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Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic.
Sherratt, Katharine; Carnegie, Anna C; Kucharski, Adam; Cori, Anne; Pearson, Carl A B; Jarvis, Christopher I; Overton, Christopher; Weston, Dale; Hill, Edward M; Knock, Edward; Fearon, Elizabeth; Nightingale, Emily; Hellewell, Joel; Edmunds, W John; Villabona Arenas, Julián; Prem, Kiesha; Pi, Li; Baguelin, Marc; Kendall, Michelle; Ferguson, Neil; Davies, Nicholas; Eggo, Rosalind M; van Elsland, Sabine; Russell, Timothy; Funk, Sebastian; Liu, Yang; Abbott, Sam.
Afiliação
  • Sherratt K; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
  • Carnegie AC; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
  • Kucharski A; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
  • Cori A; MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
  • Pearson CAB; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
  • Jarvis CI; South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, Western Cape, South Africa.
  • Overton C; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
  • Weston D; All Hazards Intelligence, Data Analytics and Surveillance, UK Health Security Agency, London, UK.
  • Hill EM; Department of Mathematical Sciences, University of Liverpool, Liverpool, UK.
  • Knock E; Department of Mathematics, The University of Manchester, Manchester, UK.
  • Fearon E; Emergency Response Department Science & Technology Behavioural Science, UK Health Security Agency, London, UK.
  • Nightingale E; Warwick Mathematics Institute and The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, University of Warwick, Coventry, UK.
  • Hellewell J; Joint UNIversities Pandemic and Epidemiological Research, JUNIPER, https://maths.org/juniper/, UK.
  • Edmunds WJ; MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
  • Villabona Arenas J; Institute for Global Health, University College London, London, UK.
  • Prem K; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
  • Pi L; European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
  • Baguelin M; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
  • Kendall M; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
  • Ferguson N; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
  • Davies N; Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
  • Eggo RM; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
  • van Elsland S; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
  • Russell T; MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
  • Funk S; Warwick Mathematics Institute and The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, University of Warwick, Coventry, UK.
  • Liu Y; MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
  • Abbott S; Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK.
Wellcome Open Res ; 9: 12, 2024.
Article em En | MEDLINE | ID: mdl-38784437
ABSTRACT

Background:

The COVID-19 pandemic both relied and placed significant burdens on the experts involved from research and public health sectors. The sustained high pressure of a pandemic on responders, such as healthcare workers, can lead to lasting psychological impacts including acute stress disorder, post-traumatic stress disorder, burnout, and moral injury, which can impact individual wellbeing and productivity.

Methods:

As members of the infectious disease modelling community, we convened a reflective workshop to understand the professional and personal impacts of response work on our community and to propose recommendations for future epidemic responses. The attendees represented a range of career stages, institutions, and disciplines. This piece was collectively produced by those present at the session based on our collective experiences.

Results:

Key issues we identified at the workshop were lack of institutional support, insecure contracts, unequal credit and recognition, and mental health impacts. Our recommendations include rewarding impactful work, fostering academia-public health collaboration, decreasing dependence on key individuals by developing teams, increasing transparency in decision-making, and implementing sustainable work practices.

Conclusions:

Despite limitations in representation, this workshop provided valuable insights into the UK COVID-19 modelling experience and guidance for future public health crises. Recognising and addressing the issues highlighted is crucial, in our view, for ensuring the effectiveness of epidemic response work in the future.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Wellcome Open Res Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Wellcome Open Res Ano de publicação: 2024 Tipo de documento: Article