9 results on '"Weekes, Michael P."'
Search Results
2. Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections
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Illingworth, Christopher JR, primary, Hamilton, William L, additional, Warne, Ben, additional, Routledge, Matthew, additional, Popay, Ashley, additional, Jackson, Chris, additional, Fieldman, Tom, additional, Meredith, Luke W, additional, Houldcroft, Charlotte J, additional, Hosmillo, Myra, additional, Jahun, Aminu S, additional, Caller, Laura G, additional, Caddy, Sarah L, additional, Yakovleva, Anna, additional, Hall, Grant, additional, Khokhar, Fahad A, additional, Feltwell, Theresa, additional, Pinckert, Malte L, additional, Georgana, Iliana, additional, Chaudhry, Yasmin, additional, Curran, Martin D, additional, Parmar, Surendra, additional, Sparkes, Dominic, additional, Rivett, Lucy, additional, Jones, Nick K, additional, Sridhar, Sushmita, additional, Forrest, Sally, additional, Dymond, Tom, additional, Grainger, Kayleigh, additional, Workman, Chris, additional, Ferris, Mark, additional, Gkrania-Klotsas, Effrossyni, additional, Brown, Nicholas M, additional, Weekes, Michael P, additional, Baker, Stephen, additional, Peacock, Sharon J, additional, Goodfellow, Ian G, additional, Gouliouris, Theodore, additional, de Angelis, Daniela, additional, and Török, M Estée, additional
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- 2021
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3. Human cytomegalovirus interactome analysis identifies degradation hubs, domain associations and viral protein functions
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Nobre, Luis V, primary, Nightingale, Katie, additional, Ravenhill, Benjamin J, additional, Antrobus, Robin, additional, Soday, Lior, additional, Nichols, Jenna, additional, Davies, James A, additional, Seirafian, Sepehr, additional, Wang, Eddie CY, additional, Davison, Andrew J, additional, Wilkinson, Gavin WG, additional, Stanton, Richard J, additional, Huttlin, Edward L, additional, and Weekes, Michael P, additional
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- 2019
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4. Single-dose BNT162b2 vaccine protects against asymptomatic SARS-CoV-2 infection.
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Jones, Nick K., Rivett, Lucy, Seaman, Shaun, Samworth, Richard J., Warne, Ben, Workman, Chris, Ferris, Mark, Wright, Jo, Quinnell, Natalie, Shaw, Ashley, Goodfellow, Ian G., Lehner, Paul J., Howes, Rob, Wright, Giles, Matheson, Nicholas J., and Weekes, Michael P.
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- 2021
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5. Control of immune ligands by members of a cytomegalovirus gene expansion suppresses natural killer cell activation
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Fielding, Ceri A, primary, Weekes, Michael P, additional, Nobre, Luis V, additional, Ruckova, Eva, additional, Wilkie, Gavin S, additional, Paulo, Joao A, additional, Chang, Chiwen, additional, Suárez, Nicolás M, additional, Davies, James A, additional, Antrobus, Robin, additional, Stanton, Richard J, additional, Aicheler, Rebecca J, additional, Nichols, Hester, additional, Vojtesek, Borek, additional, Trowsdale, John, additional, Davison, Andrew J, additional, Gygi, Steven P, additional, Tomasec, Peter, additional, Lehner, Paul J, additional, and Wilkinson, Gavin W G, additional
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- 2017
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6. Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections
