Insights gained from early modelling of COVID-19 to inform the management of outbreaks in UK prisons

PHE Joint Modelling Team

Research output: Contribution to journalArticlepeer-review

Abstract

PURPOSE: In this work, the authors present some of the key results found during early efforts to model the COVID-19 outbreak inside a UK prison. In particular, this study describes outputs from an idealised disease model that simulates the dynamics of a COVID-19 outbreak in a prison setting when varying levels of social interventions are in place, and a Monte Carlo-based model that assesses the reduction in risk of case importation, resulting from a process that requires incoming prisoners to undergo a period of self-isolation prior to admission into the general prison population. 

DESIGN/METHODOLOGY/APPROACH: Prisons, typically containing large populations confined in a small space with high degrees of mixing, have long been known to be especially susceptible to disease outbreaks. In an attempt to meet rising pressures from the emerging COVID-19 situation in early 2020, modellers for Public Health England's Joint Modelling Cell were asked to produce some rapid response work that sought to inform the approaches that Her Majesty's Prison and Probation Service (HMPPS) might take to reduce the risk of case importation and sustained transmission in prison environments. FINDINGS: Key results show that deploying social interventions has the potential to considerably reduce the total number of infections, while such actions could also reduce the probability that an initial infection will propagate into a prison-wide outbreak. For example, modelling showed that a 50% reduction in the risk of transmission (compared to an unmitigated outbreak) could deliver a 98% decrease in total number of cases, while this reduction could also result in 86.8% of outbreaks subsiding before more than five persons have become infected. Furthermore, this study also found that requiring new arrivals to self-isolate for 10 and 14 days prior to admission could detect up to 98% and 99% of incoming infections, respectively. 

RESEARCH LIMITATIONS/IMPLICATIONS: In this paper we have presented models which allow for the studying of COVID-19 in a prison scenario, while also allowing for the assessment of proposed social interventions. By publishing these works, the authors hope these methods might aid in the management of prisoners across additional scenarios and even during subsequent disease outbreaks. Such methods as described may also be readily applied use in other closed community settings. 

ORIGINALITY/VALUE: These works went towards informing HMPPS on the impacts that the described strategies might have during COVID-19 outbreaks inside UK prisons. The works described herein are readily amendable to the study of a range of addition outbreak scenarios. There is also room for these methods to be further developed and built upon which the timeliness of the original project did not permit.

Original languageEnglish
JournalInternational Journal of Prisoner Health
Volumeahead-of-print
Issue numberaheadofprint
DOIs
Publication statusPublished - 3 Aug 2021

Bibliographical note

Funding Information: No Funding Information

Open Access: This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Publisher Copyright: © Declan Bays, Hannah Williams, Lorenzo Pellis, Jacob Curran-Sebastian, Oscar O'Mara, PHE Joint Modelling Team and Thomas Finnie. Published by Emerald Publishing Limited.

Citation: Bays, D., Williams, H., Pellis, L., Curran-Sebastian, J., O'Mara, O., Team, P.J.M. and Finnie, T. (2021), "Insights gained from early modelling of COVID-19 to inform the management of outbreaks in UK prisons", International Journal of Prisoner Health, Vol. ahead-of-print No. ahead-of-print.

DOI: https://doi.org/10.1108/IJPH-09-2020-0075

Keywords

  • Covid-19
  • Health in prison
  • Health policy
  • Infectious disease
  • Modelling
  • Prisoner health

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