, L.; Cox, A.; Madona, P.; Pond, M.; Randell, P. A.; Withell, K. T.; Williams, C.; Graham, C.; Denton-Smith, R.; Swindells, E.; Turnbull, R.; Sloan, T. J.; Bosworth, A.; Hutchings, S.; Pymont, H. M.; Casey, A.; Ratcliffe, L.; Jones, C. R.; Knight, B. A.; Haque, T.; Hart, J.; Irish-Tavares, D.; Witele, E.; Mower, C.; Watson, L. K.; Collins, J.; Eltringham, G.; Crudgington, D.; Macklin, B.; Iturriza-Gomara, M.; Lucaci, A. O.; McClure, P. C.; Carlile, M.; Holmes, N.; Moore, C.; Storey, N.; Rooke, S.; Yebra, G.; Craine, N.; Perry, M.; Fearn, N. C.; Goudarzi, S.; Lyons, R. A.; Williams, T.; Haldenby, S. T.; Durham, J.; Leonard, S.; Davies, R. M.; Batra, R.; Blane, B.; Spyer, M. J.; Smith, P.; Yavus, M.; Williams, R. J.; Mahanama, A. I. K.; Samaraweera, B.; Girgis, S. T.; Hansford, S. E.; Green, A.; Beaver, C.; Bellis, K. L.; Dorman, M. J.; Kay, S.; Prestwood, L.; Rajatileka, S.; Quick, J.; Poplawski, R.; Reynolds, N.; Mack, A.; Morriss, A.; Whalley, T.; Patel, B.; Georgana, I.; Hosmillo, M.; Pinckert, M. L.; Stockton, J.; Henderson, J. H.; Hollis, A.; Stanley, W.; Yew, W. C.; Myers, R.; Thornton, A.; Adams, A.; Annett, T.; Asad, H.; Birchley, A.; Coombes, J.; Evans, J. M.; 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.; Taylor, S.; Trotter, A. J.; Williams, C. A.; Kermack, L. M.; Foulkes, B. H.; Gallis, M.; Hornsby, H. R.; Louka, S. F.; Pohare, M.; Wolverson, P.; Zhang, P.; MacIntyre-Cockett, G.; Trebes, A.; Moll, R. J.; Ferguson, L.; Goldstein, E. J.; Maclean, A.; Tomb, R.; Starinskij, I.; Thomson, L.; Southgate, J.; Kraemer, M. U. G.; Raghwani, J.; Zarebski, A. E.; Boyd, O.; Geidelberg, L.; Illingworth, C. J.; Jackson, C.; Pascall, D.; Vattipally, S.; Freeman, T. M.; Hsu, S. N.; Lindsey, B. B.; James, K.; Lewis, K.; Tonkin-Hill, G.; Tovar-Corona, J. M.; Cox, M.; Abudahab, K.; Menegazzo, M.; Taylor, B. E. W.; Yeats, C. A.; Mukaddas, A.; Wright, D. W.; de Oliveira Martins, L.; Colquhoun, R.; Hill, V.; Jackson, B.; McCrone, J. T.; Medd, N.; Scher, E.; Keatley, J. P.; Curran, T.; Morgan, S.; Maxwell, P.; Smith, K.; Eldirdiri, S.; Kenyon, A.; Holmes, A. H.; Price, J. R.; Wyatt, T.; Mather, A. E.; Skvortsov, T.; Hartley, J. A.; Guest, M.; Kitchen, C.; Merrick, I.; Munn, R.; Bertolusso, B.; Lynch, J.; Vernet, G.; Kirk, S.; Wastnedge, E.; Stanley, R.; Idle, G.; Bradley, D. T.; Poyner, J.; Mori, M.; Jones, O.; Wright, V.; Brooks, E.; Churcher, C. M.; Fragakis, M.; Galai, K.; Jermy, A.; Judges, S.; McManus, G. M.; Smith, K. S.; Westwick, E.; Attwood, S. W.; Bolt, F.; Davies, A.; De Lacy, E.; Downing, F.; Edwards, S.; Meadows, L.; Jeremiah, S.; Smith, N.; Foulser, L.; Charalampous, T.; Patel, A.; Berry, L.; Boswell, T.; Fleming, V. M.; Howson-Wells, H. C.; Joseph, A.; Khakh, M.; Lister, M. M.; Bird, P. W.; Fallon, K.; Helmer, T.; McMurray, C. L.; Odedra, M.; Shaw, J.; Tang, J. W.; Willford, N. J.; Blakey, V.; Raviprakash, V.; Sheriff, N.; Williams, L. A.; Feltwell, T.; Bedford, L.; Cargill, J. S.; Hughes, W.; Moore, J.; Stonehouse, S.; Atkinson, L.; Lee, J. C. D.; Shah, D.; Alcolea-Medina, A.; Ohemeng-Kumi, N.; Ramble, J.; Sehmi, J.; Williams, R.; Chatterton, W.; Pusok, M.; Everson, W.; Castigador, A.; Macnaughton, E.; Bouzidi, K. El, Lampejo, T.; Sudhanva, M.; Breen, C.; Sluga, G.; Ahmad, S. S. Y.; George, R. P.; Machin, N. W.; 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.; Harrison, I.; Gifford, L.; Molnar, Z.; Auckland, C.; Evans, C.; Johnson, K.; Partridge, D. G.; Raza, M.; Baker, P.; Bonner, S.; Essex, S.; Murray, L. J.; Lawton, A. I.; Burton-Fanning, S.; Payne, B. A. I.; Waugh, S.; Gomes, A. N.; Kimuli, M.; Murray, D. R.; Ashfield, P.; Dobie, D.; Ashford, F.; Best, A.; Crawford, L.; Cumley, N.; Mayhew, M.; Megram, O.; Mirza, J.; Moles-Garcia, E.; Percival, B.; Driscoll, M.; Ensell, L.; Lowe, H. L.; Maftei, L.; Mondani, M.; Chaloner, N. J.; Cogger, B. J.; Easton, L. J.; Huckson, H.; Lewis, J.; Lowdon, S.; Malone, C. S.; Munemo, F.; Mutingwende, M.; et al..
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326811

