Management and leadership in UK universities: exploring the possibilities of change

This paper considers the case for reform of management struc- tures in UK universities and offers proposals for change. The model of top-down, performance-led management that characterises many institutions is both outmoded and ill-suited to the chal- lenges of an increasingly turbulent higher education sector. Drawing on the experiences of a university that introduced a new scheme of performance management, I explore alternative approaches to leadership and management, collaborative or part- nership working designed to improve employee voice and the need to re-evaluate approaches to Human Resource Management. I conclude with a five-point model for change

The impact of COVID-19 critical illness on new disability, functional outcomes and return to work at 6 months: a prospective cohort study

Background: There are few reports of new functional impairment following critical illness from COVID-19. We aimed to describe the incidence of death or new disability, functional impairment and changes in health-related quality of life of patients after COVID-19 critical illness at 6 months. Methods: In a nationally representative, multicenter, prospective cohort study of COVID-19 critical illness, we determined the prevalence of death or new disability at 6 months, the primary outcome. We measured mortality, new disability and return to work with changes in the World Health Organization Disability Assessment Schedule 2.0 12L (WHODAS) and health status with the EQ5D-5LTM. Results: Of 274 eligible patients, 212 were enrolled from 30 hospitals. The median age was 61 (51–70) years, and 124 (58.5%) patients were male. At 6 months, 43/160 (26.9%) patients died and 42/108 (38.9%) responding survivors reported new disability. Compared to pre-illness, the WHODAS percentage score worsened (mean difference (MD), 10.40% [95% CI 7.06–13.77]; p < 0.001). Thirteen (11.4%) survivors had not returned to work due to poor health. There was a decrease in the EQ-5D-5LTM utility score (MD, − 0.19 [− 0.28 to − 0.10]; p < 0.001). At 6 months, 82 of 115 (71.3%) patients reported persistent symptoms. The independent predictors of death or new disability were higher severity of illness and increased frailty. Conclusions: At six months after COVID-19 critical illness, death and new disability was substantial. Over a third of survivors had new disability, which was widespread across all areas of functioning.Carol L. Hodgson, Alisa M. Higgins, Michael J. Bailey, Anne M. Mather, Lisa Beach, Rinaldo Bellomo, Bernie Bissett, Ianthe J. Boden, Scott Bradley, Aidan Burrell, D. James Cooper, Bentley J. Fulcher, Kimberley J. Haines, Jack Hopkins, Alice Y. M. Jones, Stuart Lane, Drew Lawrence, Lisa van der Lee, Jennifer Liacos, Natalie J. Linke, Lonni Marques Gomes, Marc Nickels, George Ntoumenopoulos, Paul S. Myles, Shane Patman, Michelle Paton, Gemma Pound, Sumeet Rai, Alana Rix, Thomas C. Rollinson, Janani Sivasuthan, Claire J. Tipping, Peter Thomas, Tony Trapani, Andrew A. Udy, Christina Whitehead, Isabelle T. Hodgson, Shannah Anderson, Ary Serpa Neto, and The COVID-Recovery Study Investigators and the ANZICS Clinical Trials Grou

Year 2030: What Is the Future of Animal Surveillance in Scotland?

In this report, we present a description of foresighting activities undertaken by EPIC, Scotland’s Centre of Expertise on Animal Disease Outbreaks, to investigate the future uncertainty of animal health surveillance in Scotland over the long-term (i.e. 2030). Using scenario planning methodologies, we explored five plausible long-term futures to identify opportunities and challenges for early diagnosis and detection of exotic, endemic and novel animal and zoonotic diseases. These scenarios highlighted critical drivers that influence the provision of animal health surveillance services including: international trade policy (i.e. globalist versus isolationist world views), data sharing philosophies (i.e. integrated versus segregated data sharing) and private versus public resourcing of surveillance capacity. Although not an original aim, the timing of the workshop meant that all of these futures also incorporated a vision of Scotland (and Scottish agriculture) in a post-Brexit world and considered the associated long-term policy and economic uncertainties this creates for the sustainability of different livestock sectors. Participants in the scenario planning exercises proposed creative strategies which might either address perceived gaps in future resilience or maximise opportunities to augment surveillance resilience in each different future. Using these participant-led proposals as a starting point, we evaluated the strengths and weaknesses of ten strategies (and their feasibility, effectiveness and relevance) to improve the resilience of the long-term future of animal health surveillance and contingency planning for animal and zoonotic disease outbreaks in Scotland. We conclude by proposing a set of five important criteria which in combination, may signal on which future path Scotland is travelling and inform decisions about which of the proposed strategies make the best investment for the long-term

Year 2030: What Is the Future of Animal Surveillance in Scotland?

In this report, we present a description of foresighting activities undertaken by EPIC, Scotland’s Centre of Expertise on Animal Disease Outbreaks, to investigate the future uncertainty of animal health surveillance in Scotland over the long-term (i.e. 2030). Using scenario planning methodologies, we explored five plausible long-term futures to identify opportunities and challenges for early diagnosis and detection of exotic, endemic and novel animal and zoonotic diseases. These scenarios highlighted critical drivers that influence the provision of animal health surveillance services including: international trade policy (i.e. globalist versus isolationist world views), data sharing philosophies (i.e. integrated versus segregated data sharing) and private versus public resourcing of surveillance capacity. Although not an original aim, the timing of the workshop meant that all of these futures also incorporated a vision of Scotland (and Scottish agriculture) in a post-Brexit world and considered the associated long-term policy and economic uncertainties this creates for the sustainability of different livestock sectors. Participants in the scenario planning exercises proposed creative strategies which might either address perceived gaps in future resilience or maximise opportunities to augment surveillance resilience in each different future. Using these participant-led proposals as a starting point, we evaluated the strengths and weaknesses of ten strategies (and their feasibility, effectiveness and relevance) to improve the resilience of the long-term future of animal health surveillance and contingency planning for animal and zoonotic disease outbreaks in Scotland. We conclude by proposing a set of five important criteria which in combination, may signal on which future path Scotland is travelling and inform decisions about which of the proposed strategies make the best investment for the long-term

FAIR data pipeline : provenance-driven data management for traceable scientific workflows

Modern epidemiological analyses to understand and combat the spread of disease depend critically on access to, and use of, data. Rapidly evolving data, such as data streams changing during a disease outbreak, are particularly challenging. Data management is further complicated by data being imprecisely identified when used. Public trust in policy decisions resulting from such analyses is easily damaged and is often low, with cynicism arising where claims of ‘following the science’ are made without accompanying evidence. Tracing the provenance of such decisions back through open software to primary data would clarify this evidence, enhancing the transparency of the decision-making process. Here, we demonstrate a Findable, Accessible, Interoperable and Reusable (FAIR) data pipeline. Although developed during the COVID-19 pandemic, it allows easy annotation of any data as they are consumed by analyses, or conversely traces the provenance of scientific outputs back through the analytical or modelling source code to primary data. Such a tool provides a mechanism for the public, and fellow scientists, to better assess scientific evidence by inspecting its provenance, while allowing scientists to support policymakers in openly justifying their decisions. We believe that such tools should be promoted for use across all areas of policy-facing research. This article is part of the theme issue ‘Technical challenges of modelling real-life epidemics and examples of overcoming these’

A search for doubly charged higgs production in z0 decays

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