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Stephen Baker, Grant Hall, Nicholas M. Brown, Aminu S Jahun, Lucy Rivett, Luke W. Meredith, Charlotte J. Houldcroft, Sally Forrest, William L Hamilton, Iliana Georgana, Daniela de Angelis, Malte L Pinckert, Michael P. Weekes, Yasmin Chaudhry, Nick K Jones, M. Estée Török, Anna Yakovleva, Sarah L Caddy, Laura G Caller, Mark Ferris, Ashley Popay, Theresa Feltwell, Tom Fieldman, Matthew Routledge, Tom Dymond, Martin D. Curran, Christopher Jackson, Myra Hosmillo, Sharon J. Peacock, Chris Workman, Christopher J. R. Illingworth, Sushmita Sridhar, Theodore Gouliouris, Effrossyni Gkrania-Klotsas, Dominic Sparkes, Fahad A Khokhar, Ben Warne, Ian Goodfellow, Kayleigh Grainger, Surendra Parmar, Illingworth, Christopher JR [0000-0002-0030-2784], Hamilton, William L [0000-0002-3330-353X], Houldcroft, Charlotte J [0000-0002-1833-5285], Hosmillo, Myra [0000-0002-3514-7681], Jahun, Aminu S [0000-0002-4585-1701], Caddy, Sarah L [0000-0002-9790-7420], Hall, Grant [0000-0003-3928-3979], Georgana, Iliana [0000-0002-8976-1177], Rivett, Lucy [0000-0002-2781-9345], Jones, Nick K [0000-0003-4475-7761], Sridhar, Sushmita [0000-0001-7453-7482], Ferris, Mark [0000-0001-5040-4263], Gkrania-Klotsas, Effrossyni [0000-0002-0930-8330], Brown, Nicholas M [0000-0002-6657-300X], Weekes, Michael P [0000-0003-3196-5545], Baker, Stephen [0000-0003-1308-5755], Peacock, Sharon J [0000-0002-1718-2782], Goodfellow, Ian G [0000-0002-9483-510X], Török, M Estée [0000-0001-9098-8590], Apollo - University of Cambridge Repository, and Illingworth, Christopher Jr [0000-0002-0030-2784]
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superspreader ,Male ,Coronavirus disease 2019 (COVID-19) ,QH301-705.5 ,Science ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Microbiology ,General Biochemistry, Genetics and Molecular Biology ,law.invention ,Disease Outbreaks ,03 medical and health sciences ,0302 clinical medicine ,law ,Health care ,Medicine ,Humans ,030212 general & internal medicine ,Biology (General) ,hospital ,030304 developmental biology ,Retrospective Studies ,0303 health sciences ,Infectious disease ,Evolutionary Biology ,Microbiology and Infectious Disease ,General Immunology and Microbiology ,business.industry ,SARS-CoV-2 ,General Neuroscience ,nosocomial transmission ,Outbreak ,COVID-19 ,Retrospective cohort study ,General Medicine ,Middle Aged ,University hospital ,Hospitals ,3. Good health ,Virus ,Transmission (mechanics) ,Infectious disease (medical specialty) ,Female ,business ,Demography ,Research Article - Abstract
SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures., eLife digest The COVID-19 pandemic, caused by the SARS-CoV-2 virus, presents a global public health challenge. Hospitals have been at the forefront of this battle, treating large numbers of sick patients over several waves of infection. Finding ways to manage the spread of the virus in hospitals is key to protecting vulnerable patients and workers, while keeping hospitals running, but to generate effective infection control, researchers must understand how SARS-CoV-2 spreads. A range of factors make studying the transmission of SARS-CoV-2 in hospitals tricky. For instance, some people do not present any symptoms, and, amongst those who do, it can be difficult to determine whether they caught the virus in the hospital or somewhere else. However, comparing the genetic information of the SARS-CoV-2 virus from different people in a hospital could allow scientists to understand how it spreads. Samples of the genetic material of SARS-CoV-2 can be obtained by swabbing infected individuals. If the genetic sequences of two samples are very different, it is unlikely that the individuals who provided the samples transmitted the virus to one another. Illingworth, Hamilton et al. used this information, along with other data about how SARS-CoV-2 is transmitted, to develop an algorithm that can determine how the virus spreads from person to person in different hospital wards. To build their algorithm, Illingworth, Hamilton et al. collected SARS-CoV-2 genetic data from patients and staff in a hospital, and combined it with information about how SARS-CoV-2 spreads and how these people moved in the hospital . The algorithm showed that, for the most part, patients were infected by other patients (20 out of 22 cases), while staff were infected equally by patients and staff. By further probing these data, Illingworth, Hamilton et al. revealed that 80% of hospital-acquired infections were caused by a group of just 21% of individuals in the study, identifying a ‘superspreader’ pattern. These findings may help to inform SARS-CoV-2 infection control measures to reduce spread within hospitals, and could potentially be used to improve infection control in other contexts.
