Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic.

Journal: Wellcome open research

Volume: 9

Issue: 

Year of Publication: 

Affiliated Institutions:  Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene & Tropical Medicine, London, UK. MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK. All Hazards Intelligence, Data Analytics and Surveillance, UK Health Security Agency, London, UK. Emergency Response Department Science & Technology Behavioural Science, UK Health Security Agency, London, UK. Warwick Mathematics Institute and The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, University of Warwick, Coventry, UK. Institute for Global Health, University College London, London, UK. European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK. Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.

Abstract summary 

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.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.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.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.

Authors & Co-authors:  Sherratt Katharine K Carnegie Anna C AC Kucharski Adam A Cori Anne A Pearson Carl A B CAB Jarvis Christopher I CI Overton Christopher C Weston Dale D Hill Edward M EM Knock Edward E Fearon Elizabeth E Nightingale Emily E Hellewell Joel J Edmunds W John WJ Villabona Arenas Julián J Prem Kiesha K Pi Li L Baguelin Marc M Kendall Michelle M Ferguson Neil N Davies Nicholas N Eggo Rosalind M RM van Elsland Sabine S Russell Timothy T Funk Sebastian S Liu Yang Y Abbott Sam S

Study Outcome 

Source Link: Visit source

Statistics
Citations :  Whitty CJM, Collet-Fenson LB: Formal and informal science advice in emergencies: COVID-19 in the UK. Interface Focus. 2021;11(6): 20210059. 10.1098/rsfs.2021.0059
Authors :  27
Identifiers
Doi : 12
SSN : 2398-502X
Study Population
Male,Female
Mesh Terms
Other Terms
COVID-19;modelling;pandemic response
Study Design
Study Approach
Country of Study
Publication Country
England