'Cocooning' in prison during COVID-19: Findings from recent research in Ireland.
Joe GarrihyIan MarderPatricia GilheaneyPublished in: European journal of criminology (2022)
The advent of COVID-19 prompted the enforced isolation of elderly and vulnerable populations around the world, for their own safety. For people in prison, these restrictions risked compounding the isolation and harm they experienced. At the same time, the pandemic created barriers to prison oversight when it was most needed to ensure that the state upheld the rights and wellbeing of those in custody. This article reports findings from a unique collaboration in Ireland between the Office of the Inspector of Prisons - a national prison oversight body - and academic criminologists. Early in the pandemic, they cooperated to hear the voices of people 'cocooning' - isolated because of their advanced age or a medical vulnerability - in Irish prisons by providing journals to this cohort, analysing the data, and encouraging the Irish Prison Service to change practices accordingly. The findings indicated that 'cocooners' were initially ambivalent about these new restrictions, both experiencing them as a punishment akin to solitary confinement, and understanding the goal of protection. As time passed, however, participants reported a drastic impact on their mental and physical health, and implications for their (already limited) agency and relationships with others, experienced more or less severely depending on staff and management practices. The paper also discusses the implications for prison practices during and following the pandemic, understanding isolation in the penological context, and collaboration between prison oversight bodies and academics.
Keyphrases
- coronavirus disease
- healthcare
- sars cov
- mental health
- primary care
- public health
- physical activity
- general practice
- randomized controlled trial
- climate change
- systematic review
- emergency department
- respiratory syndrome coronavirus
- electronic health record
- health information
- machine learning
- deep learning
- human health
- genetic diversity
- data analysis
- long term care