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- 2021
7. Single-dose BNT162b2 vaccine protects against asymptomatic SARS-CoV-2 infection
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Jo Wright, Shaun R. Seaman, Rob Howes, Giles Wright, Mark Ferris, Paul J. Lehner, Ashley Shaw, Natalie Quinnell, Lucy Rivett, Nick K Jones, Richard J. Samworth, Michael P. Weekes, Chris Workman, Nicholas J Matheson, Ian Goodfellow, Ben Warne, Jones, Nick K [0000-0003-4475-7761], Rivett, Lucy [0000-0002-2781-9345], Goodfellow, Ian G [0000-0002-9483-510X], Lehner, Paul J [0000-0001-9383-1054], Matheson, Nicholas J [0000-0002-3318-1851], Weekes, Michael P [0000-0003-3196-5545], and Apollo - University of Cambridge Repository
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0301 basic medicine ,global health ,Disease ,0302 clinical medicine ,Pandemic ,Epidemiology ,Global health ,Medicine ,Biology (General) ,Asymptomatic Infections ,Microbiology and Infectious Disease ,Transmission (medicine) ,General Neuroscience ,Vaccination ,General Medicine ,3. Good health ,epidemiology ,medicine.symptom ,Human ,medicine.medical_specialty ,COVID-19 Vaccines ,QH301-705.5 ,Science ,infectious disease ,Health Personnel ,Immunization, Secondary ,Asymptomatic ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,Internal medicine ,Humans ,asymptomatic ,Infectious disease (athletes) ,BNT162 Vaccine ,Immunization Schedule ,General Immunology and Microbiology ,SARS-CoV-2 ,business.industry ,microbiology ,COVID-19 ,Epidemiology and Global Health ,030104 developmental biology ,BNT162b2 ,Pfizer-BioNTech ,Research Advance ,business ,030217 neurology & neurosurgery - Abstract
The BNT162b2 mRNA COVID-19 vaccine (Pfizer-BioNTech) is being utilised internationally for mass COVID-19 vaccination. Evidence of single-dose protection against symptomatic disease has encouraged some countries to opt for delayed booster doses of BNT162b2, but the effect of this strategy on rates of asymptomatic SARS-CoV-2 infection remains unknown. We previously demonstrated frequent pauci- and asymptomatic SARS-CoV-2 infection amongst healthcare workers (HCWs) during the UK’s first wave of the COVID-19 pandemic, using a comprehensive PCR-based HCW screening programme (Rivett et al., 2020; Jones et al., 2020). Here, we evaluate the effect of first-dose BNT162b2 vaccination on test positivity rates and find a fourfold reduction in asymptomatic infection amongst HCWs ≥12 days post-vaccination. These data provide real-world evidence of short-term protection against asymptomatic SARS-CoV-2 infection following a single dose of BNT162b2 vaccine, suggesting that mass first-dose vaccination will reduce SARS-CoV-2 transmission, as well as the burden of COVID-19 disease.
