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1.
PLoS Computational Biology ; 18(9):e1010406, 2022.
Article in English | MEDLINE | ID: covidwho-2021465

ABSTRACT

The first year of the COVID-19 pandemic put considerable strain on healthcare systems worldwide. In order to predict the effect of the local epidemic on hospital capacity in England, we used a variety of data streams to inform the construction and parameterisation of a hospital progression model, EpiBeds, which was coupled to a model of the generalised epidemic. In this model, individuals progress through different pathways (e.g. may recover, die, or progress to intensive care and recover or die) and data from a partially complete patient-pathway line-list was used to provide initial estimates of the mean duration that individuals spend in the different hospital compartments. We then fitted EpiBeds using complete data on hospital occupancy and hospital deaths, enabling estimation of the proportion of individuals that follow the different clinical pathways, the reproduction number of the generalised epidemic, and to make short-term predictions of hospital bed demand. The construction of EpiBeds makes it straightforward to adapt to different patient pathways and settings beyond England. As part of the UK response to the pandemic, EpiBeds provided weekly forecasts to the NHS for hospital bed occupancy and admissions in England, Wales, Scotland, and Northern Ireland at national and regional scales.

2.
Philos Trans A Math Phys Eng Sci ; 380(2233): 20210315, 2022 Oct 03.
Article in English | MEDLINE | ID: covidwho-1992467

ABSTRACT

The English SARS-CoV-2 epidemic has been affected by the emergence of new viral variants such as B.1.177, Alpha and Delta, and changing restrictions. We used statistical models and the agent-based model Covasim, in June 2021, to estimate B.1.177 to be 20% more transmissible than the wild type, Alpha to be 50-80% more transmissible than B.1.177 and Delta to be 65-90% more transmissible than Alpha. Using these estimates in Covasim (calibrated 1 September 2020 to 20 June 2021), in June 2021, we found that due to the high transmissibility of Delta, resurgence in infections driven by the Delta variant would not be prevented, but would be strongly reduced by delaying the relaxation of restrictions by one month and with continued vaccination. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Models, Statistical , SARS-CoV-2/genetics , Systems Analysis
3.
Journal of Hepatology ; 77:S240-S241, 2022.
Article in English | EMBASE | ID: covidwho-1967503

ABSTRACT

Background and aims: Canada is currently on target to reach the 2030 WHO goal of HCV elimination. Continued high rates of treatment initiation are required to meet this goal. Novel models have proven successful to engage populations who use drugs (PWUD) in HCV therapy with a simplified, task-shifted cascade of care: Tayside, Scotland pharmacy-based HCV screening and treatment has demonstrated excellent outcomes and progress towards local HCV elimination. The EPIC Study seeks to determine whether pharmacybased treatment successes can be replicated at community pharmacies in Victoria BC. Method: Four community pharmacies known to work with PWUD and provide opioid agonist therapy (OAT) were provided training sessions to equip staff with a standardized tool kit of resources. In fall 2020, pharmacy staff were trained to provide verbal informed consent and perform point of care HCV OraQuick antibody screening. Pharmacies were supported by a study nurse to link to HCV RNA testing when antibody positive patients were identified, with initiation of HCV treatment offered to those found to be RNA positive. (Figure Presented) Figure: (: THU296): Antibody responses after the COVID-19 vaccination in patients with AILD and healthy controls. (A-B) The seropositivity rate (A) and titers (B) of anti-RBD-IgG in patients with AILD and healthy controls. (D-E) The seropositivity rate (D) and titers (E) of NAbs in patients with AILD and healthy controls. The distribution of anti-RBD-IgG (C) and NAbs (F) antibody titers over time in patients with AILD and healthy controls. AILD, autoimmune liver disease;anti-RBD-IgG, spike receptor-binding domain IgG antibody;NAbs, neutralizing antibodies. The study nurse worked with pharmacy staff to strategize adherence and support as needed by study subjects. Qualitative interviews have been conducted with five pharmacy staff to explore their experiences with testing and monitoring HCV treatment and the feasibility of involving pharmacists in the HCV care cascade. Results: To date pharmacy staff completed 171 HCV OraQuick tests finding 53 tested positive for HCV antibodies: 23 people were HCV RNA negative, (20 previously treated and 2 self-cleared), 8 unk/LTF. Of the 22 RNA positive participants, 1 is pending treatment start, 21 people have started treatment, with 8 achieving SVR. While great success has been achieved in treating identified people, less than half of projected OraQuick tests have been completed. Although the onset of the Covid 19 pandemic was a fundamental barrier incorporating HCV testing at pharmacies, stigma related to HCV and illicit drug use continues to impact this process. Pharmacists described feeling hesitant about approaching participants, especially after receiving negative responses from clients about HCV testing. Some worried their relationship would change with clients as asking about HCV implied risky drug use. Conclusion: This innovative and novel approach to HCV therapy in PWUD attempted to use a pharmacy-based approach to find people with limited connection to primary health care to test and treat HCV. Increased training of pharmacy staff related to stigma around drug use and HCV is required both before and ongoing for successful integration of pharmacy-led HCV testing and treatment in Canada.

