Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic [version 1; peer review: 2 approved]

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,...

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Main Authors: Carl A B Pearson, Anne Cori, Christopher Overton, Sabine van Elsland, Christopher I Jarvis, Edward M Hill, Dale Weston, Edward Knock, Kiesha Prem, Sam Abbott, Joel Hellewell, Sebastian Funk, Elizabeth Fearon, Julián Villabona Arenas, W John Edmunds, Michelle Kendall, Li Pi, Nicholas Davies, Neil Ferguson, Timothy Russell, Rosalind M Eggo, Yang Liu, Adam Kucharski, Marc Baguelin, Katharine Sherratt, Emily Nightingale, Anna C Carnegie
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語言:英语
出版: Wellcome 2024-01-01
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在線閱讀:https://wellcomeopenresearch.org/articles/9-12/v1
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author Carl A B Pearson
Anne Cori
Christopher Overton
Sabine van Elsland
Christopher I Jarvis
Edward M Hill
Dale Weston
Edward Knock
Kiesha Prem
Sam Abbott
Joel Hellewell
Sebastian Funk
Elizabeth Fearon
Julián Villabona Arenas
W John Edmunds
Michelle Kendall
Li Pi
Nicholas Davies
Neil Ferguson
Timothy Russell
Rosalind M Eggo
Yang Liu
Adam Kucharski
Marc Baguelin
Katharine Sherratt
Emily Nightingale
Anna C Carnegie
author_facet Carl A B Pearson
Anne Cori
Christopher Overton
Sabine van Elsland
Christopher I Jarvis
Edward M Hill
Dale Weston
Edward Knock
Kiesha Prem
Sam Abbott
Joel Hellewell
Sebastian Funk
Elizabeth Fearon
Julián Villabona Arenas
W John Edmunds
Michelle Kendall
Li Pi
Nicholas Davies
Neil Ferguson
Timothy Russell
Rosalind M Eggo
Yang Liu
Adam Kucharski
Marc Baguelin
Katharine Sherratt
Emily Nightingale
Anna C Carnegie
author_sort Carl A B Pearson
collection DOAJ
container_title Wellcome Open Research
description 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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spelling doaj-art-a344f96cc2b942b59dccc92d2f68f73e2025-08-19T23:03:09ZengWellcomeWellcome Open Research2398-502X2024-01-01910.12688/wellcomeopenres.19601.121712Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic [version 1; peer review: 2 approved]Carl A B Pearson0https://orcid.org/0000-0003-0701-7860Anne Cori1Christopher Overton2Sabine van Elsland3https://orcid.org/0000-0003-0775-7463Christopher I Jarvis4Edward M Hill5https://orcid.org/0000-0002-2992-2004Dale Weston6Edward Knock7Kiesha Prem8https://orcid.org/0000-0003-0528-798XSam Abbott9https://orcid.org/0000-0001-8057-8037Joel Hellewell10Sebastian Funk11https://orcid.org/0000-0002-2842-3406Elizabeth Fearon12Julián Villabona Arenas13W John Edmunds14Michelle Kendall15Li Pi16https://orcid.org/0000-0001-7818-408XNicholas Davies17Neil Ferguson18Timothy Russell19https://orcid.org/0000-0001-5610-6080Rosalind M Eggo20Yang Liu21https://orcid.org/0000-0002-9368-0425Adam Kucharski22Marc Baguelin23Katharine Sherratt24https://orcid.org/0000-0003-2049-3423Emily Nightingale25https://orcid.org/0000-0002-9265-1841Anna C Carnegie26https://orcid.org/0000-0002-6385-7795Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UKAll Hazards Intelligence, Data Analytics and Surveillance, UK Health Security Agency, London, UKMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKWarwick Mathematics Institute and The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, University of Warwick, Coventry, UKEmergency Response Department Science & Technology Behavioural Science, UK Health Security Agency, London, UKMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKInstitute for Global Health, University College London, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKWarwick Mathematics Institute and The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, University of Warwick, Coventry, UKBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKCentre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UKBackground 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.https://wellcomeopenresearch.org/articles/9-12/v1modelling COVID-19 pandemic responseeng
spellingShingle Carl A B Pearson
Anne Cori
Christopher Overton
Sabine van Elsland
Christopher I Jarvis
Edward M Hill
Dale Weston
Edward Knock
Kiesha Prem
Sam Abbott
Joel Hellewell
Sebastian Funk
Elizabeth Fearon
Julián Villabona Arenas
W John Edmunds
Michelle Kendall
Li Pi
Nicholas Davies
Neil Ferguson
Timothy Russell
Rosalind M Eggo
Yang Liu
Adam Kucharski
Marc Baguelin
Katharine Sherratt
Emily Nightingale
Anna C Carnegie
Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic [version 1; peer review: 2 approved]
modelling
COVID-19
pandemic response
eng
title Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic [version 1; peer review: 2 approved]
title_full Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic [version 1; peer review: 2 approved]
title_fullStr Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic [version 1; peer review: 2 approved]
title_full_unstemmed Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic [version 1; peer review: 2 approved]
title_short Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic [version 1; peer review: 2 approved]
title_sort improving modelling for epidemic responses reflections from members of the uk infectious disease modelling community on their experiences during the covid 19 pandemic version 1 peer review 2 approved
topic modelling
COVID-19
pandemic response
eng
url https://wellcomeopenresearch.org/articles/9-12/v1
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