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- 2021
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8. Effective control of SARS-CoV-2 transmission between healthcare workers during a period of diminished community prevalence of COVID-19
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Jones, N. K., Rivett, L., Sparkes, D., Forrest, S., Sridhar, S., Young, J., Pereira-Dias, J., Cormie, C., Gill, H., Reynolds, N., Wantoch, M., Routledge, M., Warne, B., Levy, J., Jimenez, W. D. C., Samad, F. N. B., Mcnicholas, C., Ferris, M., Gray, J., Gill, M., Curran, M. D., Fuller, S., Chaudhry, A., Shaw, A., Bradley, J. R., Hannon, G. J., Goodfellow, I. G., Dougan, G., Smith, K. G. C., Lehner, P. J., Wright, G., Matheson, N. J., Baker, S., Weekes, M. P., Bradley, J., Goodfellow, I., Gupta, R., Lyons, P. A., Torok, M. E., Toshner, M., Kean, I., Caddy, S., Caller, L., Feltwell, T., Hall, G., Hamilton, W., Hosmillo, M., Houldcroft, C., Jahun, A., Khokhar, F., Meredith, L., Yakovleva, A., Butcher, H., Caputo, D., Clapham-Riley, D., Dolling, H., Furlong, A., Graves, B., Gresley, E. L., Kingston, N., Papadia, S., Stark, H., Stirrups, K. E., Webster, J., Calder, J., Harris, J., Hewitt, S., Kennet, J., Meadows, A., Rastall, R., Brien, C. O., Price, J., Publico, C., Rowlands, J., Ruffolo, V., Tordesillas, H., Hannon, G., Brookes, K., Canna, L., Cruz, I., Dempsey, K., Elmer, A., Escoffery, N., Jones, H., Ribeiro, C., Saunders, C., Wright, A., Nyagumbo, R., Roberts, A., Bucke, A., Hargreaves, S., Johnson, D., Narcorda, A., Read, D., Sparke, C., Worboys, L., Lagadu, K., Mactavous, L., Gould, T., Raine, T., Mather, C., Ramenatte, N., Vallier, A. -L., Kasanicki, M., Eames, P. -J., Thake, L., Bartholomew, N., Brown, N., Curran, M., Parmar, S., Zhang, H., Bowring, A., Martell, G., Quinnell, N., Wright, J., Murphy, H., Dunmore, B. J., Legchenko, E., Graf, S., Huang, C., Hodgson, J., Hunter, K., Martin, J., Mescia, F., Odonnell, C., Pointon, L., Shih, J., Sutcliffe, R., Tilly, T., Tong, Z., Treacy, C., Wood, J., Bergamaschi, L., Betancourt, A., Bowyer, G., De Sa, A., Epping, M., Hinch, A., Huhn, O., Jarvis, I., Lewis, D., Marsden, J., Mccallum, S., Nice, F., Omarjee, O., Perera, M., Romashova, N., Strezlecki, M., Yarkoni, N. S., Turner, L., Bailey, B., Doughton, R., Workman, C., Trotter, C., David, W., Jimenez, C., Jones, Nick K [0000-0003-4475-7761], Sridhar, Sushmita [0000-0001-7453-7482], Hannon, Gregory J [0000-0003-4021-3898], Goodfellow, Ian G [0000-0002-9483-510X], Lehner, Paul J [0000-0001-9383-1054], Matheson, Nicholas J [0000-0002-3318-1851], Weekes, Michael P [0000-0003-3196-5545], and Apollo - University of Cambridge Repository
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0301 basic medicine ,Male ,Infectious Disease Transmission ,global health ,Occupational safety and health ,Hospitals, University ,Patient-to-Professional ,0302 clinical medicine ,COVID-19 Testing ,Patient Admission ,Nasopharynx ,Pandemic ,Epidemiology ,Prevalence ,Medicine ,Infection control ,Mass Screening ,030212 general & internal medicine ,Viral ,Biology (General) ,Family Characteristics ,General Neuroscience ,Infectious ,human biology ,virus diseases ,General Medicine ,Middle Aged ,Hospitals ,3. Good health ,virology ,Community-Acquired Infections ,Occupational Diseases ,England ,epidemiology ,Female ,medicine.symptom ,Symptom Assessment ,Coronavirus Infections ,Hospital Units ,Adult ,medicine.medical_specialty ,Infectious Disease Transmission, Patient-to-Professional ,QH301-705.5 ,Health Personnel ,infectious disease ,Science ,Pneumonia, Viral ,Real-Time Polymerase Chain Reaction ,Asymptomatic ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,Betacoronavirus ,Disease Transmission ,Disease Transmission, Infectious ,Humans ,human ,Human Biology and Medicine ,Hospitals, Teaching ,Pandemics ,Mass screening ,Asymptomatic Diseases ,emerging pathogens ,University ,Infection Control ,General Immunology and Microbiology ,business.industry ,Clinical Laboratory Techniques ,SARS-CoV-2 ,Teaching ,COVID-19 ,Pneumonia ,medicine ,occupational health ,Contact Tracing ,Program Evaluation ,030104 developmental biology ,Epidemiology and Global Health ,Emergency medicine ,business ,Research Advance ,Contact tracing - Abstract
Previously, we showed that 3% (31/1032)of asymptomatic healthcare workers (HCWs) from a large teaching hospital in Cambridge, UK, tested positive for SARS-CoV-2 in April 2020. About 15% (26/169) HCWs with symptoms of coronavirus disease 2019 (COVID-19) also tested positive for SARS-CoV-2 (Rivett et al., 2020). Here, we show that the proportion of both asymptomatic and symptomatic HCWs testing positive for SARS-CoV-2 rapidly declined to near-zero between 25th April and 24th May 2020, corresponding to a decline in patient admissions with COVID-19 during the ongoing UK ‘lockdown’. These data demonstrate how infection prevention and control measures including staff testing may help prevent hospitals from becoming independent ‘hubs’ of SARS-CoV-2 transmission, and illustrate how, with appropriate precautions, organizations in other sectors may be able to resume on-site work safely.