4.
Internal Medicine Journal ; 52:33-34, 2022.
Article in English | English Web of Science | ID: covidwho-1880642
5.
Embase; 2021.
Preprint in English | EMBASE | ID: ppcovidwho-335847

ABSTRACT

Low- and middle-income countries (LMICs) remain of high potential for hotspots for COVID-19 deaths and emerging variants given the inequality of vaccine distribution and their vulnerable healthcare systems. We aim to evaluate containment strategies that are sustainable and effective for LMICs. We constructed synthetic populations with varying contact and household structures to capture LMIC demographic characteristics that vary across communities. Using an agent-based model, we explored the optimal containment strategies for rural and urban communities by designing and simulating setting-specific strategies that deploy rapid diagnostic tests, symptom screening, contact tracing and physical distancing. In low-density rural communities, we found implementing either high quality (sensitivity > 50%) antigen rapid diagnostic tests or moderate physical distancing could contain the transmission. In urban communities, we demonstrated that both physical distancing and case finding are essential for containing COVID-19 (average infection rate < 10%). In high density communities that resemble slums and squatter settlements, physical distancing is less effective compared to rural and urban communities. Lastly, we demonstrated contact tracing is essential for effective containment. Our findings suggested that rapid diagnostic tests could be prioritised for control and monitor COVID-19 transmission and highlighted that contact survey data could guide strategy design to save resources for LMICs. An accompanying open source R package is available for simulating COVID-19 transmission based on contact network models.

6.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333732

ABSTRACT

BACKGROUND: Relatively few COVID-19 cases and deaths have been reported through much of sub-Saharan Africa, including South Sudan, although the extent of SARS-CoV-2 spread remains unclear due to weak surveillance systems and few population-representative serosurveys. METHODS: We conducted a representative household-based cross-sectional serosurvey in Juba, South Sudan. We quantified IgG antibody responses to SARS-CoV-2 spike protein receptor-binding domain and estimated seroprevalence using a Bayesian regression model accounting for test performance. RESULTS: We recruited 2,214 participants from August 10 to September 11, 2020 and 22.3% had anti-SARS-CoV-2 IgG titers above levels in pre-pandemic samples. After accounting for waning antibody levels, age, and sex, we estimated that 38.5% (32.1 - 46.8) of the population had been infected with SARS-CoV-2. For each RT-PCR confirmed COVID-19 case, 104 (87-126) infections were unreported. Background antibody reactivity was higher in pre-pandemic samples from Juba compared to Boston, where the serological test was validated. The estimated proportion of the population infected ranged from 30.1% to 60.6% depending on assumptions about test performance and prevalence of clinically severe infections. CONCLUSIONS: SARS-CoV-2 has spread extensively within Juba. Validation of serological tests in sub-Saharan African populations is critical to improve our ability to use serosurveillance to understand and mitigate transmission.

