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1.
Preprint in English | medRxiv | ID: ppmedrxiv-20219642

ABSTRACT

Identifying linked cases of infection is a key part of the public health response to viral infectious disease. Viral genome sequence data is of great value in this task, but requires careful analysis, and may need to be complemented by additional types of data. The Covid-19 pandemic has highlighted the urgent need for analytical methods which bring together sources of data to inform epidemiological investigations. We here describe A2B-COVID, an approach for the rapid identification of linked cases of coronavirus infection. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and novel approaches to genome sequence data to assess whether or not cases of infection are consistent or inconsistent with linkage via transmission. We apply our method to analyse and compare data collected from two wards at Cambridge University Hospitals, showing qualitatively different patterns of linkage between cases on designated Covid-19 and non-Covid-19 wards. Our method is suitable for the rapid analysis of data from clinical or other potential outbreak settings.

2.
Preprint in English | medRxiv | ID: ppmedrxiv-20182279

ABSTRACT

COVID-19 poses a major challenge to care homes, as SARS-CoV-2 is readily transmitted and causes disproportionately severe disease in older people. Here, 1,167 residents from 337 care homes were identified from a dataset of 6,600 COVID-19 cases from the East of England. Older age and being a care home resident were associated with increased mortality. SARS-CoV-2 genomes were available for 700 residents from 292 care homes. By integrating genomic and temporal data, 409 viral clusters within the 292 homes were identified, indicating two different patterns - outbreaks among care home residents and independent introductions with limited onward transmission. Approximately 70% of residents in the genomic analysis were admitted to hospital during the study, providing extensive opportunities for transmission between care homes and hospitals. Limiting viral transmission within care homes should be a key target for infection control to reduce COVID-19 mortality in this population. Impact statementSARS-CoV-2 can spread efficiently within care homes causing COVID-19 outbreaks among residents, who are at increased risk of severe disease, emphasising the importance of stringent infection control in this population.

3.
Preprint in English | medRxiv | ID: ppmedrxiv-20082909

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), 1,032 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{middle dot}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. Appendix: The CITIID-NIHR COVID-19 BioResource CollaborationO_ST_ABSPrincipal InvestigatorsC_ST_ABSStephen Baker, John Bradley, Gordon Dougan, Ian Goodfellow, Ravi Gupta, Paul J. Lehner, Paul A. Lyons, Nicholas J. Matheson, Kenneth G.C. Smith, M. Estee Torok, Mark Toshner, Michael P. Weekes Infectious Diseases DepartmentNicholas K. Jones, Lucy Rivett, Matthew Routledge, Dominic Sparkes, Ben Warne SARS-CoV-2 testing teamJosefin Bartholdson Scott, Claire Cormie, Sally Forrest, Harmeet Gill, Iain Kean, Mailis Maes, Joana Pereira-Dias, Nicola Reynolds, Sushmita Sridhar, Michelle Wantoch, Jamie Young COG-UK Cambridge Sequencing TeamSarah Caddy, Laura Caller, Theresa Feltwell, Grant Hall, William Hamilton, Myra Hosmillo, Charlotte Houldcroft, Aminu Jahun, Fahad Khokhar, Luke Meredith, Anna Yakovleva NIHR BioResourceHelen Butcher, Daniela Caputo, Debra Clapham-Riley, Helen Dolling, Anita Furlong, Barbara Graves, Emma Le Gresley, Nathalie Kingston, Sofia Papadia, Hannah Stark, Kathleen E. Stirrups, Jennifer Webster Research nursesJoanna Calder, Julie Harris, Sarah Hewitt, Jane Kennet, Anne Meadows, Rebecca Rastall, Criona O,Brien, Jo Price, Cherry Publico, Jane Rowlands, Valentina Ruffolo, Hugo Tordesillas NIHR Cambridge Clinical Research FacilityKaren Brookes, Laura Canna, Isabel Cruz, Katie Dempsey, Anne Elmer, Naidine Escoffery, Stewart Fuller, Heather Jones, Carla Ribeiro, Caroline Saunders, Angela Wright Cambridge Cancer Trial CentreRutendo Nyagumbo, Anne Roberts Clinical Research Network EasternAshlea Bucke, Simone Hargreaves, Danielle Johnson, Aileen Narcorda, Debbie Read, Christian Sparke, Lucy Warboys Administrative staff, CUHKirsty Lagadu, Lenette Mactavous CUH NHS Foundation TrustTim Gould, Tim Raine, Ashley Shaw Cambridge Cancer Trials CentreClaire Mather, Nicola Ramenatte, Anne-Laure Vallier Legal/EthicsMary Kasanicki CUH Improvement and Transformation TeamPenelope-Jane Eames, Chris McNicholas, Lisa Thake Clinical Microbiology & Public Health Laboratory (PHE): Neil Bartholomew, Nick Brown, Martin Curran, Surendra Parmar, Hongyi Zhang Occupational HealthAilsa Bowring, Mark Ferris, Geraldine Martell, Natalie Quinnell, Giles Wright, Jo Wright Health and SafetyHelen Murphy Department of Medicine Sample LogisticsBenjamin J. Dunmore, Ekaterina Legchenko, Stefan Graf, Christopher Huang, Josh Hodgson, Kelvin Hunter, Jennifer Martin, Federica Mescia, Ciara ODonnell, Linda Pointon, Joy Shih, Rachel Sutcliffe, Tobias Tilly, Zhen Tong, Carmen Treacy, Jennifer Wood Department of Medicine Sample Processing and Acquisition: Laura Bergamaschi, Ariana Betancourt, Georgie Bowyer, Aloka De Sa, Maddie Epping, Andrew Hinch, Oisin Huhn, Isobel Jarvis, Daniel Lewis, Joe Marsden, Simon McCallum, Francescsa Nice, Ommar Omarjee, Marianne Perera, Nika Romashova, Mateusz Strezlecki, Natalia Savoinykh Yarkoni, Lori Turner Epic team/other computing supportBarrie Bailey, Afzal Chaudhry, Rachel Doughton, Chris Workman Statistics/modellingRichard J. Samworth, Caroline Trotter

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