ABSTRACT

The scale of data produced during the SARS-CoV-2 pandemic has been unprecedented, with more than 5 million sequences shared publicly at the time of writing. This wealth of sequence data provides important context for interpreting local outbreaks. However, placing sequences of interest into national and international context is difficult given the size of the global dataset. Often outbreak investigations and genomic surveillance efforts require running similar analyses again and again on the latest dataset and producing reports. We developed civet (cluster investigation and virus epidemiology tool) to aid these routine analyses and facilitate virus outbreak investigation and surveillance. Civet can place sequences of interest in the local context of background diversity, resolving the query into different 'catchments' and presenting the phylogenetic results alongside metadata in an interactive, distributable report. Civet can be used on a fine scale for clinical outbreak investigation, for local surveillance and cluster discovery, and to routinely summarise the virus diversity circulating on a national level. Civet reports have helped researchers and public health bodies feedback genomic information in the appropriate context within a timeframe that is useful for public health.

4.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-296037

ABSTRACT

Introduction A second wave of SARS-CoV-2 infection spread across the UK in 2020 linked with emergence of the more transmissible B.1.1.7 variant. The emergence of new variants, particularly during relaxation of social distancing policies and implementation of mass vaccination, highlights the need for real-time integration of detailed patient clinical data alongside pathogen genomic data. We linked clinical data with viral genome sequence data to compare cases admitted during the first and second waves of SARS-CoV-2 infection. Methods Clinical, laboratory and demographic data from five electronic health record (EHR) systems was collected for all cases with a positive SARS-CoV-2 RNA test between March 13th 2020 and February 17th 2021. SARS-CoV-2 viral sequencing was performed using Oxford Nanopore Technology. Descriptive data are presented comparing cases between waves, and between cases of B.1.1.7 and non-B.1.1.7 variants. Results There were 5810 SARS-CoV-2 RNA positive cases comprising inpatients (n=2341), healthcare workers (n=1549), outpatients (n=874), emergency department (ED) attenders not subsequently admitted (n=532), inter-hospital transfers (n=281) and nosocomial cases (n=233). There were two dominant waves of hospital admissions, with wave one starting from March 13 th (n=838) and wave two from October 20 th (n=1503), both with a temporally aligned rise in nosocomial cases (n=96 in wave one, n=137 in wave two). 1470 SARS-CoV-2 isolates were successfully sequenced, including 216/838 (26%) admitted cases from wave one, 472/1503 (31%) admitted cases in wave two and 121/233 (52%) nosocomial cases. The first B.1.1.7 variant was identified on 15th November 2020 and increased rapidly such that it comprised 400/472 (85%) of sequenced isolates from admitted cases in wave two. Females made up a larger proportion of admitted cases in wave two (47.3% vs 41.8%, p=0.011), and in those infected with the B.1.1.7 variant compared to non-B.1.1.7 variants (48.0% vs 41.8%, p=0.042). A diagnosis of frailty was less common in wave two (11.5% v 22.8%, p<0.001) and in the group infected with B.1.1.7 (14.5% v 22.4%, p=0.001). There was no difference in severity on admission between waves, as measured by hypoxia at admission (wave one: 64.3% vs wave two: 65.5%, p=0.67). However, a higher proportion of cases infected with the B.1.1.7 variant were hypoxic on admission compared to other variants (70.0% vs 62.5%, p=0.029). Conclusions Automated EHR data extraction linked with SARS-CoV-2 genome sequence data provides valuable insight into the evolving characteristics of cases admitted to hospital with COVID-19. The proportion of cases with hypoxia on admission was greater in those infected with the B.1.1.7 variant, which supports evidence the B.1.1.7 variant is associated with more severe disease. The number of nosocomial cases was similar in both waves despite introduction of many infection control interventions before wave two, an observation requiring further investigation.