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- 2020
9. Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission.
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Rivett L, Sridhar S, Sparkes D, Routledge M, Jones NK, Forrest S, Young J, Pereira-Dias J, Hamilton WL, Ferris M, Torok ME, Meredith L, Curran MD, Fuller S, Chaudhry A, Shaw A, Samworth RJ, Bradley JR, Dougan G, Smith KG, Lehner PJ, Matheson NJ, Wright G, Goodfellow IG, Baker S, and Weekes MP
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- Betacoronavirus physiology, COVID-19, COVID-19 Testing, COVID-19 Vaccines, Coronavirus Infections diagnosis, Coronavirus Infections epidemiology, Coronavirus Infections transmission, Female, Humans, Infection Control, Male, Pandemics, Pneumonia, Viral diagnosis, Pneumonia, Viral epidemiology, Pneumonia, Viral transmission, Real-Time Polymerase Chain Reaction, SARS-CoV-2, United Kingdom epidemiology, Asymptomatic Infections, Clinical Laboratory Techniques, Health Personnel
- Abstract
Significant differences exist in the availability of healthcare worker (HCW) SARS-CoV-2 testing between countries, and existing programmes focus on screening symptomatic rather than asymptomatic staff. Over a 3 week period (April 2020), 1032 asymptomatic HCWs were screened for SARS-CoV-2 in a large UK teaching hospital. Symptomatic staff and symptomatic household contacts were additionally tested. Real-time RT-PCR was used to detect viral RNA from a throat+nose self-swab. 3% of HCWs in the asymptomatic screening group tested positive for SARS-CoV-2. 17/30 (57%) were truly asymptomatic/pauci-symptomatic. 12/30 (40%) had experienced symptoms compatible with coronavirus disease 2019 (COVID-19)>7 days prior to testing, most self-isolating, returning well. Clusters of HCW infection were discovered on two independent wards. Viral genome sequencing showed that the majority of HCWs had the dominant lineage B∙1. Our data demonstrates the utility of comprehensive screening of HCWs with minimal or no symptoms. This approach will be critical for protecting patients and hospital staff., Competing Interests: LR, SS, DS, MR, NJ, SF, JY, JP, WH, MF, LM, MC, SF, AS, JB, GW No competing interests declared, MT Reports grants from Academy of Medical Sciences and the Health Foundation, non-financial support from National Institute of Health Research, grants from Medical Research Council, grants from Global Challenges Research Fund, personal fees from Wellcome Sanger Institute, personal fees from University of Cambridge, personal fees from Oxford University Press, AC Reports grants from Cambridge Biomedical Research Centre at CUHNFT, RS Reports grants from EPSRC fellowship, GD Reports grants from NIHR, KS, MW Reports grants from Wellcome Trust, PL, IG, SB Reports grants from Wellcome Trust and Addenbrooke's Charitable Trust, NM Reports grants from MRC (UK) and NHS Blood and Transfusion, (© 2020, Rivett et al.)
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- 2020
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