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Moloney G, Eyre DW, Mac Aogáin M, McElroy MC, Vaughan A, Peto TE, Crook DW, Rogers TR. Human and Porcine Transmission of Clostridioides difficile Ribotype 078, Europe. Emerg Infect Dis 2021; 27:2294-2300. [PMID: 34423760 PMCID: PMC8386809 DOI: 10.3201/eid2709.203468] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Genomic analysis of a diverse collection of Clostridioides difficile ribotype 078 isolates from Ireland and 9 countries in Europe provided evidence for complex regional and international patterns of dissemination that are not restricted to humans. These isolates are associated with C. difficile colonization and clinical illness in humans and pigs.
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Evans S, Agnew E, Vynnycky E, Stimson J, Bhattacharya A, Rooney C, Warne B, Robotham J. The impact of testing and infection prevention and control strategies on within-hospital transmission dynamics of COVID-19 in English hospitals. Philos Trans R Soc Lond B Biol Sci 2021; 376:20200268. [PMID: 34053255 PMCID: PMC8165586 DOI: 10.1098/rstb.2020.0268] [Citation(s) in RCA: 54] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/15/2021] [Indexed: 12/31/2022] Open
Abstract
Nosocomial transmission of SARS-CoV-2 is a key concern, and evaluating the effect of testing and infection prevention and control strategies is essential for guiding policy in this area. Using a within-hospital SEIR transition model of SARS-CoV-2 in a typical English hospital, we estimate that between 9 March 2020 and 17 July 2020 approximately 20% of infections in inpatients, and 73% of infections in healthcare workers (HCWs) were due to nosocomial transmission. Model results suggest that placing suspected COVID-19 patients in single rooms or bays has the potential to reduce hospital-acquired infections in patients by up to 35%. Periodic testing of HCWs has a smaller effect on the number of hospital-acquired COVID-19 cases in patients, but reduces infection in HCWs by as much as 37% and results in only a small proportion of staff absences (approx. 0.3% per day). This is considerably less than the 20-25% of staff that have been reported to be absent from work owing to suspected COVID-19 and self-isolation. Model-based evaluations of interventions, informed by data collected so far, can help to inform policy as the pandemic progresses and help prevent transmission in the vulnerable hospital population. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.
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Affiliation(s)
- Stephanie Evans
- Modelling and Economics Unit, National Infection Service, Public Health England, London, UK
- Healthcare Associated Infection and Antimicrobial Resistance Division, National Infection Service, Public Health England, London, UK
| | - Emily Agnew
- Modelling and Economics Unit, National Infection Service, Public Health England, London, UK
- Healthcare Associated Infection and Antimicrobial Resistance Division, National Infection Service, Public Health England, London, UK
| | - Emilia Vynnycky
- Modelling and Economics Unit, National Infection Service, Public Health England, London, UK
- TB Modelling Group, TB Centre and Centre for Mathematical Modelling of Infectious Diseases, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - James Stimson
- Modelling and Economics Unit, National Infection Service, Public Health England, London, UK
- Healthcare Associated Infection and Antimicrobial Resistance Division, National Infection Service, Public Health England, London, UK
| | - Alex Bhattacharya
- Healthcare Associated Infection and Antimicrobial Resistance Division, National Infection Service, Public Health England, London, UK
| | | | - Ben Warne
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Julie Robotham
- Modelling and Economics Unit, National Infection Service, Public Health England, London, UK
- Healthcare Associated Infection and Antimicrobial Resistance Division, National Infection Service, Public Health England, London, UK
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford in partnership with Public Health England, Oxford, UK
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