Unrealised fears: monitoring museum closure and reopening in the UK during the Covid-19 pandemic

Fears of widespread permanent closures of museums expressed at the start of the Covid-19 pandemic prompted our research to monitor closures and other museum behaviour in 2021–2022. We wanted to understand how the UK sector changed in this period. Which museums closed, and what factors were at work in their closure? Did museums that closed have anything in common? Were there trends or patterns across the sector? To monitor as widely as possible we conducted an experimental analysis of the sector using website scraping and machine learning to perform large-scale data collection and analysis. We found that museums did not close in the numbers expected; on the contrary, during the pandemic fewer museums closed than in previous years and we reflect on the likely reasons for this. Although the pandemic functioned as our case study, our methods are potentially applicable to other situations requiring whole-sector monitoring of museums’ behaviour.

Authors

Publication Details

Journal
BIROn (Birkbeck, University of London)
Published
2026-04-13
Primary Topic
Museums and Cultural Heritage
Type
article
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article

Unrealised fears: monitoring museum closure and reopening in the UK during the Covid-19 pandemic

Fiona Candlin, Alex Poulovassilis, Jamie Larkin, Andrea Ballatore et al.
BIROn (Birkbeck, University of London)
Museums and Cultural Heritage
article

Unrealised fears: monitoring museum closure and reopening in the UK during the Covid-19 pandemic

Fiona Candlin, Alex Poulovassilis, Jamie Larkin, Andrea Ballatore, Mark Liebenrood, Peter Wood
article en

Abstract

Fears of widespread permanent closures of museums expressed at the start of the Covid-19 pandemic prompted our research to monitor closures and other museum behaviour in 2021–2022. We wanted to understand how the UK sector changed in this period. Which museums closed, and what factors were at work in their closure? Did museums that closed have anything in common? Were there trends or patterns across the sector? To monitor as widely as possible we conducted an experimental analysis of the sector using website scraping and machine learning to perform large-scale data collection and analysis. We found that museums did not close in the numbers expected; on the contrary, during the pandemic fewer museums closed than in previous years and we reflect on the likely reasons for this. Although the pandemic functioned as our case study, our methods are potentially applicable to other situations requiring whole-sector monitoring of museums’ behaviour.

BIROn (Birkbeck, University of London)
Good health and well-being
Openalex Percentile: Top 5%
Museums and Cultural Heritage
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