5.
Infect Prev Pract ; 3(4): 100186, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1517292

ABSTRACT

BACKGROUND: Point-of-care (POC) SARS-CoV-2 lateral-flow antigen detection (LFD) testing in the emergency department (ED) could inform rapid infection control decisions but requirements for safe deployment have not been fully defined. METHODS: Review of LFD test results, laboratory and POC-RT-PCR results and ED-performance metrics during a two-week high SARS-CoV-2 prevalence period followed by several months of falling prevalence. AIM: Determine whether LFD testing can be safely deployed in ED to provide an effective universal SARS-CoV-2 testing capability. FINDINGS: 93% (345/371) of COVID-19 patients left ED with a virological diagnosis during the 2-week universal LFD evaluation period compared to 77% with targeted POC-RT-PCR deployment alone, on background of approximately one-third having an NHS Track and Trace RT-PCR test-result at presentation. LFD sensitivity and specificity was 70.7% and 99.1% respectively providing a PPV of 97.7% and NPV of 86.4% with disease prevalence of 34.7%. ED discharge-delays (breaches) attributable to COVID-19 fell to 33/3532 (0.94%) compared with the preceding POC-RT-PCR period (107/4114 (2.6%); p=<0.0001). Importantly, LFD testing identified 1 or 2 clinically-unsuspected COVID-19 patients/day. Three clinically-confirmed LFD false positive patients were appropriately triaged based on LFD action-card flowchart, and only 5 of 95 false-negative LFD results were inappropriately admitted to non-COVID-19 areas where no onward-transmission was identified. LFD testing was restricted to asymptomatic patients when disease prevalence fell below 5% and detected 1-3 cases/week. CONCLUSION: Universal SARS-CoV-2 LFD testing can be safely and effectively deployed in ED alongside POC-RT-PCR testing during periods of high and low disease prevalence.

6.
Journal of Physics: Conference Series ; 1950(1), 2021.
Article in English | ProQuest Central | ID: covidwho-1349738

ABSTRACT

The novel coronavirus or officially known as SARS-CoV 2 (Severe Acute Respiratory Syndrome Coronavirus 2) has caused a severe pandemic over the world affecting not only the economy of the countries but also the lifestyle of the people worldwide. As on 31.12.2020, Covid-19 (coronavirus disease) has infecting more than 10266674 people and causing about 148738 deaths in India. It has been seen through various statistics of various countries that the number of Covid-19 cases grows exponentially as the number of test increases then after some period, the rate of new cases decreases. In this research paper, researchers have created deep learning-based model to predict the curve of the new Covid-19 cases vs the total number of tests conducted in India. There is still lockdown in some part of the country while some states have partially relaxed the rules and some states totally lifted the lockdown. Predicting the number of new cases and their trend can help in deciding what is the optimal time to release the lockdown. It will also help in determining when the coronavirus will loosen its grip from India.

7.
International Journal of Modern Agriculture ; 10(2):790-803, 2021.
Article in English | Web of Science | ID: covidwho-1224516

ABSTRACT

This paper investigates various ways in which a pandemic such as the novel coronavirus, could be predicted using different mathematical models. It also studies the various ways in which these models could be depicted using various visualization techniques. This paper aims to present various statistical techniques suggested by the Centres for Disease Control and Prevention in order to represent the epidemiological data. The main focus of this paper is to analyse how epidemiological data or contagious diseases are theorized using any available information and later may be presented wrongly by not following the guidelines, leading to inaccurate representation and interpretations of the current scenario of the pandemic;with a special reference to the Indian Subcontinent

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