7.
Critical Care Medicine ; 50(1 SUPPL):43, 2022.
Article in English | EMBASE | ID: covidwho-1692106

ABSTRACT

INTRODUCTION: The U.S. healthcare system remains vulnerable to crisis and troubled by resource inequities. Uneven distribution and scarcity of critical care (CC) clinicians is one example: COVID19 overwhelmed many hospitals with critically ill patients forcing some clinicians to provide care beyond their normal scope of practice and level of comfort. METHODS: The National Emergency Tele-Critical Care Network (NETCCN) was developed to address this problem by providing on-demand access to CC experts. NETCCN was funded by the Coronavirus, Aid, Relief, and Economic Security (CARES) Act;as a collaboration between the U.S. Army's Telemedicine and Advanced Technology Research Center (TATRC), the Department of Health and Human Services Assistant Secretary for Preparedness and Response (HHS ASPR), and the Society of Critical Care Medicine (SCCM). NETCCN focused on rapid development and deployment of technology platforms that were simple and user-friendly, cyber-secure, and HIPAA compliant, and only required a cellular connected mobile device. This federally funded resource allowed local non-CC caregivers to consult with CC experts. RESULTS: NETCCN has deployed to six states/territories, eight hospitals and cared for hundreds of patients in locations unfamiliar with managing critically-ill patients. While limited in scope, the NETCCN experience highlights key challenges and successes to address or sustain moving forward. Fear commonly prevented wider acceptance and use of NETCCN support. Clinicians fear judgment when asking questions;hospital administrators fear violating laws or disrupting “normal” practice patterns;and provider groups fear loss of market share. Despite laws that permit expedience during disaster conditions, major policy barriers, particularly local credentialing and privileging processes, hinder the use of tele-CC consultation solutions. Finally, lack of consistent federal, state, and local telehealth policies, especially for in-patient and e-consult services, caused confusion and prevented wider deployment of NETCCN. CONCLUSIONS: A federal capability that provides telemedicine support to hospitals or communities in crisis as part of a disaster response system is feasible, but policy barriers and cultural expectations impede rapid adoption.

8.
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.

9.
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. 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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.

10.
Integrative and Comparative Biology ; 61:E274-E275, 2021.
Article in English | Web of Science | ID: covidwho-1250176
11.
Hepatology ; 72(1 SUPPL):607A-608A, 2020.
Article in English | EMBASE | ID: covidwho-986099

ABSTRACT

Background: Stigma and poor linkage to care, amplified in the setting of the COVID-19 pandemic, are significant barriers for treating hepatitis C (HCV) in vulnerable patients, reducing our ability to implement a rapid test and treat (TnT) strategy with minimal monitoring within a simple patient cascade, as currently available HCV therapies would allow us to do This real-world analysis evaluates our ability to implement this approach in both general (GP) and vulnerable (VP) populations Methods: HCV-infected patients from 32 clinical cohorts in 8 countries treated with sofosbuvir/ velpatasvir without a history of decompensation or prior NS5A-inhibitor exposure were included in this analysis The VP included prisoners, homeless patients and patients with mental disorders Time to treatment (TT) between the most recent HCV RNA measurement and treatment initiation was estimated based on available data Results: A total of 2449 patients were included, 937 in GP (58% males), 1512 (72% males) in VP (59% with mental disorders, 31% homeless, 10% imprisoned) Mean age [standard deviation] was 55 [14] and 50 [14] years in GP and VP respectively Genotype 3 was observed in 35% and 33% respectively, compensated cirrhosis confirmed in 20% and 18% of GP versus VP. The median TT [MTT, interquartile range] was 55 days [23- 107] in GP and 60 days [27-132] in VP The longest MTT of 66 days [32-134] was observed in patients with mental disorders MTT was 63 days [29-149] in prisoners and 27 days [13-71] among the homeless Only 13% of GP and 8% of VP were treated the same day of diagnosis, and 70% of GP and 63% of VP were treated within 3 months In patients with mental disorders only 4% were treated the same day of diagnosis Cure rates were high and consistent with previously reported cure rates Conclusion: MTT varies across HCV patient groups, from over 6 months to 1 day This analysis shows that a quick treatment start is possible, both in general population and in vulnerable populations, supporting the feasibility of a TnT approach in all populations New strategies should be considered to engage patients with mental disorders in this model of care more effectively.

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